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cs.LG2025
Unlocking Out-of-Distribution Generalization in Transformers via Recursive Latent Space Reasoning
Awni Altabaa, Siyu Chen, John Lafferty +1
Systematic, compositional generalization beyond the training distribution remains a core challenge in machine learning -- and a critical bottleneck for the emergent reasoning abili…
cs.LG2025
Taming Polysemanticity in LLMs: Provable Feature Recovery via Sparse Autoencoders
Siyu Chen, Heejune Sheen, Xuyuan Xiong +2
We study the challenge of achieving theoretically grounded feature recovery using Sparse Autoencoders (SAEs) for the interpretation of Large Language Models. Existing SAE training…
cs.LG2025
In-Context Linear Regression Demystified: Training Dynamics and Mechanistic Interpretability of Multi-Head Softmax Attention
Jianliang He, Xintian Pan, Siyu Chen +1
We study how multi-head softmax attention models are trained to perform in-context learning on linear data. Through extensive empirical experiments and rigorous theoretical analysi…