45 citations · 164 across the 56 of their papers we have counts for
64 papers
Long-to-Short Video Evidence Reasoning for Grounded Question Answering
Kaiyan Chen, Junbin Xiao, Xun Yang
We present LOVER, a \underline{L}ong to sh\underline{O}rt \underline{V}ideo \underline{E}vidence \underline{R}einforced model for grounded question answering (GQA). LOVER highlight…
MOJITO: Modal Joint Learning for Unified End-to-End Autonomous Driving
Zhijing Cheng, Xuancheng Zhang, Donglin Di +4
End-to-end autonomous driving systems commonly follow a cascaded two-stage pipeline where a perception stage compresses multi-modal sensor inputs into a compact context and a downs…
Omni-Perception Policy Optimization for Multimodal Emotion Reasoning
Zhiyuan Han, Beier Zhu, Wenwen Tong +6
We find that current emotion-oriented Omni-MLLMs still lack reliable omni-modal perception: they (i) underutilize multimodal cues in their reasoning trajectories and (ii) exhibit u…
TextGaze: Prompting Gaze Target Estimation with Textual Scene Cues
Junhui She, Fei Wang, Kun Li +4
Gaze target estimation aims to infer the position of a person's gaze within a scene. Within mainstream design logic, multi-branch methods require extra supervision and annotations,…
SafeGuard: A Multi-Agent Perception-Reasoning Framework for Social-Risk AI-Generated Video Detection
Wenlin Wu, Sheng Zhou, Peipei Song +3
As video generation paradigms evolve from localized manipulation to full-scene synthesis, AI-generated video detection becomes increasingly challenging, as forgeries exhibit cohere…
MER-R1: Multimodal Emotion Reasoning via Slow-Fast Thinking Synergy
Zhiyuan Han, Beier Zhu, Wenwen Tong +8
We find that explicit reasoning does not necessarily translate into better multimodal emotion recognition (MER) accuracy, even though it makes predictions more interpretable. Speci…
A New Multi-Domain Benchmark for Micro-Action Recognition and Detection
Yanbin Hao, Pengyu Liu, Xing Wei +3
Micro-actions are short-duration, low-amplitude subtle body movements at the whole-body level that can reveal latent intentions, involuntary reactions, and fine-grained affective c…
MuKV: Multi-Grained KV Cache Compression for Long Streaming Video Question-Answering
Junbin Xiao, Jiajun Chen, Tianxiang Sun +2
Long streaming video QA remains challenging due to growing visual tokens and limited reasoning length of large language models (LLMs). KV-caching stores the Key-Value (KV) of the h…
Memory-Augmented Query Intent Understanding for Efficient Chat-based Image Retrieval
Xianke Chen, Daizong Liu, Yushuo Lou +5
Different from traditional text-to-image retrieval tasks, chat-based image retrieval allows the human-interactive system to iteratively clarify and refine user intent through multi…
EverybodyDance: Bipartite Graph-Based Identity Correspondence for Multi-Character Animation
Haotian Ling, Zequn Chen, Qiuying Chen +6
Consistent pose-driven character animation has achieved remarkable progress in single-character scenarios. However, extending these advances to multi-character settings is non-triv…
Towards Seamless Interaction: Causal Turn-Level Modeling of Interactive 3D Conversational Head Dynamics
Junjie Chen, Fei Wang, Zhihao Huang +5
Human conversation involves continuous exchanges of speech and nonverbal cues such as head nods, gaze shifts, and facial expressions that convey attention and emotion. Modeling the…
AffordBot: 3D Fine-grained Embodied Reasoning via Multimodal Large Language Models
Xinyi Wang, Xun Yang, Yanlong Xu +3
Effective human-agent collaboration in physical environments requires understanding not only what to act upon, but also where the actionable elements are and how to interact with t…
Dual Learning with Dynamic Knowledge Distillation and Soft Alignment for Partially Relevant Video Retrieval
Jianfeng Dong, Lei Huang, Daizong Liu +5
Almost all previous text-to-video retrieval works ideally assume that videos are pre-trimmed with short durations containing solely text-related content. However, in practice, vide…
Enhancing Partially Relevant Video Retrieval with Robust Alignment Learning
Long Zhang, Peipei Song, Jianfeng Dong +2
Partially Relevant Video Retrieval (PRVR) aims to retrieve untrimmed videos partially relevant to a given query. The core challenge lies in learning robust query-video alignment ag…
MoCA: Identity-Preserving Text-to-Video Generation via Mixture of Cross Attention
Qi Xie, Yongjia Ma, Donglin Di +2
Achieving ID-preserving text-to-video (T2V) generation remains challenging despite recent advances in diffusion-based models. Existing approaches often fail to capture fine-grained…
Psyche-R1: Towards Reliable Psychological LLMs through Unified Empathy, Expertise, and Reasoning
Chongyuan Dai, Jinpeng Hu, Hongchang Shi +4
Amidst a shortage of qualified mental health professionals, the integration of large language models (LLMs) into psychological applications offers a promising way to alleviate the…
Video-EM: Event-Centric Episodic Memory for Long-Form Video Understanding
Yun Wang, Long Zhang, Jingren Liu +9
Video Large Language Models (Video-LLMs) have shown strong video understanding, yet their application to long-form videos remains constrained by limited context windows. A common w…
Audio Does Matter: Importance-Aware Multi-Granularity Fusion for Video Moment Retrieval
Junan Lin, Daizong Liu, Xianke Chen +5
Video Moment Retrieval (VMR) aims to retrieve a specific moment semantically related to the given query. To tackle this task, most existing VMR methods solely focus on the visual a…
Benchmarking and Bridging Emotion Conflicts for Multimodal Emotion Reasoning
Zhiyuan Han, Beier Zhu, Yanlong Xu +2
Despite their strong performance in multimodal emotion reasoning, existing Multimodal Large Language Models (MLLMs) often overlook the scenarios involving emotion conflicts, where…
QR-LoRA: Efficient and Disentangled Fine-tuning via QR Decomposition for Customized Generation
Jiahui Yang, Yongjia Ma, Donglin Di +6
Existing text-to-image models often rely on parameter fine-tuning techniques such as Low-Rank Adaptation (LoRA) to customize visual attributes. However, when combining multiple LoR…
MUPA: Towards Multi-Path Agentic Reasoning for Grounded Video Question Answering
Jisheng Dang, Huilin Song, Junbin Xiao +6
Grounded Video Question Answering (Grounded VideoQA) requires aligning textual answers with explicit visual evidence. However, modern multimodal models often rely on linguistic pri…
Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective
Ruixuan Zhang, He Wang, Zhengyu Zhao +4
Rapid advances in Artificial Intelligence Generated Images (AIGI) have facilitated malicious use, such as forgery and misinformation. Therefore, numerous methods have been proposed…
AlphaFuse: Learn ID Embeddings for Sequential Recommendation in Null Space of Language Embeddings
Guoqing Hu, An Zhang, Shuo Liu +3
Recent advancements in sequential recommendation have underscored the potential of Large Language Models (LLMs) for enhancing item embeddings. However, existing approaches face thr…
Structure-guided Diffusion Transformer for Low-Light Image Enhancement
Xiangchen Yin, Zhenda Yu, Longtao Jiang +4
While the diffusion transformer (DiT) has become a focal point of interest in recent years, its application in low-light image enhancement remains a blank area for exploration. Cur…