59 citations · 211 across the 39 of their papers we have counts for
7 papers · 1 filter
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…
MM-ToolSandBox: A Unified Framework for Evaluating Visual Tool-Calling Agents
Kaixin Ma, Di Feng, Alexander Metz +3
We introduce MM-ToolSandBox, a benchmark and evaluation framework for visually grounded tool-calling agents. The framework provides a stateful execution environment spanning 500+ t…
Sparse Evidence Can Suffice: Agentic Evidence Seeking for Multimodal Video Misinformation Detection
Haochen Zhao, Yongxiu Xu, Xinkui Lin +6
Multimodal video misinformation detection is commonly formulated as a holistic video-understanding task, where the entire video and its associated content are processed and judged…
Learning Structure, Energy, and Dynamics: A Survey of Artificial Intelligence for Protein Dynamics
Haocheng Tang, Liang Shi, Ya-Shi Zhang +3
Protein dynamics underlie many biological functions, yet remain difficult to characterize due to the high computational cost of molecular dynamics simulations and the scarcity of d…
Atomic Trajectory Modeling with State Space Models for Biomolecular Dynamics
Liang Shi, Jiarui Lu, Junqi Liu +3
Understanding the dynamic behavior of biomolecules is fundamental to elucidating biological function and facilitating drug discovery. While Molecular Dynamics (MD) simulations prov…
ASTRA-bench: Evaluating Tool-Use Agent Reasoning and Action Planning with Personal User Context
Zidi Xiu, David Q. Sun, Kevin Cheng +9
Next-generation AI must manage vast personal data, diverse tools, and multi-step reasoning, yet most benchmarks remain context-free and single-turn. We present ASTRA-bench (Assista…
Conditionally Site-Independent Neural Evolution of Antibody Sequences
Stephen Zhewen Lu, Aakarsh Vermani, Kohei Sanno +4
Common deep learning approaches for antibody engineering focus on modeling the marginal distribution of sequences. By treating sequences as independent samples, however, these meth…