858 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Shanghai Artificial Intelligence LaboratoryCN102 papers
- University of Chinese Academy of SciencesCN77 papers
- Chinese Academy of SciencesCN73 papers
- Peking UniversityCN67 papers
- Tsinghua UniversityCN65 papers
- Institute of AutomationCN58 papers
- Shandong Institute of AutomationCN35 papers
- Shanghai Jiao Tong UniversityCN34 papers
- Beihang UniversityCN25 papers
- Fudan UniversityCN25 papers
- Center for Excellence in Brain Science and Intelligence TechnologyCN20 papers
- Chinese University of Hong KongHK19 papers
41 papers · 1 filter
A Data-Driven Multimodal Method for Early Detection of Coordinated Abnormal Behaviors in Live-Streaming Platforms
Jingwen Luo, Pinrui Zhu, Yiyan Wang +4
With the rapid growth of live-streaming e-commerce and digital marketing, abnormal marketing behaviors have become increasingly concealed and coordinated across heterogeneous modal…
IntentQA: Intent Question Answering in Videos by Cognitive Context Reasoning
Jiapeng Li, Ping Wei, Wenjuan Han +2
Video understanding requires intelligent agents to transcend mere recognition of visual facts and comprehend the underlying intents behind human actions (often termed the "dark mat…
Understanding Cognition-Induced Risks in Agentic AI Systems
Guanchu Wang, Qinuo Li, Mengnan Du +2
Frontier agentic systems powered by large language models (LLMs) exhibit human-like patterns of cognition. As these systems become deeply integrated across different domains, their…
Revisiting Shape and Texture Reliance with Category-Separability-Calibrated Suppression
Ning Jiang, Tianyi Luo, Zhengyong Huang +1
Feature-suppression evaluations infer model reliance on shape or texture from the accuracy loss caused by attenuating each type of information. Such losses, however, conflate featu…
Large Language Models in Mental Health: A Systematic Review of Applications, Innovations, and Ethical Challenges
Yisong Chen, Yifan Gao, Sijing Yu +2
We present a review on the applications of large language models (LLMs) in health, e.g., social media analysis, clinical conversational agents, therapy support tools, prompt engine…
Miles: Metric Learning with Expandable Subspace for Pre-Trained Model-Based Class-Incremental Learning
Kai Jiang, Zisong Lin, Hongyuan Zhang +2
Class Incremental Learning (CIL) aims to learn new concepts consistently from a data stream without forgetting. Unlike typical CIL methods which need to learn a model from scratch,…
LDFE: Laplacian Decoupled Feature Enhancement Block for Dual-Stream CNN-based RGB-IR Object Detection
Wenhao Dong, Xiaoyan Luo, Linlin Yang +4
The complementary information between RGB and IR images can significantly enhance object detection performance under extreme conditions. Existing methods prefer dual-stream CNN bac…
CausalMoE: A Billion-Scale Multimodal Foundation Model for Granger Causal Discovery with Pattern-Routed Heterogeneous Experts
Bo Liu, Di Dai, Jingwei Liu +5
Granger Causal Discovery (GCD) is fundamental for analyzing temporal dependencies in complex systems. However, existing neural GCD methods predominantly rely on a "one-size-fits-al…
A Distributed Multi-UGV Exploration Framework With Loop-Aware Planning and Descriptor-Aided Localization in Resource-Limited Environments
Zhiwei Li, Haiou Liu, Xijun Zhao +3
Robust and efficient cooperative exploration with multiple unmanned ground vehicles (UGVs) in unknown, GPSdenied, and bandwidth-limited environments without prior maps remains chal…
DBHN-Net: Dual-Branch Hybrid Neural Network For Low-Complexity Monaural Speech Enhancement
Cunhang Fan, Enrui Liu, Jing Zhou +6
Although artificial neural network (ANN) based speech enhancement (SE) methods demonstrate excellent performance, the high computational complexity and high energy consumption hind…
BotDirector: Robot Storytelling Across the Symmetrical Reality with Multi-modal Interactions
Zhe Sun, Meng Wang, Lei Wang +4
Robot storytelling offers a unique blend of technological innovation and creative expression that engages children in unprecedented ways. However, the technical aspects are often t…
