5 citations · 5 across the 4 of their papers we have counts for
5 papers
Intern-S2-Preview: Scientific Agentic Foundation Model
Lei Bai, Jiaqi Cao, Chiyu Chen +121
Scientific discovery increasingly requires AI systems that can reason over scientific evidence of heterogeneous modalities, interact with scientific tools and environments, and sus…
MoLAN: A Unified Modality-Aware Noise Dynamic Editing Framework for Multimodal Sentiment Analysis
Xingle Xu, Yongkang Liu, Dexian Cai +4
Multimodal Sentiment Analysis aims to integrate information from various modalities, such as audio, visual, and text, to make complementary predictions. However, it often struggles…
Why Do More Experts Fail? A Theoretical Analysis of Model Merging
Zijing Wang, Xingle Xu, Yongkang Liu +6
Model merging dramatically reduces storage and computational resources by combining multiple expert models into a single multi-task model. Although recent model merging methods hav…
Look Within or Look Beyond? A Theoretical Comparison Between Parameter-Efficient and Full Fine-Tuning
Yongkang Liu, Xingle Xu, Ercong Nie +5
Parameter-Efficient Fine-Tuning (PEFT) methods achieve performance comparable to Full Fine-Tuning (FFT) while requiring significantly fewer computing resources, making it the go-to…
Affective Computing in the Era of Large Language Models: A Survey from the NLP Perspective
Yiqun Zhang, Xiaocui Yang, Xingle Xu +8
Affective Computing (AC) integrates computer science, psychology, and cognitive science to enable machines to recognize, interpret, and simulate human emotions across domains such…