3 papers
cs.IR2026
RAGR: Review-Augmented Generative Recommendation
Yingyi Zhang, Junyi Li, Yejing Wang +8
Sequential recommendation (SR) is traditionally formulated as next-item prediction over chronological item interactions. Although recent generative recommendation (GR) methods intr…
cs.LG2025
APLOT: Robust Reward Modeling via Adaptive Preference Learning with Optimal Transport
Zhuo Li, Yuege Feng, Dandan Guo +3
The reward model (RM) plays a crucial role in aligning Large Language Models (LLMs) with human preferences through Reinforcement Learning, where the Bradley-Terry (BT) objective ha…
cs.CL2025
Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm
Zhuo Li, Yuhao Du, Xiaoqi Jiao +5
Selecting high-quality and diverse training samples from extensive datasets plays a crucial role in reducing training overhead and enhancing the performance of Large Language Model…