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age-0102 | Benchmarks & Datasets | Prompt-injection evaluation | Benchmark | AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents | https://openreview.net/forum?id=m1YYAQjO3w | NeurIPS Datasets & Benchmarks | 2,024 | Edoardo Debenedetti; Jie Zhang; Mislav Balunovic; Luca Beurer-Kellner; Marc Fischer; Florian Tramèr | Provides an extensible adversarial environment with 97 realistic tasks and 629 security test cases for agents executing tools over untrusted data. | Tests the instruction-data boundary that every external-input and artifact edge must preserve; compromised peer-agent messages require separate evaluation. | Benchmark/dataset | Reliability |
age-0103 | Benchmarks & Datasets | Agent misuse benchmark | Benchmark | AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents | https://openreview.net/forum?id=AC5n7xHuR1 | ICLR | 2,025 | Maksym Andriushchenko; Alexandra Souly; Mateusz Dziemian; Derek Duenas; Maxwell Lin; Justin Wang; Dan Hendrycks; Andy Zou; J. Zico Kolter; Matt Fredrikson; Yarin Gal; Xander Davies | Evaluates refusal and retained task capability on 110 explicitly malicious multi-stage agent tasks with 440 augmented variants across 11 harm categories. | Tests whether safety gates reject prohibited work and stop a compromised node from completing a harmful path; the score is not a general measure of agent-system safety. | Benchmark/dataset | Gates |
age-0104 | Reliability & Durable Execution | Structural prompt-injection defense | Paper | IPIGuard: A Novel Tool Dependency Graph-Based Defense Against Indirect Prompt Injection in LLM Agents | https://aclanthology.org/2025.emnlp-main.53/ | EMNLP | 2,025 | Hengyu An; Jinghuai Zhang; Tianyu Du; Chunyi Zhou; Qingming Li; Tao Lin; Shouling Ji | Models task execution as traversal over a planned Tool Dependency Graph and separates action planning from interaction with untrusted external data. | Shows how structural constraints on allowed tool edges can block unauthorized actions instead of relying only on prompts or classifiers. | Peer-reviewed research | Work graphs |
age-0105 | Protocols & Handoffs | Agent identity and delegated authorization | Docs | Identity Management for Agentic AI: The new frontier of authorization, authentication, and security for an AI agent world | https://openid.net/wp-content/uploads/2025/10/Identity-Management-for-Agentic-AI.pdf | OpenID Foundation | 2,025 | OpenID Foundation Artificial Intelligence Identity Management Community Group | Maps identity, authentication, delegated authority, consent, governance, and accountability gaps for autonomous agents against OAuth and OpenID Connect foundations. | Provides a standards-grounded vocabulary for identity-bearing nodes and auditable delegation across agent and tool edges; it is a non-normative landscape whitepaper, not a protocol. | Official documentation | Handoffs |
age-0106 | Protocols & Handoffs | Agent capability and discovery schema | Standard | Open Agentic Schema Framework (OASF) v1.1.0 | https://github.com/agntcy/oasf/releases/tag/v1.1.0 | AGNTCY Project, Linux Foundation | 2,026 | AGNTCY Project | Defines versioned schemas and taxonomies for agent identity metadata, capabilities, skills, modules, interactions, and discovery records, including MCP and A2A alignment modules. | Gives graph builders a portable node descriptor for capability-based discovery and routing validation; it describes capabilities but does not execute a graph or authorize an edge. | Industry standard | Roles |
age-0107 | State, Memory & Artifacts | Artifact provenance | Standard | PROV-DM: The PROV Data Model | https://www.w3.org/TR/prov-dm/ | W3C Recommendation | 2,013 | Luc Moreau; Paolo Missier | Defines entities, activities, agents, derivation, attribution, responsibility, bundles, and collections for interoperable provenance records. | Maps artifacts, execution steps, and responsible nodes into a portable lineage model; storage, access control, and cryptographic integrity remain implementation concerns. | Industry standard | State |
age-0108 | State, Memory & Artifacts | Cryptographic artifact provenance | Paper | in-toto: Providing farm-to-table guarantees for bits and bytes | https://www.usenix.org/conference/usenixsecurity19/presentation/torres-arias | USENIX Security | 2,019 | Santiago Torres-Arias; Hammad Afzali; Trishank Karthik Kuppusamy; Reza Curtmola; Justin Cappos | Introduces signed material and product links for supply-chain steps and verifies them against an expected layout, supported by analysis of 30 historical compromises and deployed integrations. | Supplies a transferable receipt pattern that binds each artifact transformation to an authorized step and identity; it verifies process integrity, not semantic correctness. | Peer-reviewed research | State |
age-0109 | Reliability & Durable Execution | Portable workflow semantics | Standard | Serverless Workflow Specification v1.0.0 | https://open-workflow-specification.org/blog/releases/release-100/ | Open Workflow Specification, Cloud Native Computing Foundation | 2,025 | Open Workflow Specification Project | Defines a vendor-neutral workflow language with sequential and concurrent tasks, event correlation, service calls, error handling, retries, and timeouts. | Provides an inspectable execution contract for production work graphs; conformance does not itself supply a durable runtime, an agent protocol, or model-level correctness. | Industry standard | Reliability |
