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Renmin University of China
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TurnSight reveals that leveraging turn-level hindsight can dramatically enhance LLM performance in complex tool interactions, outperforming conventional reinforcement learning techniques.
A unified taxonomy reveals how agentic architectures can transform recommender systems into more autonomous and interactive entities.
OneRank achieves superior multi-task recommendation performance by seamlessly integrating task-specific learning within a unified Transformer framework, eliminating the traditional encoder-predictor bottleneck.
