1 citations · 1 across the 27 of their papers we have counts for
28 papers
KwaiMind Technical Report
Junlong Wu, Zijun Li, Yuting Hu +14
Commercial image editing requires product identity preservation, accurate text rendering, and user appeal alongside general editing quality. We present KwaiMind, an image editing s…
Joint Alignment and Distillation for Video Generation via Sample-Guided Distribution Matching
Jiuzhou Lin, Junlong Wu, Fei Zuo +11
Aligning video generative models to human preferences heavily relies on Reinforcement Learning (RL), which suffers from extensive computational overhead. Existing workflows typical…
Step Back to Move Forward: Reflection-Aware Preference Optimization for Visual Generation
Junlong Wu, Jiuzhou Lin, Jia Sun +7
Diffusion models have become the mainstream paradigm for modern visual generation and have substantially advanced multimedia content synthesis, especially in text-to-image and text…
TextRefine: Improving Textual Fidelity, Spatial Placement, and Glyph Rendering for Text Editing in Product Posters
Honglie Wang, Jia Sun, Zijun Li +11
Text editing in product posters entails inserting new text or replacing existing text while preserving product appearance, background content, and global composition. Despite recen…
DetailAnywhere: Fashion Detail Generation via Cross-Modal Feature Alignment Distillation
Zijun Li, Yimin Zhou, Jia Sun +12
Diffusion-based generative AI has achieved remarkable success in e-commerce applications such as virtual try-on, poster generation, and product background synthesis. However, when…
DELTAVID: Enhancing Fine-Grained Spatiotemporal Perception with Cross-Video Differences
Yankai Yang, Yancheng Long, Bin Wen +4
Video multimodal large language models have made strong progress on open-ended video understanding, but they still lack precise local spatiotemporal perception. When two videos sha…
SpatialFlow-GRPO: Where Spatial Credit Drives Image Editing
Yankai Yang, Yancheng Long, Wei Chen +7
Recent online reinforcement learning has substantially improved image editing quality. However, existing Flow-GRPO-style methods usually rely on a single whole-image reward, which…
OneReason Technical Report
OneRec Team, Biao Yang, Boyang Ding +81
Generative recommendation models in the OneRec family have been widely deployed in many real-world services, such as short-video, live-streaming, advertising, and e-commerce. Howev…
CaC: Advancing Video Reward Models via Hierarchical Spatiotemporal Concentrating
Jiyuan Wang, Huan Ouyang, Jiuzhou Lin +15
In this paper, we propose Concentrate and Concentrate (CaC), a coarse-to-fine anomaly reward model based on Vision-Language Models. During inference, it first conducts a global tem…
When Reasoning Traces Become Performative: Step-Level Evidence that Chain-of-Thought Is an Imperfect Oversight Channel
Wenkai Li, Fan Yang, Ananya Hazarika +2
Chain-of-thought (CoT) traces are increasingly used both to improve language model capability and to audit model behavior, implicitly assuming that the visible trace remains synchr…
A Single Layer to Explain Them All:Understanding Massive Activations in Large Language Models
Zeru Shi, Zhenting Wang, Fan Yang +2
We investigate the origins of massive activations in large language models (LLMs) and identify a specific layer named the \textbf{Massive Emergence Layer (ME Layer)}, that is consi…
Spatial Chain-of-Thought: Bridging Understanding and Generation Models for Spatial Reasoning Generation
Wei Chen, Yancheng Long, Mingqiao Liu +9
While diffusion models have shown exceptional capabilities in aesthetic image synthesis, they often struggle with complex spatial understanding and reasoning. Existing approaches r…
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…
KEPO: Knowledge-Enhanced Preference Optimization for Multimodal Reasoning with Applications to Medical VQA
Fan Yang, Rui Meng, Trudi Di Qi +2
Reinforcement learning (RL) has emerged as a promising paradigm for inducing explicit reasoning behaviors in large language and vision-language models. However, reasoning-oriented…
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…
InstructEngine: Instruction-driven Text-to-Image Alignment
Xingyu Lu, Yuhang Hu, YiFan Zhang +9
Reinforcement Learning from Human/AI Feedback (RLHF/RLAIF) has been extensively utilized for preference alignment of text-to-image models. Existing methods face certain limitations…
Decoupling Contrastive Decoding: Robust Hallucination Mitigation in Multimodal Large Language Models
Wei Chen, Xin Yan, Bin Wen +4
Although multimodal large language models (MLLMs) exhibit remarkable reasoning capabilities on complex multimodal understanding tasks, they still suffer from the notorious hallucin…
TIME: Temporal-Sensitive Multi-Dimensional Instruction Tuning and Robust Benchmarking for Video-LLMs
Yunxiao Wang, Meng Liu, Wenqi Liu +7
Video large language models have achieved remarkable performance in tasks such as video question answering, however, their temporal understanding remains suboptimal. To address thi…
Exo2Ego: Exocentric Knowledge Guided MLLM for Egocentric Video Understanding
Haoyu Zhang, Qiaohui Chu, Meng Liu +3
AI personal assistants, deployed through robots or wearables, require embodied understanding to collaborate effectively with humans. However, current Multimodal Large Language Mode…
iMOVE: Instance-Motion-Aware Video Understanding
Jiaze Li, Yaya Shi, Zongyang Ma +7
Enhancing the fine-grained instance spatiotemporal motion perception capabilities of Video Large Language Models is crucial for improving their temporal and general video understan…
MM-RLHF: The Next Step Forward in Multimodal LLM Alignment
Yi-Fan Zhang, Tao Yu, Haochen Tian +17
Despite notable advancements in Multimodal Large Language Models (MLLMs), most state-of-the-art models have not undergone thorough alignment with human preferences. This gap exists…
TaskGalaxy: Scaling Multi-modal Instruction Fine-tuning with Tens of Thousands Vision Task Types
Jiankang Chen, Tianke Zhang, Changyi Liu +8
Multimodal visual language models are gaining prominence in open-world applications, driven by advancements in model architectures, training techniques, and high-quality data. Howe…