works on

From the 1 of 10 linked papers with an AI index.

collaborators
Showing cs.IRShow all

5 papers · 1 filter

cs.IR2026

Think When Needed: Model-Aware Reasoning Routing for LLM-based Ranking

Huizhong Guo, Tianjun Wei, Dongxia Wang +4

The paper introduces a lightweight router that decides per query whether to apply reasoning (chain‑of‑thought) or direct inference with large language models for ranking, using pre…

cs.IR2026

MMGRid: Navigating Temporal-aware and Cross-domain Generative Recommendation via Model Merging

Tianjun Wei, Enneng Yang, Yingpeng Du +3

Model merging (MM) offers an efficient mechanism for integrating multiple specialized models without access to original training data or costly retraining. While MM has demonstrate…

cs.IR2026

Diagnostic-Guided Dynamic Profile Optimization for LLM-based User Simulators in Sequential Recommendation

Hongyang Liu, Zhu Sun, Tianjun Wei +3

Recent advances in large language models (LLMs) have enabled realistic user simulators for developing and evaluating recommender systems (RSs). However, existing LLM-based simulato…

cs.IR2025

LLM-Driven Dual-Level Multi-Interest Modeling for Recommendation

Ziyan Wang, Yingpeng Du, Zhu Sun +4

Recently, much effort has been devoted to modeling users' multi-interests based on their behaviors or auxiliary signals. However, existing methods often rely on heuristic assumptio…

cs.IR2025

Enhancing New-item Fairness in Dynamic Recommender Systems

Huizhong Guo, Zhu Sun, Dongxia Wang +3

New-items play a crucial role in recommender systems (RSs) for delivering fresh and engaging user experiences. However, traditional methods struggle to effectively recommend new-it…