15 citations · 28 across the 27 of their papers we have counts for
14 papers · 1 filter
CoANeRV: Coordinate-Aware Token-Space Neural Video Representation
Jialong Guo, Ke Liu, Mengxuan Li +2
Neural representations for videos (NeRV) have shown strong reconstruction fidelity by storing video-specific information in network weights. However, existing formulations typicall…
CAER: Conflict-Aware Evidence Routing with Dual Prefix Experts for Multimodal Large Language Models
Zixuan Liu, Juntao Cai, Xiaoxu Cai +2
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in multimodal understanding and generation. However, when textual inputs conflict with visual evi…
DeepBD: A Grounded Agentic Workflow for Variant Prioritization and Diagnosis of Genetic Birth Defects
Shiyu Li, Ziqi Yan, Zhihao Wu +7
Birth defects are a major cause of fetal loss, neonatal morbidity and long-term disability. In the subset with suspected genetic etiologies, exome and genome sequencing have moved…
Morphology-Aware Multimodal Representation Learning for Insect Phylogenetic Reconstruction
Zixuan Liu, Kaijie Yu, Chun He +5
Morphological traits provide important evidence for phylogenetic reconstruction and evolutionary relationship analysis. Recent image-based approaches have introduced deep learning,…
Sparsity Curse: Understanding RLVR Model Parameter Space from Model Merging
Chenrui Wu, Zexi Li, Jiajun Bu +2
Reinforcement Learning with Verifiable Reward (RLVR) has emerged as a powerful post-training paradigm that surpasses Supervised Fine-Tuning (SFT) in eliciting reasoning intelligenc…
Medical world models: representing medical states, modelling clinical dynamics and guiding intervention policies
Ke Liu, Mengxuan Li, Yanyi Bao +4
Medical diagnosis and treatment are dynamic processes in which patient states evolve over time and clinical interventions alter future outcomes. Although current medical AI can det…
Beyond the Individual: Virtualizing Multi-Disciplinary Reasoning for Clinical Intake via Collaborative Agents
Huangwei Chen, Wu Li, Junhao Jia +7
The initial outpatient consultation is critical for clinical decision-making, yet it is often conducted by a single physician under time pressure, making it prone to cognitive bias…
Sci-Mind: Cognitively-Inspired Adversarial Debate for Autonomous Mathematical Modeling
Junhao Jia, Huangwei Chen, Ruiying Sun +4
Real-world mathematical modeling is inherently an experiential and collaborative endeavor. Domain experts rarely solve complex problems from scratch; instead, they draw upon analog…
Learning Image-Text Matching with Optimal Partial Transport
Zhengxin Pan, Haishuai Wang, Fangyu Wu +3
Cross-modal matching, a fundamental task in bridging vision and language, has recently garnered substantial research interest. Despite the development of numerous methods aimed at…
Bi-TEAM: A Unified Cross-Scale Representation Learning Framework for Chemically Modified Biomolecules
Chunbin Gu, Zijun Gao, Mutian He +8
Representation learning for protein biochemical space faces a difficult trade-off: protein language models excel at capturing long-range biological semantics but often miss fine-gr…
LLM-Bootstrapped Targeted Finding Guidance for Factual MLLM-based Medical Report Generation
Cunyuan Yang, Dejuan Song, Xiaotao Pang +7
The automatic generation of medical reports utilizing Multimodal Large Language Models (MLLMs) frequently encounters challenges related to factual instability, which may manifest a…
Unsupervised Causal Prototypical Networks for De-biased Interpretable Dermoscopy Diagnosis
Junhao Jia, Yueyi Wu, Huangwei Chen +4
Despite the success of deep learning in dermoscopy image analysis, its inherent black-box nature hinders clinical trust, motivating the use of prototypical networks for case-based…
Directed Ordinal Diffusion Regularization for Progression-Aware Diabetic Retinopathy Grading
Huangwei Chen, Junhao Jia, Ruocheng Li +7
Diabetic Retinopathy (DR) progresses as a continuous and irreversible deterioration of the retina, following a well-defined clinical trajectory from mild to severe stages. However,…
VasGuideNet: Vascular Topology-Guided Couinaud Liver Segmentation with Structural Contrastive Loss
Chaojie Shen, Jingjun Gu, Zihao Zhao +4
Accurate Couinaud liver segmentation is critical for preoperative surgical planning and tumor localization.However, existing methods primarily rely on image intensity and spatial l…