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…
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…
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…
Probing Commonsense Reasoning Capability of Text-to-Image Generative Models via Non-visual Description
Mianzhi Pan, Jianfei Li, Mingyue Yu +4
Commonsense reasoning, the ability to make logical assumptions about daily scenes, is one core intelligence of human beings. In this work, we present a novel task and dataset for e…
Food-500 Cap: A Fine-Grained Food Caption Benchmark for Evaluating Vision-Language Models
Zheng Ma, Mianzhi Pan, Wenhan Wu +4
Vision-language models (VLMs) have shown impressive performance in substantial downstream multi-modal tasks. However, only comparing the fine-tuned performance on downstream tasks…
Probing Cross-modal Semantics Alignment Capability from the Textual Perspective
Zheng Ma, Shi Zong, Mianzhi Pan +4
In recent years, vision and language pre-training (VLP) models have advanced the state-of-the-art results in a variety of cross-modal downstream tasks. Aligning cross-modal semanti…