12 papers
Skill-RM: Unifying Heterogeneous Evaluation Criteria via Agent Skill
Tao Chen, Gangwei Jiang, Pengyu Cheng +10
Reward models (RMs) provide critical feedback signals for LLM post-training, notably in reinforced fine-tuning (RFT) and reinforcement learning (RL) pipelines. However, current rew…
ContextRL: Enhancing MLLM's Knowledge Discovery Efficiency with Context-Augmented RL
Xingyu Lu, Jinpeng Wang, YiFan Zhang +12
We propose ContextRL, a novel framework that leverages context augmentation to overcome these bottlenecks. Specifically, to enhance Identifiability, we provide the reward model wit…
UniRef-Image-Edit: Towards Scalable and Consistent Multi-Reference Image Editing
Hongyang Wei, Bin Wen, Yancheng Long +22
We present UniRef-Image-Edit, a high-performance multi-modal generation system that unifies single-image editing and multi-image composition within a single framework. Existing dif…
VideoTemp-o3: Harmonizing Temporal Grounding and Video Understanding in Agentic Thinking-with-Videos
Wenqi Liu, Yunxiao Wang, Shijie Ma +14
In long-video understanding, conventional uniform frame sampling often fails to capture key visual evidence, leading to degraded performance and increased hallucinations. To addres…
Joint Reward Modeling: Internalizing Chain-of-Thought for Efficient Visual Reward Models
Yankai Yang, Yancheng Long, Hongyang Wei +12
Reward models are critical for reinforcement learning from human feedback, as they determine the alignment quality and reliability of generative models. For complex tasks such as i…
SpatialReward: Bridging the Perception Gap in Online RL for Image Editing via Explicit Spatial Reasoning
Yancheng Long, Yankai Yang, Hongyang Wei +12
Online Reinforcement Learning (RL) offers a promising avenue for complex image editing but is currently constrained by the scarcity of reliable and fine-grained reward signals. Exi…
Kwai Keye-VL 1.5 Technical Report
Biao Yang, Bin Wen, Boyang Ding +58
In recent years, the development of Large Language Models (LLMs) has significantly advanced, extending their capabilities to multimodal tasks through Multimodal Large Language Mode…
Thyme: Think Beyond Images
Yi-Fan Zhang, Xingyu Lu, Shukang Yin +17
Following OpenAI's introduction of the ``thinking with images'' concept, recent efforts have explored stimulating the use of visual information in the reasoning process to enhance…
A Navigation Framework Utilizing Vision-Language Models
Yicheng Duan, Kaiyu tang
Vision-and-Language Navigation (VLN) presents a complex challenge in embodied AI, requiring agents to interpret natural language instructions and navigate through visually rich, un…
R1-Reward: Training Multimodal Reward Model Through Stable Reinforcement Learning
Yi-Fan Zhang, Xingyu Lu, Xiao Hu +13
Multimodal Reward Models (MRMs) play a crucial role in enhancing the performance of Multimodal Large Language Models (MLLMs). While recent advancements have primarily focused on im…
VLM as Policy: Common-Law Content Moderation Framework for Short Video Platform
Xingyu Lu, Tianke Zhang, Chang Meng +14
Exponentially growing short video platforms (SVPs) face significant challenges in moderating content detrimental to users' mental health, particularly for minors. The dissemination…
Kwai-STaR: Transform LLMs into State-Transition Reasoners
Xingyu Lu, Yuhang Hu, Changyi Liu +12
Mathematical reasoning presents a significant challenge to the cognitive capabilities of LLMs. Various methods have been proposed to enhance the mathematical ability of LLMs. Howev…