Papers by Anshul Mittal

1 papers
JTPRO: A Joint Tool–Prompt Reflective Optimization Framework for Language Agents (2026.findings-acl)

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Challenge: Large language model agents struggle with ambiguous tool descriptions and underspecified tool schemas that ignore tool-specific nuances.
Approach: They propose a framework for improving tool-calling reliability in trace-supervised settings by rolling out-driven reflection.
Outcome: The proposed framework outperforms baselines and reflective prompt optimizers by 5%–20% on OSR.

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