activity
20242026
most citedBeyond Models! Explainable Data Valuation and Metric Adaption for Recommendation

1 citations · 1 across the 12 of their papers we have counts for

collaborators
Showing 2025Show all

9 papers · 1 filter

cs.IR2025

Have We Really Understood Collaborative Information? An Empirical Investigation

Xiaokun Zhang, Zhaochun Ren, Bowei He +2

Collaborative information serves as the cornerstone of recommender systems which typically focus on capturing it from user-item interactions to deliver personalized services. Howev…

cs.LG2025

SDrug: Bridging Protein Sequence and 3D Structure in Contrastive Representation Learning for Virtual Screening

Bowei He, Bowen Gao, Yankai Chen +5

Virtual screening (VS) is an essential task in drug discovery, focusing on the identification of small-molecule ligands that bind to specific protein pockets. Existing deep learnin…

cs.CL2025

RECODE-H: A Benchmark for Research Code Development with Interactive Human Feedback

Chunyu Miao, Henry Peng Zou, Yangning Li +28

Large language models (LLMs) show the promise in supporting scientific research implementation, yet their ability to generate correct and executable code remains limited. Existing…

cs.AI2025

Spatial CAPTCHA: Generatively Benchmarking Spatial Reasoning for Human-Machine Differentiation

Arina Kharlamova, Bowei He, Chen Ma +1

Online services rely on CAPTCHAs as a first line of defense against automated abuse, yet recent advances in multi-modal large language models (MLLMs) have eroded the effectiveness…

cs.IR2025

Counterfactual Multi-player Bandits for Explainable Recommendation Diversification

Yansen Zhang, Bowei He, Xiaokun Zhang +3

Existing recommender systems tend to prioritize items closely aligned with users' historical interactions, inevitably trapping users in the dilemma of ``filter bubble''. Recent eff…

cs.IR2025

A Survey on Side Information-driven Session-based Recommendation: From a Data-centric Perspective

Xiaokun Zhang, Bo Xu, Chenliang Li +4

Session-based recommendation is gaining increasing attention due to its practical value in predicting the intents of anonymous users based on limited behaviors. Emerging efforts in…