5 papers
CellFluxRL: Biologically-Constrained Virtual Cell Modeling via Reinforcement Learning
Dongxia Wu, Shiye Su, Yuhui Zhang +4
Building virtual cells with generative models to simulate cellular behavior in silico is emerging as a promising paradigm for accelerating drug discovery. However, prior image-base…
Three Forms of Stochastic Injection for Improved Distribution-to-Distribution Generative Modeling
Shiye Su, Yuhui Zhang, Linqi Zhou +2
Modeling transformations between arbitrary data distributions is a fundamental scientific challenge, arising in applications like drug discovery and evolutionary simulation. While…
OpenThoughts: Data Recipes for Reasoning Models
Etash Guha, Ryan Marten, Sedrick Keh +47
Reasoning models have made rapid progress on many benchmarks involving math, code, and science. Yet, there are still many open questions about the best training recipes for reasoni…
ALMANACS: A Simulatability Benchmark for Language Model Explainability
Edmund Mills, Shiye Su, Stuart Russell +1
How do we measure the efficacy of language model explainability methods? While many explainability methods have been developed, they are typically evaluated on bespoke tasks, preve…
Explaining Hypergraph Neural Networks: From Local Explanations to Global Concepts
Shiye Su, Iulia Duta, Lucie Charlotte Magister +1
Hypergraph neural networks are a class of powerful models that leverage the message passing paradigm to learn over hypergraphs, a generalization of graphs well-suited to describing…