1 citations · 1 across the 11 of their papers we have counts for
11 papers
Inter-Residue Geometry Attention for Antibody-Specific Epitope Prediction
Chuanliu Fan, Nan Yu, Junjie Wu +1
Antibody-specific epitope prediction aims to identify which antigen residues are recognized by a given antibody, a task that depends on the three-dimensional complementarity betwee…
Multi-Task Reinforcement Learning for Enhanced Multimodal LLM-as-a-Judge
Junjie Wu, Xuan Kan, Zihao He +3
Multimodal Large Language Models (MLLMs) have been widely adopted as MLLM-as-a-Judges due to their strong alignment with human judgment across various visual tasks. However, most e…
Bi-Level Prompt Optimization for Multimodal LLM-as-a-Judge
Bo Pan, Xuan Kan, Kaitai Zhang +6
Large language models (LLMs) have become widely adopted as automated judges for evaluating AI-generated content. Despite their success, aligning LLM-based evaluations with human ju…
Mirage: Transmitting a Video as a Perceptual Illusion for 50,000X Speedup
Junjie Wu, Tianrui Li, Yi Zhang +1
The existing communication framework mainly aims at accurate reconstruction of source signals to ensure reliable transmission. However, this signal-level fidelity-oriented design o…
DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories
Chenlong Deng, Mengjie Deng, Junjie Wu +10
Existing multimodal retrieval systems excel at semantic matching but implicitly assume that query-image relevance can be measured in isolation. This paradigm overlooks the rich dep…
OSCAR: Optimization-Steered Agentic Planning for Composed Image Retrieval
Teng Wang, Rong Shan, Jianghao Lin +8
Composed image retrieval (CIR) requires complex reasoning over heterogeneous visual and textual constraints. Existing approaches largely fall into two paradigms: unified embedding…
Mindscape-Aware Retrieval Augmented Generation for Improved Long Context Understanding
Yuqing Li, Jiangnan Li, Zheng Lin +5
Humans understand long and complex texts by relying on a holistic semantic representation of the content. This global view helps organize prior knowledge, interpret new information…
HiEAG: Evidence-Augmented Generation for Out-of-Context Misinformation Detection
Junjie Wu, Yumeng Fu, Nan Yu +1
Recent advancements in multimodal out-of-context (OOC) misinformation detection have made remarkable progress in checking the consistencies between different modalities for support…
Insight-A: Attribution-aware for Multimodal Misinformation Detection
Junjie Wu, Yumeng Fu, Chen Gong +1
AI-generated content (AIGC) technology has emerged as a prevalent alternative to create multimodal misinformation on social media platforms, posing unprecedented threats to societa…
MMD-Thinker: Adaptive Multi-Dimensional Thinking for Multimodal Misinformation Detection
Junjie Wu, Guohong Fu
Multimodal misinformation floods on various social media, and continues to evolve in the era of AI-generated content (AIGC). The emerged misinformation with low creation cost and h…
E2LVLM:Evidence-Enhanced Large Vision-Language Model for Multimodal Out-of-Context Misinformation Detection
Junjie Wu, Yumeng Fu, Nan Yu +1
Recent studies in Large Vision-Language Models (LVLMs) have demonstrated impressive advancements in multimodal Out-of-Context (OOC) misinformation detection, discerning whether an…