MemNovo: Look Back at the Spectrum for Balanced De Novo Peptide Sequencing from Mass Spectrometry
Dongxin Lyu, Jingbo Zhou, Hongxin Xiang +2
De novo peptide sequencing from tandem mass spectrometry is pivotal in proteomics, enabling identification of novel peptides without reference databases. While recent Transformer-b…
TriDP-PTM: a three-stage distortion-perception tradeoff guides the pre-training model for radar cardiac sensing
Jinye Li, Aidong Men, Yang Liu +1
Cardiovascular diseases (CVDs) remain a leading cause of death globally, necessitating continuous, accurate non-invasive cardiac monitoring. While non-contact radar-based approache…
LABO: LLM-Accelerated Bayesian Optimization through Broad Exploration and Selective Experimentation
Zhuo Chen, Xinzhe Yuan, Jianshu Zhang +8
The high cost and data scarcity in scientific exploration have motivated the use of large language models (LLMs) as knowledge-driven components in Bayesian optimization (BO). Howev…
A Survey of Large Language Models for Perception and Measurement of Human Psychology
Yudong Li, Xiaoyi Chen, Jiawei Cai +4
Against the backdrop of the rapid advancement of Large Language Models (LLMs), their application in the field of psychology has garnered significant academic attention. A central i…
Toward Natural and Companionable Virtual Agents via Cross-Temporal Emotional Modeling
Feier Qin, Xiao Li, Yi Zheng +5
Recent advances in foundation models have enabled conversational agents that aim for sustained companionship rather than mere task completion. Yet most still remain unable to suppo…
SOM: Structured Opponent Modeling for LLM-based Agents via Structural Causal Model
Shiyue Cao, Pei Xu, Likun Yang +3
Accurately predicting opponents' behavior from interactions is a fundamental capability for large language model (LLM)-based agents in multi-agent and game-theoretic environments.…
Repeated Deceptive Path Planning against Learnable Observer
Shiyue Cao, Pei Xu, Likun Yang +6
We study the problem of deceptive path planning (DPP), where an agent aims to conceal its true destination from external observers. While existing work assumes static, non-learning…
Logic-Regularized Verifier Elicits Reasoning from LLMs
Xinyu Wang, Changzhi Sun, Lian Cheng +4
Verifiers are crucial components for enhancing modern LLMs' reasoning capability. Typicalverifiers require resource-intensive superviseddataset construction, which is costly and fa…
How Historians Use Visualization: A Corpus-Driven Mixed-Methods Study
Xinyue Chen, Yu Zhang, Weili Zheng +2
Visualization in historical research is shifting from isolated attempts to systematic practices. However, data-driven evidence about how historians actually use visualization remai…
UniVidX: A Unified Multimodal Framework for Versatile Video Generation via Diffusion Priors
Houyuan Chen, Hong Li, Xianghao Kong +8
Recent progress has shown that video diffusion models (VDMs) can be repurposed for diverse multimodal graphics tasks. However, existing methods often train separate models for each…
CasLayout: Cascaded 3D Layout Diffusion for Indoor Scene Synthesis with Implicit Relation Modeling
Yingrui Wu, Youkang Kong, Mingyang Zhao +3
Synthesizing realistic 3D indoor scenes remains challenging due to data scarcity and the difficulty of simultaneously enforcing global architectural constraints and local semantic…
Spatiotemporal Degradation-Aware 3D Gaussian Splatting for Realistic Underwater Scene Reconstruction
Shaohua Liu, Ning Gao, Zuoya Gu +3
Reconstructing realistic underwater scenes from underwater video remains a meaningful yet challenging task in the multimedia domain. The inherent spatiotemporal degradations in und…
VCE: A zero-cost hallucination mitigation method of LVLMs via visual contrastive editing
Yanbin Huang, Yisen Li, Guiyao Tie +6
Large vision-language models (LVLMs) frequently suffer from Object Hallucination (OH), wherein they generate descriptions containing objects that are not actually present in the in…