age-0110 | Critiques & Limits | Compound-system call scaling | Paper | Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems | https://proceedings.neurips.cc/paper_files/paper/2024/hash/51173cf34c5faac9796a47dc2fdd3a71-Abstract-Conference.html | NeurIPS | 2,024 | Lingjiao Chen; Jared Davis; Boris Hanin; Peter Bailis; Ion Stoica; Matei Zaharia; James Zou | Analyzes Vote and Filter-Vote compound systems and finds that performance can rise and then fall as the number of language-model calls increases because query difficulty is heterogeneous. | Bounds claims that adding calls, voters, or nodes automatically improves a system; the experiments cover simple aggregation systems rather than rich agent organizations. | Peer-reviewed research | Observability & cost |
age-0111 | Verification & Evals | Verification-aware work graphs | Paper | Verification-Aware Planning for Multi-Agent Systems | https://aclanthology.org/2026.eacl-long.353/ | EACL | 2,026 | Tianyang Xu; Dan Zhang; Kushan Mitra; Estevam Hruschka | Introduces VeriMAP, which decomposes tasks into a dependency graph and attaches planner-defined Python and natural-language verification functions to subtasks before execution. | Makes acceptance criteria part of the work graph so handoff failures can trigger local repair instead of surfacing only in a final answer. | Peer-reviewed research | Gates |
age-0112 | Research Foundations | Human-in-the-loop work-graph planning | Paper | AIPOM: Agent-aware Interactive Planning for Multi-Agent Systems | https://aclanthology.org/2025.emnlp-demos.7/ | EMNLP System Demonstrations | 2,025 | Hannah Kim; Kushan Mitra; Chen Shen; Dan Zhang; Estevam Hruschka | Presents conversational and graph-based interfaces for inspecting, editing, and collaboratively guiding plans in orchestrated multi-agent systems. | Treats the work graph as a human-legible control surface; its non-autonomous agents execute assigned tasks, so it is a planning substrate rather than a complete agent organization. | Peer-reviewed research | Work graphs |
age-0113 | Frameworks & SDKs | Graph workflow runtime | Blog | Build reliable multi-agent applications with ADK Go 2.0 | https://developers.googleblog.com/announcing-adk-go-20/ | Google Developers Blog | 2,026 | Toni Klopfenstein; Sampath Kumar Maddula | Documents a graph-based multi-agent workflow engine with typed nodes, conditional edges, fan-out and fan-in, nested graphs, cycles, retries, durable human input, state, and unified telemetry. | Provides a first-party implementation of explicit, resumable work graphs while showing that function and tool nodes remain distinct from agent nodes. | Practitioner analysis | Work graphs |
age-0114 | Research Foundations | Decentralized adaptive coordination | Paper | AgentNet: Decentralized Evolutionary Coordination for LLM-based Multi-Agent Systems | https://proceedings.neurips.cc/paper_files/paper/2025/hash/9a379c1b05793d1c42dc832269834515-Abstract-Conference.html | NeurIPS | 2,025 | Yingxuan Yang; Huacan Chai; Shuai Shao; Yuanyi Song; Siyuan Qi; Renting Rui; Weinan Zhang | Organizes specialized agents in a decentralized DAG, uses retrieval-backed local experience for capability refinement, and adapts routing without a single central orchestrator. | Offers a contrasting topology for settings where central coordination is a bottleneck or trust boundary; its reported evidence is concentrated in reasoning and coding tasks. | Peer-reviewed research | Topology |
age-0115 | Reliability & Durable Execution | Effect-typed agent contracts | Paper | ETAS: An Effect-Typed Language for Agent Systems | https://arxiv.org/abs/2607.17780 | arXiv | 2,026 | Huiri Tan; Yikun Wang; Puyang Zhang; Shangyu Li; Jiasi Shen | Defines a language in which agents, tools, typed memory, approvals, policies, effects, and execution traces are semantic program elements, with static obligations and runtime monitors. | Provides a transferable contract model for authorizing and auditing node actions before and during execution; it is a new preprint and not yet deployment evidence. | Research preprint | Reliability |
age-0116 | Critiques & Limits | Consensus-induced search collapse | Paper | The Shared Discovery Paradox: How a One-Answer Rule Turns Better Information into Worse Search | https://arxiv.org/abs/2607.18045 | arXiv | 2,026 | Yohei Nakajima | Uses an exactly solvable multi-searcher benchmark to show that pooling information into one repeated recommendation can improve belief accuracy while sharply reducing collective discovery coverage. | Separates information quality from allocation policy and warns that consensus edges can collapse parallel exploration unless a coordinator preserves a portfolio of actions. | Research preprint | Topology |
age-0117 | Critiques & Limits | Relay information bottlenecks | Paper | When Do Multi-Agent Systems Help? An Information Bottleneck Perspective | https://arxiv.org/abs/2607.16133 | arXiv | 2,026 | Wendi Yu; Lianhao Zhou; Xiangjue Dong; Sai Sudarshan Barath; Declan Staunton; Byung-Jun Yoon; Xiaoning Qian; James Caverlee; Shuiwang Ji | Formalizes bounded inter-agent relays as an information bottleneck and reports 18 controlled experiments across five benchmarks and three model scales. | Explains when isolated contexts and compressed handoffs save useful context and when they discard task-relevant information, providing a direct test for whether a graph earns its edge losses. | Research preprint | Handoffs |
