Re-derivability Decides What a Staged Agent Pipeline Recovers After an Upstream Fault
cs.AI, cs.CL, cs.LG
Submitted: 2026-09-26
Updated: 2026-09-26
Terminology
Sources
- Phi-4 Technical Report
- Beyond the Leaderboard: A Synthesis of Tool-Use, Planning, and Reasoning Failures in Large Language Model Agents
- Adversarial Attacks in Multi-Agent LLM Pipelines: Unveiling Structural Vulnerabilities in Agentic AI Architectures
- Beyond Single-Agent Safety: A Taxonomy of Risks in LLM-to-LLM Interactions
- Why Do Multi-Agent LLM Systems Fail?
- Training Verifiers to Solve Math Word Problems
- Improving Factuality and Reasoning in Language Models through Multiagent Debate
- Faith and Fate: Limits of Transformers on Compositionality
- Byzantine Cheap Talk: Adversarial Resilience and Topology Effects in LLM Coordination Games
- PAL: Program-aided Language Models
- The Llama 3 Herd of Models
- Measuring Massive Multitask Language Understanding
- Measuring Mathematical Problem Solving With the MATH Dataset
- MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework
- On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents
- Large Language Models Cannot Self-Correct Reasoning Yet
- MAS-FIRE: Fault Injection and Reliability Evaluation for LLM-Based Multi-Agent Systems
- Dynamic Generation of Multi-LLM Agents Communication Topologies with Graph Diffusion Models
- Byzantine-Robust Decentralized Coordination of LLM Agents
- On the risk of coding before testing: An empirical study on LLM-based test generation workflow
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