activity
20232026
most citedA Survey of Personalization: From RAG to Agent

2 citations · 4 across the 22 of their papers we have counts for

collaborators

43 papers

cs.IR2026

MemSearch-o1: Empowering Large Language Models with Reasoning-Aligned Memory Growth in Agentic Search

Sheng Zhang, Junyi Li, Yingyi Zhang +7

Recent advances in large language models (LLMs) have scaled the potential for reasoning and agentic search, wherein models autonomously plan, retrieve, and reason over external kno…

cs.IR2026

Personalized Deep Research: A User-Centric Framework, Dataset, and Hybrid Evaluation for Knowledge Discovery

Xiaopeng Li, Wenlin Zhang, Yingyi Zhang +6

Deep Research agents driven by LLMs have automated the scholarly discovery pipeline, from planning and query formulation to iterative web exploration. Yet they remain constrained b…

cs.IR2026

UniRank: Unified List-wise Reranking via Confidence-Ordered Denoising

Pengyue Jia, Hailan Yang, Shuchang Liu +7

List-wise reranking arranges a request-specific pool of candidate items into an ordered slate that maximizes user satisfaction. Existing generative rerankers fall into two paradigm…

cs.CL2026

Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory

Derong Xu, Shuochen Liu, Pengfei Luo +8

Large language model (LLM) agents require long-term user memory for consistent personalization, but limited context windows hinder tracking evolving preferences over long interacti…

cs.IR20261 cited

From Local Indices to Global Identifiers: Generative Reranking for Recommender Systems via Global Action Space

Pengyue Jia, Xiaobei Wang, Yingyi Zhang +14

In modern recommender systems, list-wise reranking serves as a critical phase within the multi-stage pipeline, finalizing the exposed item sequence and directly impacting user sati…

cs.CL2026

MultiDx: A Multi-Source Knowledge Integration Framework towards Diagnostic Reasoning

Yimin Deng, Zhenxi Lin, Yejing Wang +9

Diagnostic prediction and clinical reasoning are critical tasks in healthcare applications. While Large Language Models (LLMs) have shown strong capabilities in commonsense reasoni…