1 citations · 1 across the 4 of their papers we have counts for
6 papers
PACT: Defending Recommendation against Promotional News Rewriting via Attack-Diverse Score Consistency
Chongxian Chen, Fan Mo, Xin Fan +1
Personalized news recommenders are increasingly vulnerable to LLM-powered promotional attacks, where content providers rephrase headlines to manipulate rankings without altering un…
Policy-Conditioned Constrained Decoding for Column-Level Access Control in Text-to-SQL
Ryoto Miyamoto, Xin Fan, Hayato Yamana
Text-to-SQL is increasingly deployed across trust boundaries between data providers and users. Such deployment must balance three competing requirements: policy compliance, answer…
OpenLVLM-MIA: A Controlled Benchmark Revealing the Limits of Membership Inference Attacks on Large Vision-Language Models
Ryoto Miyamoto, Xin Fan, Fuyuko Kido +2
OpenLVLM-MIA is a new benchmark that highlights fundamental challenges in evaluating membership inference attacks (MIA) against large vision-language models (LVLMs). While prior wo…
Light distillation for Incremental Graph Convolution Collaborative Filtering
X Fan, F Mo, C Chen +1
Recommender systems presently utilize vast amounts of data and play a pivotal role in enhancing user experiences. Graph Convolution Networks (GCNs) have surfaced as highly efficien…
Personalized Fashion Recommendation with Image Attributes and Aesthetics Assessment
Chongxian Chen, Fan Mo, Xin Fan +1
Personalized fashion recommendation is a difficult task because 1) the decisions are highly correlated with users' aesthetic appetite, which previous work frequently overlooks, and…
Data-Efficient Massive Tool Retrieval: A Reinforcement Learning Approach for Query-Tool Alignment with Language Models
Yuxiang Zhang, Xin Fan, Junjie Wang +4
Recent advancements in large language models (LLMs) integrated with external tools and APIs have successfully addressed complex tasks by using in-context learning or fine-tuning. D…