9 papers
When Does Visual Generation Help Visual Understanding in Unified Multimodal Models?
Yubo Zhu, Zhehan Kan, Jingyi Yang +6
Unified multimodal models (UMMs) can perform both understanding and generation, raising a central question: can visual generation improve understanding? Existing evaluations provid…
Mitigating Database Leakage in RAG Systems with Keyword-Grounded Fact Substitution
Ziliang Zhang, Yubo Zhu, Wei Tong +4
Retrieval-Augmented Generation (RAG) has emerged as a powerful paradigm for combining large language models (LLMs) with external knowledge sources. However, RAG systems remain vuln…
PURPOSE: Poisoning Conflict Resolution in RAG via Proxy-Fact-Grounded Updates
Zijian Wang, Yubo Zhu, Muzhi Dong +7
In Retrieval-Augmented Generation (RAG), post-retrieval conflict resolution arbitrates among noisy or contradictory retrieved passages. However, the robustness of this safeguard ag…
Youtu-VL: Unleashing Visual Potential via Unified Vision-Language Supervision
Zhixiang Wei, Yi Li, Zhehan Kan +38
Despite the significant advancements represented by Vision-Language Models (VLMs), current architectures often exhibit limitations in retaining fine-grained visual information, lea…
The LLM Already Knows: Estimating LLM-Perceived Question Difficulty via Hidden Representations
Yubo Zhu, Dongrui Liu, Zecheng Lin +3
Estimating the difficulty of input questions as perceived by large language models (LLMs) is essential for accurate performance evaluation and adaptive inference. Existing methods…
SafeWork-R1: Coevolving Safety and Intelligence under the AI-45 Law
Shanghai AI Lab, :, Yicheng Bao +115
We introduce SafeWork-R1, a cutting-edge multimodal reasoning model that demonstrates the coevolution of capabilities and safety. It is developed by our proposed SafeLadder framewo…
Video Summarization using Denoising Diffusion Probabilistic Model
Zirui Shang, Yubo Zhu, Hongxi Li +2
Video summarization aims to eliminate visual redundancy while retaining key parts of video to construct concise and comprehensive synopses. Most existing methods use discriminative…
Detecting Dataset Abuse in Fine-Tuning Stable Diffusion Models for Text-to-Image Synthesis
Songrui Wang, Yubo Zhu, Wei Tong +1
Text-to-image synthesis has become highly popular for generating realistic and stylized images, often requiring fine-tuning generative models with domain-specific datasets for spec…
Extensible Multi-Granularity Fusion Network and Transferable Curriculum Learning for Aspect-based Sentiment Analysis
Xinran Li, Xiaowei Zhao, Yubo Zhu +8
Aspect-based Sentiment Analysis (ABSA) aims to determine sentiment polarity toward specific aspects in text. Existing methods enrich semantic and syntactic representations through…