6 papers
LabInstruct: Benchmarking Situated Instructional Video Generation for Lab Procedures
Yuming Fu, Weijia Wu, Jing Chen +5
Self-driving laboratories (SDLs) aim to automate the full experimental loop, from scientific decision-making to physical execution. Ideally, AI-generated plans could be carried out…
ChartJudgeBench: Evaluating LMM Judges for Chart-to-Code Generation
Lijian Wu, Henry Hengyuan Zhao, Zijian Zhang +3
Building strong chart-to-code systems increasingly relies on reinforcement learning, whose effectiveness depends critically on the quality of the reward signal. Large Multimodal Mo…
HADUA: Hierarchical Attention and Dynamic Uniform Alignment for Robust Cross-Subject Emotion Recognition
Jiahao Tang, Youjun Li, Yangxuan Zheng +4
Robust cross-subject emotion recognition from multimodal physiological signals remains a challenging problem, primarily due to modality heterogeneity and inter-subject distribution…
From Charts to Code: A Hierarchical Benchmark for Multimodal Models
Jiahao Tang, Henry Hengyuan Zhao, Lijian Wu +8
We introduce Chart2Code, a new benchmark for evaluating the chart understanding and code generation capabilities of large multimodal models (LMMs). Chart2Code is explicitly designe…
SDC-Net: A Domain Adaptation Framework with Semantic-Dynamic Consistency for Cross-Subject EEG Emotion Recognition
Jiahao Tang, Youjun Li, Xiangting Fan +6
Emotion recognition based on electroencephalography (EEG) holds significant promise for affective brain-computer interfaces (aBCIs). However, its practical deployment faces challen…
SDA-DDA Semi-supervised Domain Adaptation with Dynamic Distribution Alignment Network For Emotion Recognition Using EEG Signals
Jiahao Tang
In this paper, we focus on the challenge of individual variability in affective brain-computer interfaces (aBCI), which employs electroencephalogram (EEG) signals to monitor and re…