A prompt-based uncertainty decomposition separates action confidence from request uncertainty to enable clarification seeking in LLM agents, yielding F1 gains of 73% and 36% over baselines on two new underspecified benchmarks across five models.
BrowseConf: Confidence-guided test-time scaling for web agents,
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Mobile-Aptus uses supervised fine-tuning followed by semantic similarity retrieval and direct preference optimization to calibrate confidence scores in mobile agents, yielding over 17% average task success improvement on four benchmarks.
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Uncertainty Decomposition for Clarification Seeking in LLM Agents
A prompt-based uncertainty decomposition separates action confidence from request uncertainty to enable clarification seeking in LLM agents, yielding F1 gains of 73% and 36% over baselines on two new underspecified benchmarks across five models.
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Mobile-Aptus: Confidence-Driven Proactive and Robust Interaction in MLLM-based Mobile-Using Agents
Mobile-Aptus uses supervised fine-tuning followed by semantic similarity retrieval and direct preference optimization to calibrate confidence scores in mobile agents, yielding over 17% average task success improvement on four benchmarks.