The Default Trap: Rethinking Plan Evaluation in Tool-Using LLM Agents
cs.AI, cs.LG
Submitted: 2026-09-29
Updated: 2026-09-29
Sources
- $\tau^2$-Bench: Evaluating Conversational Agents in a Dual-Control Environment
- BiasBusters: Uncovering and Mitigating Tool Selection Bias in Large Language Models
- Looking Is Not Picking: An Attention-Segment Account of Tool-Selection Failures in LLM Agents
- Strategic Evaluation of Planning Strategies for LLM Agents in Cyber-Physical Systems
- Towards a Science of Scaling Agent Systems
- Measuring Faithfulness in Chain-of-Thought Reasoning
- From Plan to Action: How Well Do Agents Follow the Plan?
- Plans Fade Fast: Why Context Management Is Load-Bearing for LLM Agents
- Revision or Re-Solving? Decomposing Second-Pass Gains in Multi-LLM Pipelines
- Towards a Science of AI Agent Reliability
- Does Rank Still Matter? Position Bias When AI Agents Shop on Our Behalf
- ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models
- ReAct: Synergizing Reasoning and Acting in Language Models
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