10 papers
Valley3: Scaling Omni Foundation Models for E-commerce
Zeyu Chen, Guanghao Zhou, Qixiang Yin +6
In this work, we present Valley3, an omni multimodal large language model (MLLM) developed for diverse global e-commerce tasks, with unified understanding and reasoning capabilitie…
Beyond the Last Frame: Process-aware Evaluation for Generative Video Reasoning
Yifan Li, Yukai Gu, Yingqian Min +6
Recent breakthroughs in video generation have demonstrated an emerging capability termed Chain-of-Frames (CoF) reasoning, where models resolve complex tasks through the generation…
MERIT: Multilingual Semantic Retrieval with Interleaved Multi-Condition Query
Wei Chow, Yuan Gao, Linfeng Li +15
Semantic retrieval is crucial for modern applications yet remains underexplored in current research. Existing datasets are limited to single languages, single images, or singular r…
Unleashing Perception-Time Scaling to Multimodal Reasoning Models
Yifan Li, Zhenghao Chen, Ziheng Wu +7
Recent advances in inference-time scaling, particularly those leveraging reinforcement learning with verifiable rewards, have substantially enhanced the reasoning capabilities of L…
Seeing is Believing? Mitigating OCR Hallucinations in Multimodal Large Language Models
Zhentao He, Can Zhang, Ziheng Wu +6
Recent advancements in multimodal large language models have enhanced document understanding by integrating textual and visual information. However, existing models exhibit incompl…
VFaith: Do Large Multimodal Models Really Reason on Seen Images Rather than Previous Memories?
Jiachen Yu, Yufei Zhan, Ziheng Wu +3
Recent extensive works have demonstrated that by introducing long CoT, the capabilities of MLLMs to solve complex problems can be effectively enhanced. However, the reasons for the…