3 citations · 4 across the 17 of their papers we have counts for
19 papers
Schema-Anchored Latent Reasoning for Semantic Parsing-Based Knowledge Base Question Answering
Guangze Gao, Zixuan Li, Sikui Zhang +5
Semantic parsing (SP)-based knowledge base question answering aims to answer natural language questions by generating executable logical forms (LFs) over knowledge bases (KBs). Whe…
Gaussian Mixture Modeling for Event-Aware Visual Allocation in Long Video Understanding
Yifan Lu, Ziqi Zhang, Chunfeng Yuan +3
Large Vision-Language Models (LVLMs) face significant challenges in long video understanding due to the excessive computational cost and information loss associated with uniform sa…
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…
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…
Captioning Daily Activity Images in Early Childhood Education: Benchmark and Algorithm
Sixing Li, Zhibin Gu, Ziqi Zhang +4
Image captioning for Early Childhood Education (ECE) is essential for automated activity understanding and educational assessment. However, existing methods face two key challenges…
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…
Mitigating Hallucinations in Large Vision-Language Models by Self-Injecting Hallucinations
Yifan Lu, Ziqi Zhang, Chunfeng Yuan +5
Large Vision-Language Models (LVLMs) suffer from serious hallucination problems, where the model-generated responses are inconsistent with the visual inputs. Existing hallucination…
LaMPE: Length-aware Multi-grained Positional Encoding for Adaptive Long-context Scaling Without Training
Sikui Zhang, Guangze Gao, Ziyun Gan +5
Large language models (LLMs) experience significant performance degradation when the input exceeds the pretraining context window, primarily due to the out-of-distribution (OOD) be…
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…
NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment
Shuhao Han, Haotian Fan, Fangyuan Kong +112
This paper reports on the NTIRE 2025 challenge on Text to Image (T2I) generation model quality assessment, which will be held in conjunction with the New Trends in Image Restoratio…
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…
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…
MIBench: Evaluating Multimodal Large Language Models over Multiple Images
Haowei Liu, Xi Zhang, Haiyang Xu +8
Built on the power of LLMs, numerous multimodal large language models (MLLMs) have recently achieved remarkable performance on various vision-language tasks. However, most existing…
Semantics-enhanced Cross-modal Masked Image Modeling for Vision-Language Pre-training
Haowei Liu, Yaya Shi, Haiyang Xu +8
In vision-language pre-training (VLP), masked image modeling (MIM) has recently been introduced for fine-grained cross-modal alignment. However, in most existing methods, the recon…
Unifying Latent and Lexicon Representations for Effective Video-Text Retrieval
Haowei Liu, Yaya Shi, Haiyang Xu +8
In video-text retrieval, most existing methods adopt the dual-encoder architecture for fast retrieval, which employs two individual encoders to extract global latent representation…
NFT1000: A Cross-Modal Dataset for Non-Fungible Token Retrieval
Shuxun Wang, Yunfei Lei, Ziqi Zhang +6
With the rise of "Metaverse" and "Web 3.0", Non-Fungible Token (NFT) has emerged as a kind of pivotal digital asset, garnering significant attention. By the end of March 2024, more…
Set Prediction Guided by Semantic Concepts for Diverse Video Captioning
Yifan Lu, Ziqi Zhang, Chunfeng Yuan +4
Diverse video captioning aims to generate a set of sentences to describe the given video in various aspects. Mainstream methods are trained with independent pairs of a video and a…