9 papers
NeurDuo-EEG: A Long-Sequence EEG Foundation Model with Persistent State and Explicit Memory
Yifan Wang, Haiping Liu, Yang Cui +13
Electroencephalography (EEG) is recorded continuously over hours, with relevant dynamics spanning timescales from milliseconds to hours. Most EEG foundation models nevertheless pro…
Seeing What Is Actually There: PriVE-Bench and PriVE-Tools for Counterfactual Evaluation of Agentic Visual Evidence in VLMs
Jingyu Sun, Jiachen Tu, Yuyang Xue +8
Vision-language models (VLMs) often answer visual questions using learned language and category priors rather than grounding their predictions in the image itself. Counterfactual i…
Are Reasoning Vision-Language Models Robust to Semantic Visual Distractions?
Yizheng Sun, Mochuan Zhan, Yanan Ma +10
Reasoning Vision-Language Models (VLMs) achieve strong performance on complex multimodal tasks, but reliable real-world application requires handling visual inputs that are messier…
Computational Lesions in Multilingual Language Models Separate Shared and Language-specific Brain Alignment
Yang Cui, Jingyuan Sun, Yizheng Sun +8
How the brain supports language across different languages is a basic question in neuroscience and a useful test for multilingual artificial intelligence. Neuroimaging has identifi…
Arg-LLaDA: Argument Summarization via Large Language Diffusion Models and Sufficiency-Aware Refinement
Hao Li, Yizheng Sun, Viktor Schlegel +3
Argument summarization aims to generate concise, structured representations of complex, multi-perspective debates. While recent work has advanced the identification and clustering…
Large Language Models in Argument Mining: A Survey
Hao Li, Viktor Schlegel, Yizheng Sun +2
Large Language Models (LLMs) have fundamentally reshaped Argument Mining (AM), shifting it from a pipeline of supervised, task-specific classifiers to a spectrum of prompt-driven,…
MIRA: Medical Time Series Foundation Model for Real-World Health Data
Hao Li, Bowen Deng, Chang Xu +8
A unified foundation model for medical time series -- pretrained on open access and ethics board-approved medical corpora -- offers the potential to reduce annotation burdens, mini…
Does Acceleration Cause Hidden Instability in Vision Language Models? Uncovering Instance-Level Divergence Through a Large-Scale Empirical Study
Yizheng Sun, Hao Li, Chang Xu +4
Vision-Language Models (VLMs) are powerful yet computationally intensive for widespread practical deployments. To address such challenge without costly re-training, post-training a…
LVPruning: An Effective yet Simple Language-Guided Vision Token Pruning Approach for Multi-modal Large Language Models
Yizheng Sun, Yanze Xin, Hao Li +3
Multi-modal Large Language Models (MLLMs) have achieved remarkable success by integrating visual and textual modalities. However, they incur significant computational overhead due…