1 citations · 1 across the 7 of their papers we have counts for
7 papers
Data-Efficient Autoregressive-to-Diffusion Language Models via On-Policy Distillation
Xingyu Su, Jacob Helwig, Shubham Parashar +6
We study the transformation of autoregressive models (ARLMs) into diffusion language models (DLMs). Rather than pretraining from scratch, prior work replaces the causal attention i…
Autonomous Agents for Scientific Discovery: Orchestrating Scientists, Language, Code, and Physics
Lianhao Zhou, Hongyi Ling, Cong Fu +14
Computing has long served as a cornerstone of scientific discovery. Recently, a paradigm shift has emerged with the rise of large language models (LLMs), introducing autonomous sys…
Language Models for Controllable DNA Sequence Design
Xingyu Su, Xiner Li, Yuchao Lin +3
We consider controllable DNA sequence design, where sequences are generated by conditioning on specific biological properties. While language models (LMs) such as GPT and BERT have…
Iterative Distillation for Reward-Guided Fine-Tuning of Diffusion Models in Biomolecular Design
Xingyu Su, Xiner Li, Masatoshi Uehara +7
We address the problem of fine-tuning diffusion models for reward-guided generation in biomolecular design. While diffusion models have proven highly effective in modeling complex,…
Dynamic Search for Inference-Time Alignment in Diffusion Models
Xiner Li, Masatoshi Uehara, Xingyu Su +5
Diffusion models have shown promising generative capabilities across diverse domains, yet aligning their outputs with desired reward functions remains a challenge, particularly in…
Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design
Masatoshi Uehara, Xingyu Su, Yulai Zhao +5
To fully leverage the capabilities of diffusion models, we are often interested in optimizing downstream reward functions during inference. While numerous algorithms for reward-gui…
Learning to Discover Regulatory Elements for Gene Expression Prediction
Xingyu Su, Haiyang Yu, Degui Zhi +1
We consider the problem of predicting gene expressions from DNA sequences. A key challenge of this task is to find the regulatory elements that control gene expressions. Here, we i…