age-0118 | Critiques & Limits | Critique uptake failure | Paper | Precise but Uncoupled: Reviewer Precision Does Not Guarantee Critique Uptake in Multi-Agent Math Reasoning | https://arxiv.org/abs/2607.15388 | arXiv | 2,026 | Chih-Hsuan Yang; Jingyan Jiang; Vikram Vasudevan; Cheng-Hau Yang; Huihuo Zheng; Le Chen; Eliu A. Huerta; Venkatram Vishwanath; Ian T. Foster; Rajeev Thakur | Evaluates 4,181 verifier-grounded math problems and finds that a precise reviewer can still yield weak repair when the protocol does not carry useful critique into the next candidate. | Shows that a verifier node is insufficient by itself: the outgoing edge must couple accepted evidence to a concrete state change or retry action. | Research preprint | Gates |
age-0119 | Research Foundations | Grammar-based system search | Paper | Grammar Search for Multi-Agent Systems | https://aclanthology.org/2026.acl-long.75/ | ACL | 2,026 | Mayank Singh; Vikas Yadav; Shiva Krishna Reddy Malay; Shravan Nayak; Sai Rajeswar; Sathwik Tejaswi Madhusudhan; Eduardo Blanco | Searches a fixed grammar of composable multi-agent components to construct modular, interpretable organizations at lower search cost than unconstrained code generation. | Makes the agent-system design space explicit and auditable while retaining automated search over roles, operators, and coordination structure. | Peer-reviewed research | Evolution |
age-0120 | Research Foundations | Topology policy optimization | Paper | Graph-GRPO: Stabilizing Multi-Agent Topology Learning via Group Relative Policy Optimization | https://aclanthology.org/2026.findings-acl.1010/ | Findings of ACL | 2,026 | Yueyang Cang; Xiaoteng Zhang; Erlu Zhao; Zehua Ji; Yuhang Liu; Yuchen He; Zhiyuan Ning; Chen Yijun; Wenge Que; Li Shi | Samples groups of query-specific communication graphs and uses relative rewards to assign edge-level credit while training a topology-generating policy. | Addresses unstable topology learning with explicit graph samples and localized credit rather than treating orchestration as an opaque prompt update. | Peer-reviewed research | Evolution |
age-0121 | Observability & Cost | Cost-aware graph compression | Paper | AgentSlimming: Towards Efficient and Cost-Aware Multi-Agent Systems | https://aclanthology.org/2026.acl-long.1387/ | ACL | 2,026 | Yulang Chen; Haoxuan Peng; Jinyan Liu; Zichen Wen; Dongrui Liu; Linfeng Zhang | Compresses graph-structured agent workflows using centrality and approximate Shapley importance, then validates agent removal and cheaper-model substitution against the original system. | Provides a measured way to reduce nodes and spend without assuming every role contributes equally or that a smaller graph preserves behavior automatically. | Peer-reviewed research | Evolution |
age-0122 | Research Foundations | One-shot topology generation | Paper | TopoDIM: One-shot Topology Generation of Diverse Interaction Modes for Multi-Agent Systems | https://aclanthology.org/2026.findings-acl.207/ | Findings of ACL | 2,026 | Rui Sun; Jie Ding; Chenghua Gong; Tianjun Gu; Yihang Jiang; Juyuan Zhang; Liming Pan; Linyuan Lü | Generates heterogeneous decentralized communication topologies in one pass, replacing repeated coordination rounds with a task-conditioned interaction structure. | Expands topology design beyond homogeneous or fully connected teams while directly evaluating the quality and token cost of the generated graph. | Peer-reviewed research | Topology |
age-0123 | Research Foundations | Evolving hypergraph collaboration | Paper | EvoHyper: Evolving Hypergraph Topologies for Unified Collaboration in Multi-Agent Communication | https://aclanthology.org/2026.findings-acl.1258/ | Findings of ACL | 2,026 | Heng Zhang; Yihao Zhong; Lubin Gan; Zhihe Chen; Jiajun Wu; Yuling Shi; Xiaodong Gu; Hao Zhang; Haochen You; Jin Huang | Uses evolving hyperedges to bind groups of agents to shared memory while a controller creates, updates, and merges collaboration units during execution. | Models group communication as a first-class structure and joins topology evolution with explicit shared-state ownership instead of reducing every exchange to pairwise chat. | Peer-reviewed research | Evolution |
age-0124 | Research Foundations | Heterogeneous graph routing | Paper | RouterHGC: Optimized Router for LLM-based Multi-Agent Systems via Heterogeneous Graph Contrastive Learning | https://aclanthology.org/2026.findings-acl.1589/ | Findings of ACL | 2,026 | Yitao Xiao; Shaoyong Guo; Guoming Yang; Qingnan Wang; Yinlin Ren; Xuesong Qiu; Qi Feng | Represents queries, collaboration modes, roles, and language models as heterogeneous nodes and learns cost-performance routing relationships with graph contrastive learning. | Treats the agent organization itself as the graph under optimization and exposes model, role, mode, and budget choices within one routing decision. | Peer-reviewed research | Evolution |
age-0125 | Research Foundations | Dynamic workflow scheduling | Paper | LLM-as-Scheduler: Agentic Workflow Dynamic Scheduling | https://aclanthology.org/2026.acl-long.581/ | ACL | 2,026 | Dawei Xiang; Kexin Chu; Wenyan Xu; Wenhui Zhang; Wei Zhang | Dynamically selects query-specific paths through a workflow DAG, including early exit, verification, repair, and rerouting decisions made during execution. | Separates the reusable work graph from the runtime path and supplies concrete control points for budgets, validation, and local recovery. | Peer-reviewed research | Work graphs |
