17 citations · 29 across the 14 of their papers we have counts for
17 papers
A reduced model for neoclassical transport in non-axisymmetric magnetic configurations
Y. Ban, X. Garbet, R. Varennes +6
A unified framework is proposed to compute a neoclassical equilibrium for tokamaks with non-axisymmetric magnetic perturbations, based on a Hamiltonian description combined with a…
MMAgent-R: Learning to Rerank and Reject for Agentic mRAG
Tao Zhang, Ziqi Zhang, Zongyang Ma +7
Knowledge-based Visual Question Answering (KB-VQA) requires models to retrieve visual entities matching the query image from large-scale encyclopedic knowledge bases and answer rel…
How Far Is Document Parsing from Solved? PureDocBench: A Source-Traceable Benchmark across Clean, Degraded, and Real-World Settings
Zhiheng Li, Zongyang Ma, Jiaxian Chen +12
Document parsing models are improving rapidly, but existing benchmarks are still insufficient for a comprehensive evaluation of their capabilities. We introduce PureDocBench, a ben…
Making MLLMs Blind: Adversarial Smuggling Attacks in MLLM Content Moderation
Zhiheng Li, Zongyang Ma, Yuntong Pan +8
Multimodal Large Language Models (MLLMs) are increasingly being deployed as automated content moderators. Within this landscape, we uncover a critical threat: Adversarial Smuggling…
Beyond Semantic Search: Towards Referential Anchoring in Composed Image Retrieval
Yuxin Yang, Yinan Zhou, Yuxin Chen +6
Composed Image Retrieval (CIR) has demonstrated significant potential by enabling flexible multimodal queries that combine a reference image and modification text. However, CIR inh…
MMhops-R1: Multimodal Multi-hop Reasoning
Tao Zhang, Ziqi Zhang, Zongyang Ma +7
The ability to perform multi-modal multi-hop reasoning by iteratively integrating information across various modalities and external knowledge is critical for addressing complex re…
UniPixel: Unified Object Referring and Segmentation for Pixel-Level Visual Reasoning
Ye Liu, Zongyang Ma, Junfu Pu +4
Recent advances in Large Multi-modal Models (LMMs) have demonstrated their remarkable success as general-purpose multi-modal assistants, with particular focuses on holistic image-…
TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos
Fanheng Kong, Jingyuan Zhang, Hongzhi Zhang +7
Videos are unique in their integration of temporal elements, including camera, scene, action, and attribute, along with their dynamic relationships over time. However, existing ben…
DetailFusion: A Dual-branch Framework with Detail Enhancement for Composed Image Retrieval
Yuxin Yang, Yinan Zhou, Yuxin Chen +8
Composed Image Retrieval (CIR) aims to retrieve target images from a gallery based on a reference image and modification text as a combined query. Recent approaches focus on balanc…
STAR-R1: Spatial TrAnsformation Reasoning by Reinforcing Multimodal LLMs
Zongzhao Li, Zongyang Ma, Mingze Li +6
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities across diverse tasks, yet they lag significantly behind humans in spatial reasoning. We investiga…
iMOVE: Instance-Motion-Aware Video Understanding
Jiaze Li, Yaya Shi, Zongyang Ma +7
Enhancing the fine-grained instance spatiotemporal motion perception capabilities of Video Large Language Models is crucial for improving their temporal and general video understan…
mRAG: Multimodal Retrieval-Reflection-Augmented Generation for Knowledge-Based VQA
Tao Zhang, Ziqi Zhang, Zongyang Ma +10
Advanced Multimodal Large Language Models (MLLMs) struggle with recent Knowledge-based Visual Question Answering (VQA) tasks, such as INFOSEEK and Encyclopedic-VQA, due to their li…
E.T. Bench: Towards Open-Ended Event-Level Video-Language Understanding
Ye Liu, Zongyang Ma, Zhongang Qi +3
Recent advances in Video Large Language Models (Video-LLMs) have demonstrated their great potential in general-purpose video understanding. To verify the significance of these mode…
How to Make Cross Encoder a Good Teacher for Efficient Image-Text Retrieval?
Yuxin Chen, Zongyang Ma, Ziqi Zhang +7
Dominant dual-encoder models enable efficient image-text retrieval but suffer from limited accuracy while the cross-encoder models offer higher accuracy at the expense of efficienc…
EA-VTR: Event-Aware Video-Text Retrieval
Zongyang Ma, Ziqi Zhang, Yuxin Chen +8
Understanding the content of events occurring in the video and their inherent temporal logic is crucial for video-text retrieval. However, web-crawled pre-training datasets often l…
Large Language Models Meet Text-Centric Multimodal Sentiment Analysis: A Survey
Hao Yang, Yanyan Zhao, Yang Wu +6
Compared to traditional sentiment analysis, which only considers text, multimodal sentiment analysis needs to consider emotional signals from multimodal sources simultaneously and…
Open-Vocabulary One-Stage Detection with Hierarchical Visual-Language Knowledge Distillation
Zongyang Ma, Guan Luo, Jin Gao +5
Open-vocabulary object detection aims to detect novel object categories beyond the training set. The advanced open-vocabulary two-stage detectors employ instance-level visual-to-vi…