Author name cluster

Yang Sun

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8 papers

2 author rows

EAAI Journal 2026 Journal Article

Irrelevance discriminative network for enhancing cross-center generalization in medical imaging segmentation

Yibin Lin
Dongming Li
Xiao Chen
Wude He
Qi Guan
Danru Chen
Anguo Zhang
Xiaorong Yan

Cross-center generalization in medical image segmentation (MIS) is a significant challenge due to the variability introduced by different imaging devices, operator techniques, and patient populations. In this paper, we propose the deep learning based Irrelevance Discriminative Network (ID-Net) method, which enhances cross-center generalization in MIS. We incorporate multiple auxiliary domain datasets (ADDs) from various centers alongside a single or limited number of target domain datasets. By training on the ADDs, the Irrelevance Discriminative (ID) module is capable of discriminating the latent representation of input images into common features, domain-specific features, and disturbance/noise. This allows for the fusion of common features with domain-specific features from the target domain dataset while discarding irrelevant noise, thereby significantly improving the cross-center generalization ability in the target domain tasks. Our approach effectively mitigates the domain shift problem and enhances the robustness and adaptability of MIS models across different centers.

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IS Journal 2025 Journal Article

Benchmarking Explainable Argumentation Dialogue via Freeman’s Theory

Yang Sun
Geng Tu
Wenpeng Lu
Min Yang
Erik Cambria
Ruifeng Xu

Argumentative dialogue involves structured exchanges of claims and supporting evidence, yet progress in building effective dialogue systems is limited by the scarcity of high-quality datasets. To address this, we introduce CMV-AD, a baseline dataset derived from the ChangeMyView corpus, designed for modeling structured argumentative interactions. We further propose FTCoT, a Freeman’s Theory-based Chain-of-Thought framework that enhances interpretability and reasoning in dialogue generation. FTCoT represents each dialogue turn with a structured quadruple: Dialogue Summary, User Argument, Assistant Argument, and Response Reasoning. We construct FTCoT using large language models (LLMs), leveraging their capabilities in reasoning and data annotation. Extensive automatic and human evaluations demonstrate the effectiveness of FTCoT in improving both the interpretability and quality of generated responses.

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AAAI Conference 2025 Conference Paper

Complex-Cycle-Consistent Diffusion Model for Monaural Speech Enhancement

Yi Li
Yang Sun
Plamen P Angelov

In this paper, we present a novel diffusion model-based monaural speech enhancement method. Our approach incorporates the separate estimation of speech spectra's magnitude and phase in two diffusion networks. Throughout the diffusion process, noise clips from real-world noise interferences are added gradually to the clean speech spectra and a noise-aware reverse process is proposed to learn how to generate both clean speech spectra and noise spectra. Furthermore, to fully leverage the intrinsic relationship between magnitude and phase, we introduce a complex-cycle-consistent (CCC) mechanism that uses the estimated magnitude to map the phase, and vice versa. We implement this algorithm within a phase-aware speech enhancement diffusion model (SEDM). We conduct extensive experiments on public datasets to demonstrate the effectiveness of our method, highlighting the significant benefits of exploiting the intrinsic relationship between phase and magnitude information to enhance speech. The comparison to conventional diffusion models demonstrates the superiority of SEDM.

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IROS Conference 2025 Conference Paper

DPGP: A Hybrid 2D-3D Dual Path Potential Ghost Probe Zone Prediction Framework for Safe Autonomous Driving

Weiming Qu
Jiawei Du
Shenghai Yuan 0001
Jia Wang
Yang Sun
Shengyi Liu
Yuanhao Zhu
Jiayi Rao

Modern robots must coexist with humans in dense urban environments. A key challenge is the ghost probe problem, where pedestrians or objects unexpectedly rush into traffic paths. This issue affects both autonomous vehicles and human drivers. Existing works propose vehicle-to-everything (V2X) strategies and non-line-of-sight (NLOS) imaging for ghost probe zone detection. However, most require high computational power or specialized hardware, limiting real-world feasibility. Additionally, many methods do not explicitly address this issue. To tackle this, we propose DPGP, a hybrid 2D-3D fusion framework for ghost probe zone prediction using only a monocular camera during training and inference. With unsupervised depth prediction, we observe ghost probe zones align with depth discontinuities, but different depth representations offer varying robustness. To exploit this, we fuse multiple feature embeddings to improve prediction. To validate our approach, we created a 12K-image dataset annotated with ghost probe zones, carefully sourced and cross-checked for accuracy. Experimental results show our framework outperforms existing methods while remaining cost-effective. To our knowledge, this is the first work extending ghost probe zone prediction beyond vehicles, addressing diverse non-vehicle objects. We will open-source our code and dataset for community benefit.

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AAAI Conference 2024 Conference Paper

OVD-Explorer: Optimism Should Not Be the Sole Pursuit of Exploration in Noisy Environments

Jinyi Liu
Zhi Wang
Yan Zheng
Jianye Hao
Chenjia Bai
Junjie Ye
Zhen Wang
Haiyin Piao

In reinforcement learning, the optimism in the face of uncertainty (OFU) is a mainstream principle for directing exploration towards less explored areas, characterized by higher uncertainty. However, in the presence of environmental stochasticity (noise), purely optimistic exploration may lead to excessive probing of high-noise areas, consequently impeding exploration efficiency. Hence, in exploring noisy environments, while optimism-driven exploration serves as a foundation, prudent attention to alleviating unnecessary over-exploration in high-noise areas becomes beneficial. In this work, we propose Optimistic Value Distribution Explorer (OVD-Explorer) to achieve a noise-aware optimistic exploration for continuous control. OVD-Explorer proposes a new measurement of the policy's exploration ability considering noise in optimistic perspectives, and leverages gradient ascent to drive exploration. Practically, OVD-Explorer can be easily integrated with continuous control RL algorithms. Extensive evaluations on the MuJoCo and GridChaos tasks demonstrate the superiority of OVD-Explorer in achieving noise-aware optimistic exploration.

