5 papers
Kwai Summary Attention Technical Report
Chenglong Chu, Guorui Zhou, Guowang Zhang +35
Long-context ability, has become one of the most important iteration direction of next-generation Large Language Models, particularly in semantic understanding/reasoning, code agen…
Towards Fair Large Language Model-based Recommender Systems without Costly Retraining
Jin Li, Huilin Gu, Shoujin Wang +5
Large Language Models (LLMs) have revolutionized Recommender Systems (RS) through advanced generative user modeling. However, LLM-based RS (LLM-RS) often inadvertently perpetuates…
Revealing Multimodal Causality with Large Language Models
Jin Li, Shoujin Wang, Qi Zhang +5
Uncovering cause-and-effect mechanisms from data is fundamental to scientific progress. While large language models (LLMs) show promise for enhancing causal discovery (CD) from uns…
Generating with Fairness: A Modality-Diffused Counterfactual Framework for Incomplete Multimodal Recommendations
Jin Li, Shoujin Wang, Qi Zhang +2
Incomplete scenario is a prevalent, practical, yet challenging setting in Multimodal Recommendations (MMRec), where some item modalities are missing due to various factors. Recentl…
Structural Representation Learning and Disentanglement for Evidential Chinese Patent Approval Prediction
Jinzhi Shan, Qi Zhang, Chongyang Shi +3
Automatic Chinese patent approval prediction is an emerging and valuable task in patent analysis. However, it involves a rigorous and transparent decision-making process that inclu…