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cs.LG2025
Explicit Preference Optimization: No Need for an Implicit Reward Model
Xiangkun Hu, Lemin Kong, Tong He +1
The generated responses of large language models (LLMs) are often fine-tuned to human preferences through a process called reinforcement learning from human feedback (RLHF). As RLH…
cs.LG2025
Sparse Autoencoders, Again?
Yin Lu, Xuening Zhu, Tong He +1
Is there really much more to say about sparse autoencoders (SAEs)? Autoencoders in general, and SAEs in particular, represent deep architectures that are capable of modeling low-di…
cs.LG2024★ 2 cited
BloomGML: Graph Machine Learning through the Lens of Bilevel Optimization
Amber Yijia Zheng, Tong He, Yixuan Qiu +2
Bilevel optimization refers to scenarios whereby the optimal solution of a lower-level energy function serves as input features to an upper-level objective of interest. These optim…