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20222026
most citedWhen Large Language Models Meet Personalization: Perspectives of Challenges and Opportunities

338 citations · 454 across the 70 of their papers we have counts for

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Showing 2025 · cs.CLShow all

6 papers · 2 filters

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

RAPID: Efficient Retrieval-Augmented Long Text Generation with Writing Planning and Information Discovery

Hongchao Gu, Dexun Li, Kuicai Dong +6

Generating knowledge-intensive and comprehensive long texts, such as encyclopedia articles, remains significant challenges for Large Language Models. It requires not only the preci…

cs.CL2025

Learning to Substitute Components for Compositional Generalization

Zhaoyi Li, Gangwei Jiang, Chenwang Wu +3

Despite the rising prevalence of neural language models, recent empirical evidence suggests their deficiency in compositional generalization. One of the current de-facto solutions…