14 papers
From Agent Traces to Trust: A Survey of Evidence Tracing and Execution Provenance in LLM Agents
Yiqi Wang, Jiaqi Zhang, Taotao Cai +8
Large language model (LLM)-based agents are evolving from passive text generators into autonomous systems capable of planning, tool use, retrieval, memory access, environmental int…
Distance-Aware Joint Spatio-Temporal Graph Contrastive Learning for Major Depressive Disorder Diagnosis
Muhammad Asif Hasan, Yanming Zhu, Xuefei Yin +1
Major depressive disorder (MDD) is a common neuropsychiatric condition whose accurate diagnosis from resting-state functional magnetic resonance imaging (rs-fMRI) remains difficult…
fMRI-Diffusion: Generating fMRI Time Series Via a Temporal Transformer Diffusion Model for Major Depressive Disorder Diagnosis
Muhammad Asif Hasan, Yanming Zhu, Xuefei Yin +1
Diagnosing Major Depressive Disorder (MDD) from functional magnetic resonance imaging (fMRI) using functional connectivity (FC) analysis requires large amounts of labeled data that…
RT-NeRV: Rethinking Hybrid Neural Representations for Video via Residual Tokenization
Yunjie Xu, Xiang Feng, Chengkai Wang +3
Neural Representations for Videos(NeRV) have emerged as a promising paradigm for video compression by representing videos as compact neural networks with efficient decoding. Hybrid…
Neuroscience-inspired Staged Representation Learning with Disentangled Coarse- and Fine-Grained Semantics for EEG Visual Decoding
Xiang Gao, Hui Tian, Yanming Zhu +2
Decoding visual information from electroencephalography (EEG) signals remains a fundamental challenge in brain-computer interfaces and medical rehabilitation. Existing EEG visual d…
Causal-Audit: Explicit and Auditable Graph-based Reasoning via Target-Aware Causal Chain Construction
Su Lan, Xuefei Yin, Yanming Zhu +1
Causal and intervention-based question answering is fundamental to advancing large language models (LLMs) toward reasoning beyond surface-level correlations and understanding under…