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YNIMG Journal 2024 Journal Article

Visual selective attention in individuals with age-related hearing loss

Min Zhu
Yufei Qiao
Wen Sun
Yang Sun
Yuanshun Long
Hua Guo
Chang Cai
Hang Shen

Evidence from epidemiological studies suggests that hearing loss is associated with an accelerated decline in cognitive function, but the underlying pathophysiological mechanism remains poorly understood. Studies using auditory tasks have suggested that degraded auditory input increases the cognitive load for auditory perceptual processing and thereby reduces the resources available for other cognitive tasks. Attention-related networks are among the systems overrecruited to support degraded auditory perception, but it is unclear how they function when no excessive recruitment of cognitive resources for auditory processing is needed. Here, we implemented an EEG study using a nonauditory visual attentional selection task in 30 individuals with age-related hearing loss (ARHLs, 60-73 years) and compared them with aged (N = 30, 60-70 years) and young (N = 35, 22-29 years) normal-hearing controls. Compared with their normal-hearing peers, ARHLs demonstrated a significant amplitude reduction for the posterior contralateral N2 component, which is a well-validated index of the allocation of selective visual attention, despite the comparable behavioral performance. Furthermore, the amplitudes were observed to correlate significantly with hearing acuities (pure tone audiometry thresholds) and higher-order hearing abilities (speech-in-noise thresholds) in aged individuals. The target-elicited alpha lateralization, another mechanism of visuospatial attention, demonstrated in control groups was not observed in ARHLs. Although behavioral performance is comparable, the significant decrease in N2pc amplitude in ARHLs provides neurophysiologic evidence that may suggest a visual attentional deficit in ARHLs even without extra-recruitment of cognitive resources by auditory processing. It supports the hypothesis that constant degraded auditory input in ARHLs has an adverse impact on the function of cognitive control systems, which is a possible mechanism mediating the relationship between hearing loss and cognitive decline.

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YNIMG Journal 2021 Journal Article

The divided brain: Functional brain asymmetry underlying self-construal

Gen Shi
Xuesong Li
Yifan Zhu
Ruihong Shang
Yang Sun
Hua Guo
Jie Sui

Self-construal (orientations of independence and interdependence) is a fundamental concept that guides human behaviour, and it is linked to a large number of brain regions. However, understanding the connectivity of these regions and the critical principles underlying these self-functions are lacking. Because brain activity linked to self-related processes are intrinsic, the resting-state method has received substantial attention. Here, we focused on resting-state functional connectivity matrices based on brain asymmetry as indexed by the differential partition of the connectivity located in mirrored positions of the two hemispheres, hemispheric specialization measured using the intra-hemispheric (left or right) connectivity, brain communication via inter-hemispheric interactions, and global connectivity as the sum of the two intra-hemispheric connectivity. Combining machine learning techniques with hypothesis-driven network mapping approaches, we demonstrated that orientations of independence and interdependence were best predicted by the asymmetric matrix compared to brain communication, hemispheric specialization, and global connectivity matrices. The network results revealed that there were distinct asymmetric connections between the default mode network, the salience network and the executive control network which characterise independence and interdependence. These analyses shed light on the importance of brain asymmetry in understanding how complex self-functions are optimally represented in the brain networks.

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YNIMG Journal 2019 Journal Article

Downward cross-modal plasticity in single-sided deafness

Yufei Qiao
Xuesong Li
Hang Shen
Xue Zhang
Yang Sun
Wenyang Hao
Bingya Guo
Daofeng Ni

The auditory cortex has been shown to participate in visual processing in individuals with complete auditory deprivation. However, it remains unclear whether partial hearing deprivation like single-sided deafness (SSD) leads to similar cross-modal plasticity. To investigate this, we enrolled individuals with long-term SSD, into functional MRI scans under resting-state and a visuo-spatial working memory task. Contrary to previous findings in bilateral deafness, our study revealed decreased activation in the auditory cortex in both left (LSSD) and right (RSSD) single-sided deafness compared to normal hearing controls, with statistical significance in RSSD. The degree of involvement was correlated with residual hearing ability in RSSD. These observations suggest that SSD can lead to a downward cross-modal plasticity: the more hearing ability lost, the fewer brain resources in the auditory cortex can be applied to visual tasks. In addition, the fronto-parietal cortex was observed to be less activated during the visual task in RSSD while the resting-state fMRI revealed increased functional connectivity between the fronto-parietal cortex and the auditory cortex, suggesting fronto-parietal resources may be recruited less by vision but more by hearing. The LSSD showed a similar alteration trend with RSSD, but without statistical significance. Together these findings may indicate that when hearing is partially deprived in SSD, there may be redistribution for brain resources between hearing and vision, and vision tends to allocate less resources. Our findings in this pilot study of unilateral auditory-deprived individuals enrich the understanding of cross-modal plasticity in the brain.

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