Thesis Proposal: When Does an Agent Know It Is Lost? Confidence Trajectory Analysis for Tool-Using LLMs (2026.acl-srw)
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| Challenge: | Existing uncertainty quantification methods treat each step in isolation, ignoring how confidence evolves and compounds across a full task trajectory. |
| Approach: | They propose a framework for trajectory-level confidence analysis in the tool-use agent setting. |
| Outcome: | The proposed framework will expose early warning signals for agent failure and offer interpretable diagnostic tools for understanding when and why LLM agents lose confidence. |
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