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20192026
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cs.LG2026

INFUSER: Influence-Guided Self-Evolution Improves Reasoning

Siyu Chen, Miao Lu, Beining Wu +7

Self-evolution offers a scalable path to stronger reasoning: a pretrained language model improves itself with only minimal external supervision. Yet existing methods either depend…

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.LG2024

Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers

Siyu Chen, Heejune Sheen, Tianhao Wang +1

In-context learning (ICL) is a cornerstone of large language model (LLM) functionality, yet its theoretical foundations remain elusive due to the complexity of transformer architec…

cs.LG2024

Implicit Regularization of Gradient Flow on One-Layer Softmax Attention

Heejune Sheen, Siyu Chen, Tianhao Wang +1

We study gradient flow on the exponential loss for a classification problem with a one-layer softmax attention model, where the key and query weight matrices are trained separately…

cs.LG2024

Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality

Siyu Chen, Heejune Sheen, Tianhao Wang +1

We study the dynamics of gradient flow for training a multi-head softmax attention model for in-context learning of multi-task linear regression. We establish the global convergenc…