5 citations · 5 across the 6 of their papers we have counts for
4 papers · 1 filter
Escaping the BLEU Trap: A Signal-Grounded Framework with Decoupled Semantic Guidance for EEG-to-Text Decoding
Yuchen Wang, Haonan Wang, Yu Guo +2
Decoding natural language from non-invasive EEG signals is a promising yet challenging task. However, current state-of-the-art models remain constrained by three fundamental issues…
Compose and Fuse: Revisiting the Foundational Bottlenecks in Multimodal Reasoning
Yucheng Wang, Yifan Hou, Aydin Javadov +2
Multimodal large language models (MLLMs) promise enhanced reasoning by integrating diverse inputs such as text, vision, and audio. Yet cross-modal reasoning remains underexplored,…
DREAM: Disentangling Risks to Enhance Safety Alignment in Multimodal Large Language Models
Jianyu Liu, Hangyu Guo, Ranjie Duan +14
Multimodal Large Language Models (MLLMs) pose unique safety challenges due to their integration of visual and textual data, thereby introducing new dimensions of potential attacks…
TEGEE: Task dEfinition Guided Expert Ensembling for Generalizable and Few-shot Learning
Xingwei Qu, Yiming Liang, Yucheng Wang +10
Large Language Models (LLMs) exhibit the ability to perform in-context learning (ICL), where they acquire new tasks directly from examples provided in demonstrations. This process…