Papers by Sathvika Ayyappa Prabhu

1 papers
Beyond Blind Following: Evaluating Robustness of LLM Agents under Imperfect Guidance (2026.eacl-long)

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Challenge: Large language models (LLMs) have shown strong capabilities as task-solving agents across interactive domains, but in complex environments, auxiliary guidance may be imperfect.
Approach: They propose a benchmark to measure the robustness of large language models under imperfect guidance.
Outcome: The proposed benchmark compared LLM agents in navigation, cooking, and gaming in a variety of environments with auxiliary guidance and noisy or underspecified instructions extracted from demonstrations.

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