age-0126 | Research Foundations | Adaptive message representation | Paper | Learning Optimal Message Representations for Agentic Communication | https://aclanthology.org/2026.findings-acl.1441/ | Findings of ACL | 2,026 | Shashwat Gupta; Anson Bastos; Mayukh Das; Supriyo Ghosh; Nagarajan Natarajan; Chetan Bansal; Saravan Rajmohan | Models the choice of inter-agent message representation as an expanding Markov decision process that can select natural-language or structured protocols at each exchange. | Makes payload format an adaptive edge policy rather than a global convention, clarifying when structure, compression, or expressiveness should dominate. | Peer-reviewed research | Handoffs |
age-0127 | Reliability & Durable Execution | Handoff clarification | Paper | AgentAsk: Multi-Agent Systems Need to Ask | https://aclanthology.org/2026.acl-long.1294/ | ACL | 2,026 | Bohan Lin; Kuo Yang; Zelin Tan; Yingchuan Lai; Chen Zhang; Guibin Zhang; Xinlei Yu; Miao Yu; Xu Wang; Yudong Zhang; Yang Wang | Defines an edge-level handoff-error taxonomy and adds selective clarification questions at critical exchanges where transferred information is ambiguous or incomplete. | Turns clarification into an explicit recovery action for communication-contract failures instead of letting uncertainty silently propagate downstream. | Peer-reviewed research | Handoffs |
age-0128 | Reliability & Durable Execution | Execution-verified diagnosis | Paper | Towards Self-Improving Error Diagnosis in Multi-Agent Systems | https://aclanthology.org/2026.findings-acl.98/ | Findings of ACL | 2,026 | Jiazheng Li; Emine Yilmaz; Bei Chen; Thu Le | Detects local anomalies, traces backward to decisive failures, tests diagnostic hypotheses with tools, and retains only execution-verified diagnostic memories. | Combines trace localization, active validation, and durable learning so a diagnostic node improves from evidence rather than storing unverified explanations. | Peer-reviewed research | Observability & cost |
age-0129 | Reliability & Durable Execution | Denial-of-collaboration attacks | Paper | CORBA: Contagious Recursive Blocking Attacks on Multi-Agent Systems Based on Large Language Models | https://aclanthology.org/2026.findings-acl.342/ | Findings of ACL | 2,026 | Zhenhong Zhou; Zherui Li; Jie Zhang; Yuanhe Zhang; Kun Wang; Yang Liu; Qing Guo | Formalizes attacks that deform communication topology into cycles or recursively expanding exchanges, blocking useful collaboration while exhausting system resources. | Shows that edge activation and termination policies are security boundaries, not only scheduling details, and motivates cycle and budget guards. | Peer-reviewed research | Reliability |
age-0130 | Reliability & Durable Execution | Topology confidentiality | Paper | CIA: Inferring the Communication Topology from LLM-based Multi-Agent Systems | https://aclanthology.org/2026.acl-long.815/ | ACL | 2,026 | Yongxuan Wu; Xixun Lin; He Zhang; Nan Sun; Kun Wang; Chuan Zhou; Shirui Pan; Yanan Cao | Infers hidden communication topology from black-box multi-agent systems using adversarial queries and semantic correlations among observed responses. | Establishes topology confidentiality as an engineering property and demonstrates that apparently private coordination structure can leak through behavior. | Peer-reviewed research | Reliability |
age-0131 | Benchmarks & Datasets | Cascading-injection evaluation | Benchmark | ACIArena: Toward Unified Evaluation for Agent Cascading Injection | https://aclanthology.org/2026.acl-long.457/ | ACL | 2,026 | Hengyu An; Minxi Li; Jinghuai Zhang; Naen Xu; Chunyi Zhou; Changjiang Li; Xiaogang Xu; Tianyu Du; Shouling Ji | Evaluates cascading injection through external inputs, agent profiles, and inter-agent messages across six implementations and 1,356 attack cases. | Measures how topology, roles, and interaction design affect propagation instead of treating prompt injection as an isolated single-node event. | Benchmark/dataset | Reliability |
age-0132 | Reliability & Durable Execution | Unknown-attack detection | Paper | BlindGuard: Safeguarding LLM-based Multi-Agent Systems under Unknown Attacks | https://aclanthology.org/2026.acl-long.1819/ | ACL | 2,026 | Rui Miao; Yixin Liu; Yili Wang; Xu Shen; Yue Tan; Yiwei Dai; Shirui Pan; Xin Wang | Learns normal individual, neighborhood, and global interaction behavior without attack labels, then detects malicious agents through corruption-guided contrastive learning. | Adds graph-aware anomaly detection for attacks that were absent from training and distinguishes local behavior from neighborhood and system-wide patterns. | Peer-reviewed research | Reliability |
age-0133 | Reliability & Durable Execution | Fine-grained graph anomaly detection | Paper | Explainable and Fine-Grained Safeguarding of LLM Multi-Agent Systems via Bi-Level Graph Anomaly Detection | https://aclanthology.org/2026.acl-long.1407/ | ACL | 2,026 | Junjun Pan; Yixin Liu; Rui Miao; Kaize Ding; Yu Zheng; Quoc Viet Hung Nguyen; Alan Wee-Chung Liew; Shirui Pan | Detects sentence- and token-level anomalies over multi-agent interaction graphs and attributes suspicious tokens to support finer-grained explanations of compromised exchanges. | Connects graph-level protection to actionable message evidence rather than returning only an opaque risk score for an entire agent or run. | Peer-reviewed research | Reliability |
