3 citations · 4 across the 18 of their papers we have counts for
9 papers · 1 filter
IE as Cache: Information Extraction Enhanced Agentic Reasoning
Hang Lv, Sheng Liang, Hongchao Gu +5
Information Extraction aims to distill structured, decision-relevant information from unstructured text, serving as a foundation for downstream understanding and reasoning. However…
SpecSteer: Synergizing Local Context and Global Reasoning for Efficient Personalized Generation
Hang Lv, Sheng Liang, Hao Wang +6
Realizing personalized intelligence faces a core dilemma: sending user history to centralized large language models raises privacy concerns, while on-device small language models l…
CoSteer: Collaborative Decoding-Time Personalization via Local Delta Steering
Hang Lv, Sheng Liang, Hao Wang +6
Personalization has become crucial for adapting models to the diverse and evolving needs of users across cultural, temporal, and contextual dimensions. While existing methods often…
Prompting is not Enough: Exploring Knowledge Integration and Controllable Generation
Tingjia Shen, Hao Wang, Chuan Qin +5
Open-domain question answering (OpenQA) represents a cornerstone in natural language processing (NLP), primarily focused on extracting answers from unstructured textual data. With…
LLM Cache Bandit Revisited: Addressing Query Heterogeneity for Cost-Effective LLM Inference
Hantao Yang, Hong Xie, Defu Lian +1
This paper revisits the LLM cache bandit problem, with a special focus on addressing the query heterogeneity for cost-effective LLM inference. Previous works often assume uniform q…
Thought-Augmented Planning for LLM-Powered Interactive Recommender Agent
Haocheng Yu, Yaxiong Wu, Hao Wang +6
Interactive recommendation is a typical information-seeking task that allows users to interactively express their needs through natural language and obtain personalized recommendat…