collaborators

6 papers

cs.CV2026

URMF: Uncertainty-aware Robust Multimodal Fusion for Multimodal Sarcasm Detection

Zhenyu Wang, Weichen Cheng, Weijia Li +3

Multimodal sarcasm detection (MSD) aims to identify sarcastic intent from semantic incongruity between text and image. Although recent methods have improved MSD through cross-modal…

cs.CV2026

Earth-Agent: Unlocking the Full Landscape of Earth Observation with Agents

Peilin Feng, Zhutao Lv, Junyan Ye +8

Earth observation (EO) is essential for understanding the evolving states of the Earth system. Although recent MLLMs have advanced EO research, they still lack the capability to ta…

cs.CV2026

OmniEarth-Bench: Towards Holistic Evaluation of Earth's Six Spheres and Cross-Spheres Interactions with Multimodal Observational Earth Data

Fengxiang Wang, Mingshuo Chen, Xuming He +15

Existing benchmarks for multimodal learning in Earth science offer limited, siloed coverage of Earth's spheres and their cross-sphere interactions, typically restricting evaluation…

cs.CV2025

RealGen: Photorealistic Text-to-Image Generation via Detector-Guided Rewards

Junyan Ye, Leiqi Zhu, Yuncheng Guo +7

With the continuous advancement of image generation technology, advanced models such as GPT-Image-1 and Qwen-Image have achieved remarkable text-to-image consistency and world know…

cs.CV2025

Echo-4o: Harnessing the Power of GPT-4o Synthetic Images for Improved Image Generation

Junyan Ye, Dongzhi Jiang, Zihao Wang +9

Recently, GPT-4o has garnered significant attention for its strong performance in image generation, yet open-source models still lag behind. Several studies have explored distillin…

cs.CV2025

LAD-Reasoner: Tiny Multimodal Models are Good Reasoners for Logical Anomaly Detection

Weijia Li, Guanglei Chu, Jiong Chen +3

Recent advances in industrial anomaly detection have highlighted the need for deeper logical anomaly analysis, where unexpected relationships among objects, counts, and spatial con…