age-0134 | Verification & Evals | Collective-intelligence prediction | Paper | Identifying Collective Intelligence Factor in LLM Agent Groups for Generalizable Multi-Agent System Design | https://aclanthology.org/2026.findings-acl.624/ | Findings of ACL | 2,026 | Zhilun Zhou; Zihan Liu; Jiahe Liu; Yihan Wang; Qingyu Shao; Fengli Xu; Depeng Jin; Yong Li | Studies 108 agent groups varying team size, model composition, and communication topology, then derives a factor intended to predict transferable system designs. | Moves evaluation beyond one benchmark score by testing whether measurable group properties forecast performance across designs and tasks. | Peer-reviewed research | Evolution |
age-0135 | Critiques & Limits | Communication capacity bounds | Paper | Benefits and Limitations of Communication in Multi-Agent Reasoning | https://openreview.net/forum?id=0aPIVJUz5T | ICLR | 2,026 | Michael Rizvi-Martel; Satwik Bhattamishra; Neil Rathi; Guillaume Rabusseau; Michael Hahn | Derives bounds connecting agent count and the quantity and structure of communication to exact reasoning and speedups, then tests the tradeoffs on controlled language-model tasks. | Supplies principled limits for node count and bandwidth decisions and identifies regimes where communication helps or becomes an intrinsic bottleneck. | Peer-reviewed research | Handoffs |
age-0136 | Reliability & Durable Execution | Topology-aware prompt attacks | Paper | Agents Under Siege: Breaking Pragmatic Multi-Agent LLM Systems with Optimized Prompt Attacks | https://aclanthology.org/2025.acl-long.476/ | ACL | 2,025 | Rana Shahroz; Zhen Tan; Sukwon Yun; Charles Fleming; Tianlong Chen | Optimizes attack placement across latency- and bandwidth-constrained agent networks using graph-flow formulations to disrupt multi-agent task completion. | Makes topology part of the adversary model and tests how limited attack budgets exploit particular communication paths and bottlenecks. | Peer-reviewed research | Reliability |
age-0137 | Benchmarks & Datasets | Networked-agent coordination | Paper | AgentsNet: Coordination and Collaborative Reasoning in Multi-Agent LLMs | https://arxiv.org/abs/2507.08616 | arXiv; ICML 2025 Workshop on Collaborative and Federated Agentic Workflows | 2,025 | Florian Grötschla; Luis Müller; Jan Tönshoff; Mikhail Galkin; Bryan Perozzi | Evaluates local messaging and learned coordination protocols on distributed graph problems over explicit network topologies, with experiments scaling to 100 agents. | Provides unusually direct evidence about decentralized protocol formation and topology-aware reasoning; the selected artifact remains a preprint and workshop contribution. | Research preprint | Topology |
age-0138 | Benchmarks & Datasets | Pure coordination games | Benchmark | LLM-Coordination: Evaluating and Analyzing Multi-agent Coordination Abilities in Large Language Models | https://aclanthology.org/2025.findings-naacl.448/ | Findings of NAACL | 2,025 | Saaket Agashe; Yue Fan; Anthony Reyna; Xin Eric Wang | Evaluates agentic play in four pure-coordination games and 198 questions covering environment comprehension, theory of mind, and joint planning. | Separates coordination capability into measurable components and partner-generalization tests, although communication topology is not its central experimental variable. | Benchmark/dataset | Gates |
age-0139 | Research Foundations | Relevance-ordered message passing | Paper | Graph-of-Agents: A Graph-based Framework for Multi-Agent LLM Collaboration | https://openreview.net/forum?id=34cANdsHKV | ICLR | 2,026 | Sukwon Yun; Jie Peng; Pingzhi Li; Wendong Fan; Jie Chen; James Y. Zou; Guohao Li; Tianlong Chen | Selects relevant agents from model cards, constructs directed edges from response relevance, performs forward and reverse message passing, and pools the revised answers. | Offers an end-to-end graph construction and aggregation method in which node selection, edge order, and communication direction are explicit design choices. | Peer-reviewed research | Topology |
age-0140 | Research Foundations | Response-conditioned self-organization | Paper | Stochastic Self-Organization in Multi-Agent Systems | https://openreview.net/forum?id=rS3Jb9AAej | ICLR | 2,026 | Nurbek Tastan; Samuel Horváth; Karthik Nandakumar | Builds a response-conditioned directed acyclic graph from approximate peer-contribution scores and updates the communication structure across collaboration rounds. | Adapts topology from observed agent behavior without a separate judge, pretrained generator, or fixed graph, while retaining stable acyclic message flow. | Peer-reviewed research | Evolution |
age-0141 | Research Foundations | Memory-augmented agent routing | Paper | GraphPlanner: Graph Memory-Augmented Agentic Routing for Multi-Agent LLMs | https://openreview.net/forum?id=ZdGB7MNQDT | ICLR | 2,026 | Tao Feng; Haozhen Zhang; Zijie Lei; Peixuan Han; Jiaxuan You | Generates query-specific workflows by selecting both language-model backbones and agent roles while consulting a heterogeneous graph of query-agent-response history. | Combines work-graph routing with reusable interaction memory and evaluates unseen-task and unseen-model generalization rather than only in-distribution quality. | Peer-reviewed research | Evolution |
age-0142 | Observability & Cost | Runtime adaptive supervision | Paper | Stop Wasting Your Tokens: Towards Efficient Runtime Multi-Agent Systems | https://openreview.net/forum?id=pzFhtpkabh | ICLR | 2,026 | Fulin Lin; Shaowen Chen; Ruishan Fang; Hongwei Wang; Tao Lin | Adds a lightweight supervisor triggered by an LLM-free filter to intervene when a multi-agent run shows errors, inefficient behavior, or contaminated observations. | Places cost and failure control inside the live execution path and tests whether selective supervision can reduce token use without redesigning the base graph. | Peer-reviewed research | Observability & cost |
