Introduces ShopTrajQA long-context benchmark and an RLVR-trained tool-augmented agent that bypasses LLM context limits by external file storage and code-based retrieval for shopping trajectories.
Proceedings of the AAAI Conference on Artificial Intelligence , author=
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Scene Abstraction framework builds structured scene representations for lexical meaning via LLM prompting, with COCA-Scenes dataset and human experiments showing 82.4% identification accuracy and 86.4% preference over ATOMIC baselines.
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Customer-Agent: Overcoming Context Limitations in Ultra-Long Shopping Trajectories via Tool-Augmented Agents and RLVR
Introduces ShopTrajQA long-context benchmark and an RLVR-trained tool-augmented agent that bypasses LLM context limits by external file storage and code-based retrieval for shopping trajectories.
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Scene Abstraction for Lexical Semantics: Structured Representations of Situated Meaning
Scene Abstraction framework builds structured scene representations for lexical meaning via LLM prompting, with COCA-Scenes dataset and human experiments showing 82.4% identification accuracy and 86.4% preference over ATOMIC baselines.