collaborators

5 papers

cs.SI2025

Constructing Political Coordinates: Aggregating Over the Opposition for Diverse News Recommendation

Eamon Earl, Chen Ding, Richard Valenzano +1

In the past two decades, open access to news and information has increased rapidly, empowering educated political growth within democratic societies. News recommender systems (NRSs…

cs.LG2025

MLLMEraser: Achieving Test-Time Unlearning in Multimodal Large Language Models through Activation Steering

Chenlu Ding, Jiancan Wu, Leheng Sheng +4

Multimodal large language models (MLLMs) have demonstrated remarkable capabilities across vision-language tasks, yet their large-scale deployment raises pressing concerns about mem…

cs.IR2025

On Negative-aware Preference Optimization for Recommendation

Chenlu Ding, Daoxuan Liu, Jiancan Wu +6

Recommendation systems leverage user interaction data to suggest relevant items while filtering out irrelevant (negative) ones. The rise of large language models (LLMs) has garnere…

cs.LG2025

Delayed Feedback Modeling with Influence Functions

Chenlu Ding, Jiancan Wu, Yancheng Yuan +5

In online advertising under the cost-per-conversion (CPA) model, accurate conversion rate (CVR) prediction is crucial. A major challenge is delayed feedback, where conversions may…

cs.AI2024

Unified Parameter-Efficient Unlearning for LLMs

Chenlu Ding, Jiancan Wu, Yancheng Yuan +5

The advent of Large Language Models (LLMs) has revolutionized natural language processing, enabling advanced understanding and reasoning capabilities across a variety of tasks. Fin…