age-0143 | Benchmarks & Datasets | Multi-agent error attribution | Benchmark | Aegis: Automated Error Generation and Attribution for Multi-Agent Systems | https://openreview.net/forum?id=zqcYoxXiN3 | ICLR | 2,026 | Fanqi Kong; Ruijie Zhang; Huaxiao Yin; Guibin Zhang; Xiaofei Zhang; Ziang Chen; Zhaowei Zhang; Xiaoyuan Zhang; Song-Chun Zhu; Xue Feng | Creates 9,533 trajectories with annotated faulty agents and error modes by injecting context-aware faults into successful runs across multiple architectures and domains. | Provides graph-component labels for training and evaluating failure attribution instead of relying only on final-task success or expensive manual trace review. | Benchmark/dataset | Reliability |
age-0144 | Frameworks & SDKs | Multi-agent reinforced training | Paper | MARTI: A Framework for Multi-Agent LLM Systems Reinforced Training and Inference | https://openreview.net/forum?id=E7jZqo0A50 | ICLR | 2,026 | Kaiyan Zhang; Kai Tian; Runze Liu; Sihang Zeng; Xuekai Zhu; Guoli Jia; Yuchen Fan; Xingtai Lv; Yuxin Zuo; Che Jiang; Yuru Wang; Jianyu Wang; Ermo Hua; Xinwei Long; Junqi Gao; Youbang Sun; Zhiyuan Ma; Ganqu Cui; Ning Ding; Biqing Qi; Bowen Zhou | Supports centralized multi-agent interaction, distributed policy training, asynchronous rollouts, graph-defined workflows, heterogeneous models, tools, and configurable rewards. | Connects executable organizations to reinforced training infrastructure so graph policies can be optimized and evaluated rather than remaining hand-authored inference code. | Peer-reviewed research | Evolution |
age-0145 | Research Foundations | Parallel message propagation | Paper | MPAS: Breaking Sequential Constraints of Multi-Agent Communication Topologies via Individual-Epistemic Message Propagation | https://ojs.aaai.org/index.php/AAAI/article/view/40231 | AAAI | 2,026 | Jingxuan Yu; Ju Jia; Simeng Qin; Xiaojun Jia; Siqi Ma; Yihao Huang; Yali Yuan; Guang Cheng | Reworks sequential multi-agent communication into parallel graph message propagation with optimized connections and aggregation while preserving agent-specific epistemic state. | Targets latency introduced by dependency-ordered exchanges and makes the tradeoff between parallel execution, aggregation, and resilience measurable. | Peer-reviewed research | Topology |
age-0146 | Verification & Evals | Trajectory failure diagnosis | Benchmark | AgentRx: Diagnosing AI Agent Failures from Execution Trajectories | https://arxiv.org/abs/2602.02475 | arXiv | 2,026 | Shraddha Barke; Arnav Goyal; Alind Khare; Avaljot Singh; Suman Nath; Chetan Bansal | Releases 115 manually annotated failed trajectories and diagnoses critical failure steps by synthesizing guarded executable constraints and evidence-bearing validation logs. | Provides a concrete bridge from heterogeneous agent traces to repeatable failure localization; its evaluation includes Magentic-One but also single-agent workflows. | Benchmark/dataset | Gates |
age-0147 | Verification & Evals | Cross-framework system evaluation | Benchmark | MAESTRO: Multi-Agent Evaluation Suite for Testing, Reliability, and Observability | https://arxiv.org/abs/2601.00481 | arXiv | 2,026 | Tie Ma; Yixi Chen; Vaastav Anand; Alessandro Cornacchia; Amândio R. Faustino; Guanheng Liu; Shan Zhang; Hongbin Luo; Suhaib A. Fahmy; Zafar A. Qazi; Marco Canini | Standardizes configuration and execution for 12 representative multi-agent systems and exports framework-agnostic traces with latency, cost, reliability, and failure signals. | Enables controlled comparison across architectures and repeated runs while revealing that topology can dominate model or tool changes in resource and reliability profiles. | Benchmark/dataset | Observability & cost |
age-0148 | Observability & Cost | Causal root-cause tracing | Paper | AgentTrace: Causal Graph Tracing for Root Cause Analysis in Deployed Multi-Agent Systems | https://arxiv.org/abs/2603.14688 | arXiv; ICLR 2026 Workshop on Agents in the Wild | 2,026 | Zhaohui Geoffrey Wang | Reconstructs causal graphs from execution logs, traces backward from observed failures, and ranks candidate root causes without requiring language-model inference during debugging. | Offers an interpretable, low-latency diagnosis primitive for cascading failures while remaining a preprint and workshop result rather than broad production validation. | Research preprint | Observability & cost |
age-0149 | Start Here | Production reference architecture | Docs | Multi-Agent Reference Architecture | https://github.com/microsoft/multi-agent-reference-architecture | Microsoft | 2,026 | Microsoft | Maps agent registries, communication, memory, observability, evaluation, security, governance, and deployment into an end-to-end reference architecture for multi-agent systems. | Provides a broad engineering checklist grounded in customer implementations; it is evolving guidance in an official repository, not a versioned standard. | Official documentation | Topology |
age-0150 | Frameworks & SDKs | Event-driven agent runtime | Docs | AutoGen Core | https://microsoft.github.io/autogen/stable/user-guide/core-user-guide/index.html | Microsoft AutoGen Documentation | 2,026 | Microsoft | Documents an actor-style agent runtime with asynchronous messages, topics, subscriptions, distributed execution, resilience mechanisms, and telemetry. | Adds the lower-level message and runtime architecture beneath conversational teams, clarifying how agent nodes communicate and scale across processes. | Official documentation | Handoffs |
