Author

Yi-Ming Tang

2 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#machine learning Preprint Sep 2026

Understanding and Exploiting Anisotropy in Post-Training

LLM post-training combines supervised fine-tuning (SFT), a mode-covering forward-KL objective, with reinforcement learning (RL), a mode-seeking reverse-KL objective, with reinforcement learning (RL), a mode-seeking reverse-KL objective to exploit anisotropy, a division of labor that post-training can exploit.

Samyak Jha, Harshvardhan Saini, Yi-Zhen Liao et al. · 0 citations

#machine learning Preprint Sep 2026

What Does an LLM Learn from Reinforcement Learning? A Mechanistic Interpretability Perspective with Fixed-SAE Track

Fixed-SAE Track is introduced, a framework that trains one shared SAE per considered layer on activations pooled across the base model and all RL checkpoints, holding every feature direction fixed so that representation shifts are rigorously defined through the activations of interpretable SAE latents, including the de...

Ling-Heng Du, Yi-Ming Tang, Xufeng Duan et al. · 1 citation