2 citations · 3 across the 5 of their papers we have counts for
6 papers
QProtFuse: Query-Guided Layer Fusion for Retrieval-Augmented Protein Function Prediction
Mianzhi Pan, Peishuo Liu, Yawen Ouyang +4
Predicting protein functions from amino acid sequences is essential to understanding biological processes. Large language models (LLMs) offer flexible function descriptions to natu…
OSReward: Instituting Standardized Evaluation for Cross-Platform Computer-Use Reward Models
Qiushi Sun, Kanzhi Cheng, Yian Wang +20
Computer-using agents (CUAs) are advancing rapidly across the digital world. A CUA trajectory records the agent's actions, states, and reasoning. Verifying whether it fulfilled the…
Enhancing Spatial Reasoning in Large Language Models for Metal-Organic Frameworks Structure Prediction
Mianzhi Pan, JianFei Li, Peishuo Liu +5
Metal-organic frameworks (MOFs) are porous crystalline materials with broad applications such as carbon capture and drug delivery, yet accurately predicting their 3D structures rem…
A Periodic Bayesian Flow for Material Generation
Hanlin Wu, Yuxuan Song, Jingjing Gong +6
Generative modeling of crystal data distribution is an important yet challenging task due to the unique periodic physical symmetry of crystals. Diffusion-based methods have shown e…
MoMa: A Modular Deep Learning Framework for Material Property Prediction
Botian Wang, Yawen Ouyang, Yaohui Li +8
Deep learning methods for material property prediction have been widely explored to advance materials discovery. However, the prevailing pre-train then fine-tune paradigm often fai…
Vision-Language Models Can Self-Improve Reasoning via Reflection
Kanzhi Cheng, Yantao Li, Fangzhi Xu +3
Chain-of-thought (CoT) has proven to improve the reasoning capability of large language models (LLMs). However, due to the complexity of multimodal scenarios and the difficulty in…