age-0151 | Frameworks & SDKs | Managed multi-agent orchestration | Docs | Multiagent orchestration | https://platform.claude.com/docs/en/managed-agents/multiagent-orchestration | Claude Platform Documentation | 2,026 | Anthropic | Documents managed multi-agent orchestration with a lead agent that creates specialized subagents, delegates work, and combines their results under a beta API contract. | Provides a current first-party implementation of dynamic specialization and hierarchical delegation while clearly exposing its managed-runtime boundary and beta status. | Official documentation | Topology |
age-0152 | Reliability & Durable Execution | Distributed agent runtime | Blog | Introducing Agent Executor, Google’s distributed Agent Runtime | https://cloud.google.com/blog/products/ai-machine-learning/agent-executor-googles-distributed-agent-runtime | Google Cloud Blog | 2,026 | Jaana Dogan; Ethan Bao | Introduces an open-source runtime standard for execution, resumption, isolation, session consistency, reconnection, trajectory branching, and federated agent deployment. | Addresses durable long-running graphs at the runtime layer and makes checkpoints, single-writer state, recovery, and deployment boundaries explicit; the release is in preview. | Practitioner analysis | Reliability |
age-0153 | Observability & Cost | Workflow profiling and optimization | Tool | NVIDIA NeMo Agent Toolkit | https://github.com/NVIDIA/NeMo-Agent-Toolkit | NVIDIA | 2,026 | NVIDIA | Provides framework-agnostic profiling, evaluation, optimization, tracing, and A2A team support for agent workflows, including experimental graph-performance primitives. | Lets engineers measure whole-graph latency and cost while experimenting with parallel branches, speculative execution, and node priorities in maintained open-source tooling. | Maintained OSS project | Observability & cost |
age-0154 | Verification & Evals | Protocol conformance | Tool | A2A Protocol Technology Compatibility Kit | https://github.com/a2aproject/a2a-tck | Agent2Agent Project, Linux Foundation | 2,026 | Agent2Agent Project | Tests Agent2Agent protocol implementations across gRPC, JSON-RPC, and HTTP with JSON and emits machine-readable, HTML, and JUnit conformance reports. | Turns interoperability claims at agent handoff edges into executable gates that can run in development and continuous integration. | Maintained OSS project | Gates |
age-0155 | Protocols & Handoffs | Distributed agent discovery | Tool | AGNTCY Dir | https://github.com/agntcy/dir | AGNTCY Project, Linux Foundation | 2,026 | AGNTCY Project | Implements a distributed directory for capability-based discovery of agents and multi-agent systems using OASF records and cryptographic identity. | Covers how potential graph participants are registered, discovered, authenticated, and selected before a work or communication edge is created. | Maintained OSS project | Handoffs |
age-0156 | Reliability & Durable Execution | Runtime governance | Tool | Agent Governance Toolkit | https://github.com/microsoft/agent-governance-toolkit | Microsoft | 2,026 | Microsoft | Enforces runtime policies on tool calls and inter-agent messages with identity, delegation, audit logs, telemetry, and adapters for multiple agent frameworks. | Implements authorization and audit controls at graph edges; it is a public preview, and its in-process enforcement layer is not an operating-system security boundary. | Maintained OSS project | Gates |
age-0157 | Reliability & Durable Execution | Multi-agent threat modeling | Docs | Multi-Agentic System Threat Modeling Guide v1.0 | https://genai.owasp.org/resource/multi-agentic-system-threat-modeling-guide-v1-0/ | OWASP GenAI Security Project | 2,025 | OWASP GenAI Security Project | Applies an agentic threat taxonomy to multi-agent architectures and examines attack surfaces introduced by delegation, messaging, shared memory, tools, and cross-agent actions. | Provides a structured way to identify graph-specific trust boundaries and abuse paths; it is community security guidance rather than a certification or formal standard. | Official documentation | Gates |
age-0158 | Observability & Cost | Agent operations reference architecture | Blog | AgentOps: Operationalize agentic AI at scale with Amazon Bedrock AgentCore | https://aws.amazon.com/blogs/machine-learning/agentops-operationalize-agentic-ai-at-scale-with-amazon-bedrock-agentcore/ | AWS Machine Learning Blog | 2,026 | Anastasia Tzeveleka; Anna Grüebler; Antonio Rodriguez; Sergio Garcés Vitale; Aris Tsakpinis | Organizes production agent operations around governance, build and release, multi-level evaluation, observability, identity propagation, and cost attribution in a reference architecture. | Adds concrete system measures such as orchestration accuracy and exchange quality while keeping the vendor-specific implementation context visible. | Practitioner analysis | Observability & cost |
age-0159 | Production Case Studies | Enterprise supervisor architecture | Blog | Powering agentic AI sales strategy with Amazon Bedrock AgentCore | https://aws.amazon.com/blogs/machine-learning/powering-agentic-ai-sales-strategy-with-amazon-bedrock-agentcore/ | AWS Machine Learning Blog | 2,026 | Nicolle Belaunde; Umesh Mohan; Xinrui Nie | Describes an internal production system with more than 20 domain agents, supervisor routing, OAuth propagation, MCP tools, approvals, memory, distributed tracing, and evaluation. | Offers a rare detailed account of an enterprise supervisor graph at operating scale; its usage, latency, and outcome figures are self-reported by AWS. | Practitioner analysis | Topology |
