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Kai-Tuo Feng

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Preprint Aug 2026

AVCap: Reinforcing Audio-Video Joint Caption with Detail-Aware Reward

Detailed audio-video joint captioning is essential for multimodal video understanding and generation. However, prior works are constrained by three main limitations: (1) the scarcity of high-quality public datasets with fine-grained audio-visual joint captions; (2) reinforcement-learning methods that rely on coarse rew...

Ming-Yang Wu, Kai-Tuo Feng, Bohao Li et al. · 0 citations
Preprint Sep 2026

VideoGen-Agent: Reinforcing Video Generation Agents

Recent advances in video generative models have enabled high-fidelity, temporally coherent video generation. However, these models often struggle to satisfy prompts requiring specialized knowledge, specific identities, physical consistency, or ordered events. In this paper, we present VideoGen-Agent, a multimodal agent...

Bin-Xu Li, Hao-Yi Duan, Yu-Hui Zhang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

EviRover: Reinforcing Agentic Perception Beyond a Glance

Visual perception is conventionally formulated as a one-shot prediction from a single glance at the image, under the assumption that the image content and the model's parametric knowledge suffice to resolve the query. This assumption often fails in real-world scenarios that hinge on fine-grained visual details or requi...

Kai-Xuan Fan, Kai-Tuo Feng, Tian-Shuo Peng et al. · 0 citations
#machine learning Preprint Sep 2026

Stable-MM-R1: Anchoring Multimodal Reasoning Dynamics via Entropy-Guided Stratification

This work presents Hybrid Stratified Replay (HSR), a novel mechanism that restructures batches by stratifying rollouts based on Path Entropy, a rollout-level confidence proxy, and outcome reward, offering a principled solution for stable and efficient RL fine-tuning.

Yi-Meng Ye, Shuang Chen, Wen-Xuan Huang et al. · 0 citations
Jul 2026

JarvisHub: An Open Harness for Canvas-Native Multimodal Creative Agents

JarvisHub is introduced, a canvas-native creative agent harness for long-horizon multimodal creation, where agents can progressively plan, generate, revise, and organize multimodal projects while users remain able to inspect, guide, and intervene throughout the process.

Yunlong Lin, Zixu Lin, Zhaohu Xing et al. · 1 citation

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