activity
20192026
most citedLearning Multi-granularity User Intent Unit for Session-based Recommendation

85 citations · 204 across the 23 of their papers we have counts for

collaborators

23 papers

cs.CL2026

SCOUT: Active Information Foraging for Long-Text Understanding with Decoupled Epistemic States

Zhenliang Zhang, Wenqing Wang, Yong Hu +4

Long-Text Understanding (LTU) at million-token scale requires balancing reasoning fidelity with computational efficiency. Frontier long-context LLMs can process millions of token c…

cs.LG2024★ 2 cited

MTL-LoRA: Low-Rank Adaptation for Multi-Task Learning

Yaming Yang, Dilxat Muhtar, Yelong Shen +9

Parameter-efficient fine-tuning (PEFT) has been widely employed for domain adaptation, with LoRA being one of the most prominent methods due to its simplicity and effectiveness. Ho…

cs.IR2024

Direct Preference Optimization for LLM-Enhanced Recommendation Systems

Chao Sun, Yaobo Liang, Yaming Yang +3

Large Language Models (LLMs) have exhibited remarkable performance across a wide range of domains, motivating research into their potential for recommendation systems. Early effort…

cs.LG2024

You Can't Ignore Either: Unifying Structure and Feature Denoising for Robust Graph Learning

Tianmeng Yang, Jiahao Meng, Min Zhou +4

Recent research on the robustness of Graph Neural Networks (GNNs) under noises or attacks has attracted great attention due to its importance in real-world applications. Most previ…

cs.IR2023★ 1 cited

Self-Supervised Multi-Modal Sequential Recommendation

Kunzhe Song, Qingfeng Sun, Can Xu +2

With the increasing development of e-commerce and online services, personalized recommendation systems have become crucial for enhancing user satisfaction and driving business reve…

cs.CL2022

MMDialog: A Large-scale Multi-turn Dialogue Dataset Towards Multi-modal Open-domain Conversation

Jiazhan Feng, Qingfeng Sun, Can Xu +5

Responding with multi-modal content has been recognized as an essential capability for an intelligent conversational agent. In this paper, we introduce the MMDialog dataset to bett…