1 citations · 1 across the 18 of their papers we have counts for
20 papers
When Non-Adversarial Noise Hurts Learning: Benchmarking Skill Self-Evolution in Agents
Tao Yu, Zhongtian Luo, Yuchen Long +19
Large language model agents increasingly improve by distilling experience into reusable skills, but errors in that experience can persist in learned rules and affect later tasks. E…
OPIS: An Input-Grounded Benchmark for Multi-Object Memory in Video World Models
Hao Wang, Tao Yu, Liuzhou Zhang +13
Video world models must preserve the visual state of the world over time, but existing evaluation protocols often rely on generated histories, video reference, or selected revisit…
SCOPE-Router: Cost-Aware Open-Set VLM Routing for Execution-Oriented Tasks
Tao Yu, Yifei Qu, Zhiqing Cui +14
Model routing aims to select the most suitable model from a candidate pool for each query, balancing quality and cost. Existing VLM routing research is limited to traditional VQA e…
When Seeing Is Not Believing -- A Benchmark for Search-Grounded Video Misinformation Detection
Tao Yu, Yujia Yang, Shenghua Chai +18
Video misinformation increasingly operates at the semantic and evidential level: authentic footage may be selectively edited, temporally reordered, spliced across sources, or augme…
Omni-DeepSearch: A Benchmark for Audio-Driven Omni-Modal Deep Search
Tao Yu, yiming ding, Shenghua Chai +16
Current omni-modal benchmarks mainly evaluate models under settings where multiple modalities are provided simultaneously, while the ability to start from audio alone and actively…
Beyond the All-in-One Agent: Benchmarking Role-Specialized Multi-Agent Collaboration in Enterprise Workflows
Tao Yu, Hao Wang, Changyu Li +15
Large language model (LLM) agents are increasingly expected to operate in enterprise environments, where work is distributed across specialized roles, permission-controlled systems…
HIMMEL: Hierarchical Interleaved Multi-stream Motion Encoding for Long Video Understanding
Haopeng Jin, Hongzhu Yi, Wenlong Zhao +9
Long video understanding with multimodal language models suffers from three compounding bottlenecks: heavy decode cost to obtain dense RGB frames, token growth with frame count, an…
Omni IIE Bench: Benchmarking the Practical Capabilities of Image Editing Models
Yujia Yang, Yuanxiang Wang, Zhenyu Guan +11
While Instruction-based Image Editing (IIE) has achieved significant progress, existing benchmarks pursue task breadth via mixed evaluations. This paradigm obscures a critical fail…
Towards Principled Dataset Distillation: A Spectral Distribution Perspective
Ruixi Wu, Shaobo Wang, Jiahuan Chen +9
Dataset distillation (DD) aims to compress large-scale datasets into compact synthetic counterparts for efficient model training. However, existing DD methods exhibit substantial p…
ShotFinder: Imagination-Driven Open-Domain Video Shot Retrieval via Web Search
Tao Yu, Haopeng Jin, Hao Wang +19
In recent years, large language models (LLMs) have made rapid progress in information retrieval, yet existing research has mainly focused on text or static multimodal settings. Ope…
PaperX: A Unified Framework for Multimodal Academic Presentation Generation with Scholar DAG
Tao Yu, Minghui Zhang, Zhiqing Cui +17
Transforming scientific papers into multimodal presentation content is essential for research dissemination but remains labor intensive. Existing automated solutions typically trea…
Beyond Closed-Pool Video Retrieval: A Benchmark and Agent Framework for Real-World Video Search and Moment Localization
Tao Yu, Yujia Yang, Haopeng Jin +17
Traditional video retrieval benchmarks focus on matching precise descriptions to closed video pools, failing to reflect real-world searches characterized by fuzzy, multi-dimensiona…
VDE Bench: Evaluating The Capability of Image Editing Models to Modify Visual Documents
Hongzhu Yi, Yujia Yang, Yuanxiang Wang +18
Image editing models can modify visual content through natural language, but editing dense documents requires precise local changes amid tightly coupled text, tables, and layout. W…
Dynamic Deep Graph Learning for Incomplete Multi-View Clustering with Masked Graph Reconstruction Loss
Zhenghao Zhang, Jun Xie, Xingchen Chen +11
The prevalence of real-world multi-view data makes incomplete multi-view clustering (IMVC) a crucial research. The rapid development of Graph Neural Networks (GNNs) has established…
BrowserAgent: Building Web Agents with Human-Inspired Web Browsing Actions
Tao Yu, Zhengbo Zhang, Zhiheng Lyu +8
Efficiently solving real-world problems with LLMs increasingly hinges on their ability to interact with dynamic web environments and autonomously acquire external information. Whil…
MR-Align: Meta-Reasoning Informed Factuality Alignment for Large Reasoning Models
Xinming Wang, Jian Xu, Bin Yu +9
Large reasoning models (LRMs) show strong capabilities in complex reasoning, yet their marginal gains on evidence-dependent factual questions are limited. We find this limitation i…
More Is Better: A MoE-Based Emotion Recognition Framework with Human Preference Alignment
Jun Xie, Yingjian Zhu, Feng Chen +9
In this paper, we present our solution for the semi-supervised learning track (MER-SEMI) in MER2025. We propose a comprehensive framework, grounded in the principle that "more is b…
Multimodal Video Emotion Recognition with Reliable Reasoning Priors
Zhepeng Wang, Yingjian Zhu, Guanghao Dong +4
This study investigates the integration of trustworthy prior reasoning knowledge from MLLMs into multimodal emotion recognition. We employ Gemini to generate fine-grained, modality…
Team of One: Cracking Complex Video QA with Model Synergy
Jun Xie, Zhaoran Zhao, Xiongjun Guan +5
We propose a novel framework for open-ended video question answering that enhances reasoning depth and robustness in complex real-world scenarios, as benchmarked on the CVRR-ES dat…
Four Eyes Are Better Than Two: Harnessing the Collaborative Potential of Large Models via Differentiated Thinking and Complementary Ensembles
Jun Xie, Xiongjun Guan, Yingjian Zhu +5
In this paper, we present the runner-up solution for the Ego4D EgoSchema Challenge at CVPR 2025 (Confirmed on May 20, 2025). Inspired by the success of large models, we evaluate an…