7 papers
TOBench: A Task-Oriented Omni-Modal Benchmark for Real-World Tool-Using Agents
Zhiqiang Liu, Wenhui Dong, Yilang Tan +3
Tool-using agents are increasingly expected to operate across realistic professional workflows, where they must interpret multimodal inputs, coordinate external tools, inspect inte…
NGM: A Plug-and-Play Training-Free Memory Module for LLMs
Yuwen Qu, Wenhui Dong, Chenyang Si +1
Recent studies introduce conditional memory modules that decouple knowledge storage from neural computation, enabling more direct knowledge access. Compared to MoE, which relies on…
Ivy-Fake: A Unified Explainable Framework and Benchmark for Image and Video AIGC Detection
Changjiang Jiang, Wenhui Dong, Zhonghao Zhang +8
The rapid development of Artificial Intelligence Generated Content (AIGC) techniques has enabled the creation of high-quality synthetic content, but it also raises significant secu…
SpineBench: A Clinically Salient, Level-Aware Benchmark Powered by the SpineMed-450k Corpus
Ming Zhao, Wenhui Dong, Yang Zhang +23
Spine disorders affect 619 million people globally and are a leading cause of disability, yet AI-assisted diagnosis remains limited by the lack of level-aware, multimodal datasets.…
Small-Large Collaboration: Training-efficient Concept Personalization for Large VLM using a Meta Personalized Small VLM
Sihan Yang, Huitong Ji, Shaolin Lu +6
Personalizing Vision-Language Models (VLMs) to transform them into daily assistants has emerged as a trending research direction. However, leading companies like OpenAI continue to…
FILA: Fine-Grained Vision Language Models
Shiding Zhu, Wenhui Dong, Jun Song +3
Recently, there has been growing interest in the capability of multimodal large language models (MLLMs) to process high-resolution images. A common approach currently involves dyna…