9 papers
Towards Simple and Provable Parameter-Free Adaptive Gradient Methods
Yuanzhe Tao, Yifeng Liu, Huizhuo Yuan +3
Optimization algorithms such as AdaGrad and Adam have significantly advanced the training of deep models by dynamically adjusting the learning rate during the optimization process.…
Group Representational Position Encoding
Yifan Zhang, Zixiang Chen, Yifeng Liu +6
We present GRAPE (Group Representational Position Encoding), a unified framework for positional encoding based on group actions. GRAPE unifies two families of mechanisms: (i) multi…
On the Design of KL-Regularized Policy Gradient Algorithms for LLM Reasoning
Yifan Zhang, Yifeng Liu, Huizhuo Yuan +3
Policy gradient algorithms have been successfully applied to enhance the reasoning capabilities of large language models (LLMs). KL regularization is ubiquitous, yet the design sur…
Tensor Product Attention Is All You Need
Yifan Zhang, Yifeng Liu, Huizhuo Yuan +4
Scaling language models to handle longer input sequences typically necessitates large key-value (KV) caches, resulting in substantial memory overhead during inference. In this pape…
ConfRover: Simultaneous Modeling of Protein Conformation and Dynamics via Autoregression
Yuning Shen, Lihao Wang, Huizhuo Yuan +3
Understanding protein dynamics is critical for elucidating their biological functions. The increasing availability of molecular dynamics (MD) data enables the training of deep gene…
Causal Attention with Lookahead Keys
Zhuoqing Song, Peng Sun, Huizhuo Yuan +1
In standard causal attention, each token's query, key, and value (QKV) are static and encode only preceding context. We introduce CAuSal aTtention with Lookahead kEys (CASTLE), an…