activity
20232026
most citedSwallowing the Bitter Pill: Simplified Scalable Conformer Generation

8 citations · 24 across the 15 of their papers we have counts for

collaborators

18 papers

cs.LG2026

How to Guide Your Language Flow

Rohit Dilip, Tianrong Chen, Yuyang Wang +3

We introduce a new method to guide flow matching models. Our approach, which we call probe guidance, uses the frozen internal states of an existing diffusion model to construct a g…

cs.LG2026

SimpleDesign: A Joint Model for Protein Sequence and Structure Codesign

Jiarui Lu, Yuyang Wang, Yizhe Zhang +4

Proteins are fundamental to biological processes, with their function determined by the complex interplay between the amino acid sequence and the three-dimensional structure. Devel…

cs.CV2026

Show Me Examples: Inferring Visual Concepts from Image Sets

Nick Stracke, Kolja Bauer, Stefan Andreas Baumann +3

Vision-language models (VLMs) can follow complex textual instructions, yet they struggle to reason from purely visual context. In particular, current models fail to infer shared co…

cs.CV2026

STARFlow2: Bridging Language Models and Normalizing Flows for Unified Multimodal Generation

Ying Shen, Tianrong Chen, Yuan Gao +6

Deep generative models have advanced rapidly across text and vision, motivating unified multimodal systems that can understand, reason over, and generate interleaved text-image seq…

cs.CV2026

Learning Long-term Motion Embeddings for Efficient Kinematics Generation

Nick Stracke, Kolja Bauer, Stefan Andreas Baumann +3

Understanding and predicting motion is a fundamental component of visual intelligence. Although modern video models exhibit strong comprehension of scene dynamics, exploring multip…

cs.CV2025

STARFlow-V: End-to-End Video Generative Modeling with Normalizing Flows

Jiatao Gu, Ying Shen, Tianrong Chen +6

Normalizing flows (NFs) are end-to-end likelihood-based generative models for continuous data, and have recently regained attention with encouraging progress on image generation. Y…