16 citations · 25 across the 11 of their papers we have counts for
4 papers · 1 filter
Building AI Research Teams for Autonomous Discovery of Linear Attention Architectures
Yujian Liu, Li An, Zelin He +5
Autonomous agents can increasingly propose ideas, modify code, and run experiments, creating an opportunity to accelerate scientific discovery using teams of collaborative AI resea…
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…
Learnability-Informed Fine-Tuning of Diffusion Language Models
Shubham Parashar, Atharv Chagi, Jacob Helwig +5
We aim to improve the reasoning capabilities of diffusion language models (DLMs). While SFT is a popular post-training recipe for autoregressive models, its use in DLMs faces chall…
Orbital Transformers for Predicting Wavefunctions in Time-Dependent Density Functional Theory
Xuan Zhang, Haiyang Yu, Chengdong Wang +3
We aim to learn wavefunctions simulated by time-dependent density functional theory (TDDFT), which can be efficiently represented as linear combination coefficients of atomic orbit…