8 papers
TOOL4POI: A Tool-Augmented LLM Framework for Next POI Recommendation
Dongsheng Wang, Shen Gao, Chengrui Huang +3
Next Point-of-Interest (POI) recommendation is a fundamental task in location-based services. While recent advances leverage Large Language Model (LLM) for sequential modeling, exi…
CoSineVerifier: Tool-Augmented Answer Verification for Computation-Oriented Scientific Questions
Ruixiang Feng, Zhenwei An, Yuntao Wen +9
Answer verification methods are widely employed in language model training pipelines spanning data curation, evaluation, and reinforcement learning with verifiable rewards (RLVR).…
Beyond Superficial Forgetting: Thorough Unlearning through Knowledge Density Estimation and Block Re-insertion
Feng Guo, Yuntao Wen, Shen Gao +2
Machine unlearning, which selectively removes harmful knowledge from a pre-trained model without retraining from scratch, is crucial for addressing privacy, regulatory compliance,…
CESRec: Constructing Pseudo Interactions for Sequential Recommendation via Conversational Feedback
Yifan Wang, Shen Gao, Jiabao Fang +3
Sequential Recommendation Systems (SRS) have become essential in many real-world applications. However, existing SRS methods often rely on collaborative filtering signals and fail…
Evolution without Large Models: Training Language Model with Task Principles
Minghang Zhu, Shen Gao, Zhengliang Shi +5
A common training approach for language models involves using a large-scale language model to expand a human-provided dataset, which is subsequently used for model training.This me…
Generative Next POI Recommendation with Semantic ID
Dongsheng Wang, Yuxi Huang, Shen Gao +3
Point-of-interest (POI) recommendation systems aim to predict the next destinations of user based on their preferences and historical check-ins. Existing generative POI recommendat…