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20242026
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cs.CL2026

Multi-Agent Collaborative Filtering: Orchestrating Users and Items for Agentic Recommendations

Yu Xia, Sungchul Kim, Tong Yu +2

Agentic recommendations cast recommenders as large language model (LLM) agents that can plan, reason, use tools, and interact with users of varying preferences in web applications.…

cs.CL2025

Pluralistic Off-policy Evaluation and Alignment

Chengkai Huang, Junda Wu, Zhouhang Xie +6

Personalized preference alignment for LLMs with diverse human preferences requires evaluation and alignment methods that capture pluralism. Most existing preference alignment datas…

cs.CL2025

SAND: Boosting LLM Agents with Self-Taught Action Deliberation

Yu Xia, Yiran Shen, Junda Wu +5

Large Language Model (LLM) agents are commonly tuned with supervised finetuning on ReAct-style expert trajectories or preference optimization over pairwise rollouts. Most of these…

cs.CL2025

A Survey on Personalized and Pluralistic Preference Alignment in Large Language Models

Zhouhang Xie, Junda Wu, Yiran Shen +9

Personalized preference alignment for large language models (LLMs), the process of tailoring LLMs to individual users' preferences, is an emerging research direction spanning the a…

cs.CL2025

Knowledge-Aware Query Expansion with Large Language Models for Textual and Relational Retrieval

Yu Xia, Junda Wu, Sungchul Kim +4

Large language models (LLMs) have been used to generate query expansions augmenting original queries for improving information search. Recent studies also explore providing LLMs wi…

cs.CL2025

Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs

Yu Xia, Rui Wang, Xu Liu +5

Chain-of-Thought (CoT) has been a widely adopted prompting method, eliciting impressive reasoning abilities of Large Language Models (LLMs). Inspired by the sequential thought stru…