4 citations · 9 across the 9 of their papers we have counts for
5 papers · 1 filter
KALE-LM-Chem: Vision and Practice Toward an AI Brain for Chemistry
Weichen Dai, Yezeng Chen, Zijie Dai +9
Recent advancements in large language models (LLMs) have demonstrated strong potential for enabling domain-specific intelligence. In this work, we present our vision for building a…
Exploring The Neural Burden In Pruned Models: An Insight Inspired By Neuroscience
Zeyu Wang, Weichen Dai, Xiangyu Zhou +2
Vision Transformer and its variants have been adopted in many visual tasks due to their powerful capabilities, which also bring significant challenges in computation and storage. C…
COEFF-KANs: A Paradigm to Address the Electrolyte Field with KANs
Xinhe Li, Zhuoying Feng, Yezeng Chen +4
To reduce the experimental validation workload for chemical researchers and accelerate the design and optimization of high-energy-density lithium metal batteries, we aim to leverag…
Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations
Chenyu You, Yifei Min, Weicheng Dai +3
Fine-tuning pre-trained vision-language models, like CLIP, has yielded success on diverse downstream tasks. However, several pain points persist for this paradigm: (i) directly tun…
MInD: Improving Multimodal Sentiment Analysis via Multimodal Information Disentanglement
Weichen Dai, Xingyu Li, Zeyu Wang +4
Learning effective joint representations has been a central task in multi-modal sentiment analysis. Previous works addressing this task focus on exploring sophisticated fusion tech…