most citedEAGER-LLM: Enhancing Large Language Models as Recommenders through Exogenous Behavior-Semantic Integration

15 citations · 15 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

HVD: Human Vision-Driven Video Representation Learning for Text-Video Retrieval

Zequn Xie, Xin Liu, Boyun Zhang +3

The success of CLIP has driven substantial progress in text-video retrieval. However, current methods often suffer from "blind" feature interaction, where the model struggles to di…

cs.CL2025

Chat-Driven Text Generation and Interaction for Person Retrieval

Zequn Xie, Chuxin Wang, Sihang Cai +3

Text-based person search (TBPS) enables the retrieval of person images from large-scale databases using natural language descriptions, offering critical value in surveillance appli…

cs.CV2025

Astrea: A MOE-based Visual Understanding Model with Progressive Alignment

Xiaoda Yang, JunYu Lu, Hongshun Qiu +12

Vision-Language Models (VLMs) based on Mixture-of-Experts (MoE) architectures have emerged as a pivotal paradigm in multimodal understanding, offering a powerful framework for inte…

cs.CV2025

Towards Transformer-Based Aligned Generation with Self-Coherence Guidance

Shulei Wang, Wang Lin, Hai Huang +8

We introduce a novel, training-free approach for enhancing alignment in Transformer-based Text-Guided Diffusion Models (TGDMs). Existing TGDMs often struggle to generate semantical…

cs.IR202515 cited

EAGER-LLM: Enhancing Large Language Models as Recommenders through Exogenous Behavior-Semantic Integration

Minjie Hong, Yan Xia, Zehan Wang +8

Large language models (LLMs) are increasingly leveraged as foundational backbones in the development of advanced recommender systems, offering enhanced capabilities through their e…