Papers with failure recovery

2 papers
One Battle After Another: Probing LLMs’ Limits on Multi-Turn Instruction Following with a Benchmark Evolving Framework (2026.acl-long)

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Challenge: Existing benchmarks for instruction-following in multi-topic dialogues are limited to a fixed number of turns, susceptible to saturation and failing to account for users’ interactive experience.
Approach: They propose a framework featuring a three-layer tracking mechanism and a query synthesis agent to mimic sequential user behaviors.
Outcome: The proposed framework outperforms existing benchmarks in the evaluation of instruction following in multi-topic dialogues and demonstrates deficiencies in failure recovery and fine-grained instruction following.
Tools Fail: Detecting Silent Errors in Faulty Tools (2024.emnlp-main)

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Challenge: a failure in one tool can trigger a cascade of errors, leading to complete task failure.
Approach: They propose a framework for tools more broadly which explores a model’s ability to detect “silent” tool errors and reflect on how to plan.
Outcome: The proposed approach shows that the model can detect "silent" tool errors and plan.

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