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A new training-free framework based on a simple yet powerful forward-looking strategy. (AACL)

A collection of public datasets and prediction tasks that incorporate personal and relational events. (LoG)

A novel framework that constructs an intent-centric knowledge graph where both users and items are explicitly linked. (LoG)

Utilizing an alignment-first strategy to transfer advanced reasoning skills to a non-reasoning model (NeurIPS).

An efficient solution to enforce the well-typedness of LLM functions. (EurIPS)

A systematic study of Mixture of Experts (MoE) continual pre-training. (NeurIPS)

A conversational dataset specifically designed to capture and manage inter-tool dependencies across diverse domains. (NeurIPS)

A novel reward modeling framework that is rubric-agnostic, generalizable and provides reasoned score assignments. (NeurIPS)