2 citations · 3 across the 7 of their papers we have counts for
7 papers
Shared Actors Need Not Share Critics: Effects of Value Mismatch in Parallel Reinforcement Learning
Zhenya Liu, Yang Meng, Zhuokai Zhao +2
When a single policy is trained in parallel across multiple environments of the same task, such as procedurally generated levels, randomized dynamics, or curricula, implementations…
Rethinking Transfer in Continual Learning: A Replay-Based Realisation
Yang Meng, Zhenya Liu, Zhuokai Zhao +1
Continual learning studies how deployed language models can continually acquire new tasks without expensive retraining from scratch. Existing methods, whether rehearsal-based (repl…
Cognitive Structure Generation: From Educational Priors to Policy Optimization
Hengnian Gu, Zhifu Chen, Yuxin Chen +2
Cognitive structure is a student's subjective organization of an objective knowledge system, reflected in the psychological construction of concepts and their relations. However, c…
SurgiSR4K: A High-Resolution Endoscopic Video Dataset for Robotic-Assisted Minimally Invasive Procedures
Fengyi Jiang, Xiaorui Zhang, Lingbo Jin +11
High-resolution imaging is crucial for enhancing visual clarity and enabling precise computer-assisted guidance in minimally invasive surgery (MIS). Despite the increasing adoption…
Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment
Chaoqi Wang, Zhuokai Zhao, Yibo Jiang +8
Recent advances in large language models (LLMs) have demonstrated significant progress in performing complex tasks. While Reinforcement Learning from Human Feedback (RLHF) has been…
Preference Optimization with Multi-Sample Comparisons
Chaoqi Wang, Zhuokai Zhao, Chen Zhu +8
Recent advancements in generative models, particularly large language models (LLMs) and diffusion models, have been driven by extensive pretraining on large datasets followed by po…
BitCoin: Bidirectional Tagging and Supervised Contrastive Learning based Joint Relational Triple Extraction Framework
Luyao He, Zhongbao Zhang, Sen Su +1
Relation triple extraction (RTE) is an essential task in information extraction and knowledge graph construction. Despite recent advancements, existing methods still exhibit certai…