39 citations · 126 across the 40 of their papers we have counts for
10 papers · 1 filter
On the Effectiveness of Unlearning in Session-Based Recommendation
Xin Xin, Liu Yang, Ziqi Zhao +4
Session-based recommendation predicts users' future interests from previous interactions in a session. Despite the memorizing of historical samples, the request of unlearning, i.e.…
Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure
Jiyuan Yang, Yue Ding, Yidan Wang +7
Sequential recommendation (SR) models are typically trained on user-item interactions which are affected by the system exposure bias, leading to the user preference learned from th…
Multi-Defendant Legal Judgment Prediction via Hierarchical Reasoning
Yougang Lyu, Jitai Hao, Zihan Wang +6
Multiple defendants in a criminal fact description generally exhibit complex interactions, and cannot be well handled by existing Legal Judgment Prediction (LJP) methods which focu…
Learning Robust Sequential Recommenders through Confident Soft Labels
Shiguang Wu, Xin Xin, Pengjie Ren +4
Sequential recommenders that are trained on implicit feedback are usually learned as a multi-class classification task through softmax-based loss functions on one-hot class labels.…
Instruction Distillation Makes Large Language Models Efficient Zero-shot Rankers
Weiwei Sun, Zheng Chen, Xinyu Ma +6
Recent studies have demonstrated the great potential of Large Language Models (LLMs) serving as zero-shot relevance rankers. The typical approach involves making comparisons betwee…
Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related Features
Zihan Wang, Ziqi Zhao, Zhumin Chen +3
Few-shot named entity recognition (NER) has shown remarkable progress in identifying entities in low-resource domains. However, few-shot NER methods still struggle with out-of-doma…