activity
20142025
most citedGeneralization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints

53 citations · 94 across the 22 of their papers we have counts for

collaborators

24 papers

cs.IR20241 cited

Towards a Unified Paradigm: Integrating Recommendation Systems as a New Language in Large Models

Kai Zheng, Qingfeng Sun, Can Xu +2

This paper explores the use of Large Language Models (LLMs) for sequential recommendation, which predicts users' future interactions based on their past behavior. We introduce a ne…

cs.IR20242 cited

On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective

Hung Vinh Tran, Tong Chen, Guanhua Ye +3

Content-based Recommender Systems (CRSs) play a crucial role in shaping user experiences in e-commerce, online advertising, and personalized recommendations. However, due to the va…

cs.DB2024

Less is More: Efficient Time Series Dataset Condensation via Two-fold Modal Matching--Extended Version

Hao Miao, Ziqiao Liu, Yan Zhao +4

The expanding instrumentation of processes throughout society with sensors yields a proliferation of time series data that may in turn enable important applications, e.g., related…

cs.IR20241 cited

DimeRec: A Unified Framework for Enhanced Sequential Recommendation via Generative Diffusion Models

Wuchao Li, Rui Huang, Haijun Zhao +10

Sequential Recommendation (SR) plays a pivotal role in recommender systems by tailoring recommendations to user preferences based on their non-stationary historical interactions. A…

cs.CV2024

MaskVD: Region Masking for Efficient Video Object Detection

Sreetama Sarkar, Gourav Datta, Souvik Kundu +3

Video tasks are compute-heavy and thus pose a challenge when deploying in real-time applications, particularly for tasks that require state-of-the-art Vision Transformers (ViTs). S…

cs.CL2024

Talk With Human-like Agents: Empathetic Dialogue Through Perceptible Acoustic Reception and Reaction

Haoqiu Yan, Yongxin Zhu, Kai Zheng +4

Large Language Model (LLM)-enhanced agents become increasingly prevalent in Human-AI communication, offering vast potential from entertainment to professional domains. However, cur…