2 citations · 2 across the 2 of their papers we have counts for
5 papers
Answer-Consistent Chain-of-thought Reinforcement Learning For Multi-modal Large Langauge Models
Minbin Huang, Runhui Huang, Chuanyang Zheng +4
Recent advances in large language models (LLMs) have demonstrated that reinforcement learning with verifiable rewards (RLVR) can significantly enhance reasoning abilities by direct…
Pre-training for Recommendation Unlearning
Guoxuan Chen, Lianghao Xia, Chao Huang
Modern recommender systems powered by Graph Neural Networks (GNNs) excel at modeling complex user-item interactions, yet increasingly face scenarios requiring selective forgetting…
Self-Adjust Softmax
Chuanyang Zheng, Yihang Gao, Guoxuan Chen +7
The softmax function is crucial in Transformer attention, which normalizes each row of the attention scores with summation to one, achieving superior performances over other altern…
LightGNN: Simple Graph Neural Network for Recommendation
Guoxuan Chen, Lianghao Xia, Chao Huang
Graph neural networks (GNNs) have demonstrated superior performance in collaborative recommendation through their ability to conduct high-order representation smoothing, effectivel…
SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator
Guoxuan Chen, Han Shi, Jiawei Li +7
Large Language Models (LLMs) have exhibited exceptional performance across a spectrum of natural language processing tasks. However, their substantial sizes pose considerable chall…