age-0160 | Production Case Studies | Verified coding swarm | Blog | Designing Autonomous AI Agents: How We Built a Multi-Agent Swarm for UI Development | https://www.epam.com/insights/ai/blogs/building-multi-swarm-autonomous-ai-agent | EPAM Insights | 2,026 | Stanislau Shandrokha; Pavel Golub; Andrey Voroshkov | Describes a seven-agent state-machine workflow with resumable state, explicit roles, adversarial visual and code reviewers, and verification gates for interface development. | Reports practical failures such as overlapping work, skipped steps, and rubber-stamping alongside mitigations; the evidence is a narrow, self-reported implementation account. | Practitioner analysis | Gates |
age-0161 | Protocols & Handoffs | Agent message envelopes | Standard | FIPA ACL Message Structure Specification | https://www.fipa.org/specs/fipa00061/SC00061G.html | Foundation for Intelligent Physical Agents | 2,002 | FIPA TC Communication; FIPA Architecture Board | Defines interoperable agent messages with performatives, sender and receiver, ontology, protocol, conversation identifiers, reply correlation, and deadlines. | Supplies the historical standards basis for message-envelope and conversation concepts that reappear in current agent handoff protocols. | Industry standard | Handoffs |
age-0162 | Production Case Studies | Network-level red teaming | Blog | Red-teaming a network of agents: Understanding what breaks when AI agents interact at scale | https://www.microsoft.com/en-us/research/blog/red-teaming-a-network-of-agents-understanding-what-breaks-when-ai-agents-interact-at-scale/ | Microsoft Research Blog | 2,026 | Gagan Bansal; Shujaat Mirza; Keegan Hines; Will Epperson; Zachary Huang; Whitney Maxwell; Pete Bryan; Tyler Payne; Adam Fourney; Amanda Swearngin; Wenyue Hua; Tori Westerhoff; Amanda Minnich; Maya Murad; Ece Kamar; Ram Shankar Siva Kumar; Saleema Amershi | Reports a red-team exercise on a live internal platform with more than 100 persistent agents and identifies propagation, amplification, trust capture, and invisibility failures. | Demonstrates interaction risks that do not appear in isolated-agent tests; the environment and findings are company-reported rather than independently reproduced. | Practitioner analysis | Reliability |
age-0163 | Research Foundations | Hypergraph topology optimization | Paper | HyperAgent: Leveraging Hypergraphs for Topology Optimization in Multi-Agent Communication | https://www.ifaamas.org/Proceedings/aamas2026/pdfs/QTVF9552.pdf | AAMAS | 2,026 | Heng Zhang; Yuling Shi; Xiaodong Gu; Zijian Zhang; Haochen You; Lubin Gan; Yilei Yuan; Jin Huang | Represents collaboration groups as hyperedges and uses a variational hypergraph autoencoder with sparsity regularization to generate task-adaptive communication topology. | Adds group-level topology learning beyond pairwise edges and differs from evolving-hypergraph work by focusing on generated sparse structures for each task. | Peer-reviewed research | Evolution |
age-0164 | Research Foundations | Three-layer knowledge sharing | Paper | D³MAS: Decompose, Deduce, and Distribute for Enhanced Knowledge Sharing in Multi-Agent Systems | https://www.ifaamas.org/Proceedings/aamas2026/pdfs/WQMU8577.pdf | AAMAS | 2,026 | Heng Zhang; Yuling Shi; Xiaodong Gu; Haochen You; Zijian Zhang; Lubin Gan; Yilei Yuan; Jin Huang | Connects task decomposition, collaborative reasoning, and distributed memory as coordinated layers in a heterogeneous graph designed to reduce duplicated retrieval, inference, and assignment. | Unifies work, reasoning, and state dependencies in one inspectable organization rather than optimizing those coordination surfaces separately. | Peer-reviewed research | Work graphs |
age-0165 | Protocols & Handoffs | Resource-bounded communication calculus | Paper | µACP: A Formal Calculus for Expressive, Resource-Constrained Agent Communication | https://www.ifaamas.org/Proceedings/aamas2026/pdfs/PHRW6922.pdf | AAMAS | 2,026 | Arnab Mallick; Indraveni Chebolu | Formalizes resource-bounded agent communication with PING, TELL, ASK, and OBSERVE operations, proves finite-state expressiveness and message bounds, and checks properties with TLA+ and Coq. | Provides a precise substrate for reasoning about protocol behavior and communication budgets; it is a general multi-agent calculus rather than an LLM-specific runtime. | Peer-reviewed research | Handoffs |
age-0166 | Research Foundations | Reinforced evolving orchestration | Paper | Multi-Agent Collaboration via Evolving Orchestration | https://papers.nips.cc/paper_files/paper/2025/hash/f1320d2e2842169c6fc89dcbd80e94d0-Abstract-Conference.html | NeurIPS | 2,025 | Yufan Dang; Chen Qian; Xueheng Luo; Jingru Fan; Zihao Xie; Ruijie Shi; Weize Chen; Cheng Yang; Xiaoyin Che; Ye Tian; Xuantang Xiong; Lei Han; Zhiyuan Liu; Maosong Sun | Trains a centralized orchestrator with reinforcement learning to select and sequence agents from evolving task state, producing dynamic inference graphs and compact cyclic reasoning paths. | Learns runtime activation and ordering rather than fixing a workflow in advance, providing a centralized contrast to decentralized evolutionary coordination. | Peer-reviewed research | Evolution |
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