7 citations · 28 across the 34 of their papers we have counts for
40 papers
Omni-IO Skills: Harnessing Your Agent Omni-Native
Yanlin Li, Mingyang Hao, Shengqiong Wu +3
General-purpose agents can plan, reason, and act over long horizons, yet their production capabilities remain fragmented across text, images, audio, video, documents, 3D assets, an…
AI for Games in the Foundation Model Era
Meng Luo, Yanlin Li, Hao Li +7
Foundation models, alongside advances in learned game-world models, are reshaping AI across the game lifecycle. Beyond playing games, recent systems model players and game dynamics…
UrbanGround: From Local Perception to Spatial Agency in a Real-Scale City
Tianjie Ju, Zheng Wu, Yueqing Sun +15
Multimodal large language models (MLLMs) can interpret a street view, but reliable urban action depends on whether such local evidence remains useful after the agent starts to move…
OmniScientist: An Omni-Modal Omni-Discipline AI Scientist
Bobo Li, Hao Fei, Tianjie Ju +2
Recent advances in foundation models have enabled AI scientists to automate increasingly complete research workflows, from hypothesis generation and code execution to manuscript pr…
MoCA: Implicit Social Context Analysis
Wenhao Xu, Kaiwen Zhang, Hao Li +10
Human social communication, such as affection and intent, is often conveyed in highly implicit ways, where underlying meanings are expressed through indirect, socially and cultural…
EmAvatar: Multimodal Empathetic Response Generation via Conflict Resolution and Expressive Guidance
Xiaolin Chen, Xuemeng Song, Jinlan Fu +3
Avatar-based multimodal empathetic response generation has emerged as a pivotal capability in human-centric systems, aiming to recognize user emotions and synthesize responses with…
ArtECulture: Benchmarking Culture-Conditioned Visual Emotion Understanding in Multimodal Large Language Models
Xiaolin Chen, Xuemeng Song, Wenhao Shi +3
Existing visual emotion understanding methods typically ignore cultural variations in emotional perception. We introduce culture-conditioned visual emotion understanding, a task th…
From Profiling to Synthesis: Benchmarking Implicit Behavioral Alignment in Personalized LLM Agents
Jiajia Song, Bobo Li, Haiwen Yi +6
Large Language Models have enabled increasingly capable autonomous agents, yet personalization remains critical for making such agents practically useful. Recent benchmarks have be…
HoloGeo: Mitigating Landmark Bias in Geo-localization via Evidence-Driven Reasoning
Pengcheng Zhou, Xuanyu Liu, Yanchen Yin +4
Recent advances in Vision-Language Models (VLMs) have significantly improved image geo-localization, yet existing models remain susceptible to landmark bias, causing them to overlo…
Taming Actor-Observer Asymmetry in Agents via Dialectical Alignment
Bobo Li, Rui Wu, Zibo Ji +5
Large Language Model agents have rapidly evolved from static text generators into dynamic systems capable of executing complex autonomous workflows. To enhance reliability, multi-a…
SCP: Spatial Causal Prediction in Video
Yanguang Zhao, Jie Yang, Shengqiong Wu +9
Spatial reasoning, the ability to understand spatial relations, causality, and dynamic evolution, is central to human intelligence and essential for real-world applications such as…
Orthogonal Spatial-temporal Distributional Transfer for 4D Generation
Wei Liu, Shengqiong Wu, Bobo Li +4
In the AIGC era, generating high-quality 4D content has garnered increasing research attention. Unfortunately, current 4D synthesis research is severely constrained by the lack of…
UniM: A Unified Any-to-Any Interleaved Multimodal Benchmark
Yanlin Li, Minghui Guo, Kaiwen Zhang +13
In real-world multimodal applications, systems usually need to comprehend arbitrarily combined and interleaved multimodal inputs from users, while also generating outputs in any in…
Asking the Right Questions: Ontology-Grounded Interpretable Embeddings for Biomedical Text
Yixuan Tang, Zhenghong Lin, Yandong Sun +3
While dense biomedical embeddings achieve strong performance, their opaque dimensions limit transparency in biomedical NLP. Recent question-based interpretable embeddings represent…
Unveiling the Cognitive Compass: Theory-of-Mind-Guided Multimodal Emotion Reasoning
Meng Luo, Bobo Li, Shanqing Xu +8
Despite rapid progress in multimodal large language models (MLLMs), their capability for deep emotional understanding remains limited. We argue that genuine affective intelligence…
Althea: The Fact-Checking--Metalearning Tradeoff in AI-Assisted Verification
Svetlana Churina, Kokil Jaidka, Anab Maulana Barik +5
Fact-checking systems must be scalable and epistemically trustworthy. We introduce Althea, a retrieval-augmented system for user-driven claim evaluation that matches standard pipel…
LogicReward: Incentivizing LLM Reasoning via Step-Wise Logical Supervision
Jundong Xu, Hao Fei, Huichi Zhou +6
Although LLMs exhibit strong reasoning capabilities, existing training methods largely depend on outcome-based feedback, which can produce correct answers with flawed reasoning. Pr…
Multi-Part Object Representations via Graph Structures and Co-Part Discovery
Alex Foo, Wynne Hsu, Mong Li Lee
Discovering object-centric representations from images can significantly enhance the robustness, sample efficiency and generalizability of vision models. Works on images with multi…
Multi-Modal Continual Learning via Cross-Modality Adapters and Representation Alignment with Knowledge Preservation
Evelyn Chee, Wynne Hsu, Mong Li Lee
Continual learning is essential for adapting models to new tasks while retaining previously acquired knowledge. While existing approaches predominantly focus on uni-modal data, mul…
TRUST-VL: An Explainable News Assistant for General Multimodal Misinformation Detection
Zehong Yan, Peng Qi, Wynne Hsu +1
Multimodal misinformation, encompassing textual, visual, and cross-modal distortions, poses an increasing societal threat that is amplified by generative AI. Existing methods typic…
Test-Time Adaptation by Causal Trimming
Yingnan Liu, Rui Qiao, Mong Li Lee +1
Test-time adaptation aims to improve model robustness under distribution shifts by adapting models with access to unlabeled target samples. A primary cause of performance degradati…
LEAF-Mamba: Local Emphatic and Adaptive Fusion State Space Model for RGB-D Salient Object Detection
Lanhu Wu, Zilin Gao, Hao Fei +2
RGB-D salient object detection (SOD) aims to identify the most conspicuous objects in a scene with the incorporation of depth cues. Existing methods mainly rely on CNNs, limited by…
Dr.V: A Hierarchical Perception-Temporal-Cognition Framework to Diagnose Video Hallucination by Fine-grained Spatial-Temporal Grounding
Meng Luo, Shengqiong Wu, Liqiang Jing +12
Recent advancements in large video models (LVMs) have significantly enhance video understanding. However, these models continue to suffer from hallucinations, producing content tha…
MuSLR: Multimodal Symbolic Logical Reasoning
Jundong Xu, Hao Fei, Yuhui Zhang +8
Multimodal symbolic logical reasoning, which aims to deduce new facts from multimodal input via formal logic, is critical in high-stakes applications such as autonomous driving and…