10 papers
CanvasAgent: Enabling Complex Image Creation and Editing via Visual Tool Orchestration
Hairui Zhu, Yiying Yang, Tengjin Weng +5
Complex image creation and editing often require more than a single generation or editing model. A user request may involve synthesizing images, localizing objects, segmenting regi…
EmoTrans: A Benchmark for Understanding, Reasoning, and Predicting Emotion Transitions in Multimodal LLMs
He Hu, Tengjin Weng, Zebang Cheng +5
Recent multimodal large language models (MLLMs) have shown strong capabilities in perception, reasoning, and generation, and are increasingly used in applications such as social ro…
GRPO-VPS: Enhancing Group Relative Policy Optimization with Verifiable Process Supervision for Effective Reasoning
Jingyi Wang, Lei Zhu, Tengjin Weng +8
Reinforcement Learning with Verifiable Rewards (RLVR) has advanced the reasoning capabilities of Large Language Models (LLMs) by leveraging direct outcome verification instead of l…
OddGridBench: Exposing the Lack of Fine-Grained Visual Discrepancy Sensitivity in Multimodal Large Language Models
Tengjin Weng, Wenhao Jiang, Jingyi Wang +3
Multimodal large language models (MLLMs) have achieved remarkable performance across a wide range of vision language tasks. However, their ability in low-level visual perception, p…
BEAP-Agent: Backtrackable Execution and Adaptive Planning for GUI Agents
Ziyu Lu, Tengjin Weng, Yiying Yang +3
GUI agents are designed to automate repetitive tasks and enhance productivity. However, existing GUI agents struggle to recover once they follow an incorrect exploration path, ofte…
LlamaSeg: Image Segmentation via Autoregressive Mask Generation
Jiru Deng, Tengjin Weng, Tianyu Yang +3
We present \textbf{LlamaSeg}, a visual autoregressive framework that unifies multiple image segmentation tasks via natural language instructions. By reformulating segmentation as v…
VisNumBench: Evaluating Number Sense of Multimodal Large Language Models
Tengjin Weng, Jingyi Wang, Wenhao Jiang +1
Can Multimodal Large Language Models (MLLMs) develop an intuitive number sense similar to humans? Targeting this problem, we introduce Visual Number Benchmark (VisNumBench) to eval…
PMP-Swin: Multi-Scale Patch Message Passing Swin Transformer for Retinal Disease Classification
Zhihan Yang, Zhiming Cheng, Tengjin Weng +4
Retinal disease is one of the primary causes of visual impairment, and early diagnosis is essential for preventing further deterioration. Nowadays, many works have explored Transfo…
MSE-Nets: Multi-annotated Semi-supervised Ensemble Networks for Improving Segmentation of Medical Image with Ambiguous Boundaries
Shuai Wang, Tengjin Weng, Jingyi Wang +6
Medical image segmentation annotations exhibit variations among experts due to the ambiguous boundaries of segmented objects and backgrounds in medical images. Although using multi…
Accurate Segmentation of Optic Disc And Cup from Multiple Pseudo-labels by Noise-aware Learning
Tengjin Weng, Yang Shen, Zhidong Zhao +2
Optic disc and cup segmentation plays a crucial role in automating the screening and diagnosis of optic glaucoma. While data-driven convolutional neural networks (CNNs) show promis…