19 papers
BluePixel: Toward Native 4K Agentic Image Editing
Shanyan Guan, Shiyu Li, Xin Li +17
Instruction-driven image editing has reached native 4K, yet how such editors are trained remains undisclosed, and pretraining one from scratch is beyond most teams. The task itself…
DEdit: Iterative Draft Editing for Speculative Decoding
Longxuan Yu, Bingsen Chen, Peng Shi +9
Speculative decoding accelerates autoregressive LLMs by having a lightweight drafter propose tokens that the target model verifies in parallel. Diffusion-based drafters further red…
LEGO-Anything: Coding Agents for 3D Scene Reconstruction
Xirui Li, Peng Shi, Mingwen Dong +7
A 3D scene reconstructed from a single image is most useful when represented not as a rendering or a fixed 3D output, but as an explicit scene program whose execution yields a scen…
Video-MOPD: Multi-Teacher On-Policy Distillation for Video Understanding
Zhenxin Qin, Peng Shi, Cong Han +3
Video understanding demands a convergence of complementary capabilities across perception, temporal understanding, and complex reasoning, which are difficult to jointly optimize wi…
How Can Rhetoric Reward-Hack AI Reviewers? Dissecting Rhetorical Sensitivity in AI-Based Peer Review
Ming Li, Chenguang Wang, Xirui Li +5
As large language models increasingly participate in scientific evaluation, we investigate a potential form of reward hacking: how rhetorical choices shape AI-review judgments when…
Vorch-Omni: Multi-Task Orchestration of Sight and Sound
Vorch Team, Xiaoyu Chen, Yang Ding +25
Recent advances in generative video modeling have enabled diverse generation, reference-based synthesis, extension, and editing, but existing approaches often rely on fragmented ta…
Guava: Distilling Frontier VLMs into a Compact Agent through a Robotic Manipulation Harness
Haowen Liu, Xirui Li, Shaoxiong Yao +5
Language models trained on large-scale vision-language data have demonstrated strong potential for embodied agents. Harnessing models through embodied tools use offers a promising…
Beyond NL2Code: A Structured Survey of Multimodal Code Intelligence
Xuanle Zhao, Qiushi Sun, Jingyu Xiao +16
While Large Language Models (LLMs) have substantially advanced text-to-code generation, many real programming tasks specify intent through visual artifacts such as screenshots, cha…
Adaptive Latent Agentic Reasoning
Dongwon Jung, Peng Shi, Yi Zhang +2
Large reasoning models improve performance by generating extended chain-of-thought (CoT) reasoning, but this behavior becomes inefficient when applied to LLM agents. Current LLM ag…
TreeCUA: Efficiently Scaling GUI Automation with Tree-Structured Verifiable Evolution
Deyang Jiang, Jing Huang, Xuanle Zhao +6
Effectively scaling GUI automation is essential for computer-use agents (CUAs); however, existing work primarily focuses on scaling GUI grounding rather than the more crucial GUI p…
Length-Unbiased Sequence Policy Optimization: Revealing and Controlling Response Length Variation in RLVR
Fanfan Liu, Youyang Yin, Peng Shi +3
Recent applications of Reinforcement Learning with Verifiable Rewards (RLVR) to Large Language Models (LLMs) and Vision-Language Models (VLMs) have demonstrated significant success…
Flexible Entropy Control in RLVR with a Gradient-Preserving Perspective
Kun Chen, Peng Shi, Fanfan Liu +4
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a critical method for enhancing the reasoning capabilities of Large Language Models (LLMs). However, continuous…
MobileDreamer: Generative Sketch World Model for GUI Agent
Yilin Cao, Yufeng Zhong, Zhixiong Zeng +6
Mobile GUI agents have shown strong potential in real-world automation and practical applications. However, most existing agents remain reactive, making decisions mainly from curre…
Learning When to Look: A Disentangled Curriculum for Strategic Perception in Multimodal Reasoning
Siqi Yang, Zilve Gao, Haibo Qiu +5
Multimodal Large Language Models (MLLMs) demonstrate significant potential but remain brittle in complex, long-chain visual reasoning tasks. A critical failure mode is "visual forg…
Reading or Reasoning? Format Decoupled Reinforcement Learning for Document OCR
Yufeng Zhong, Lei Chen, Zhixiong Zeng +8
Reading text from images or scanned documents via OCR models has been a longstanding focus of researchers. Intuitively, text reading is perceived as a straightforward perceptual ta…
Metis-HOME: Hybrid Optimized Mixture-of-Experts for Multimodal Reasoning
Xiaohan Lan, Fanfan Liu, Haibo Qiu +4
Inspired by recent advancements in LLM reasoning, the field of multimodal reasoning has seen remarkable progress, achieving significant performance gains on intricate tasks such as…
Perceptual-Evidence Anchored Reinforced Learning for Multimodal Reasoning
Chi Zhang, Haibo Qiu, Qiming Zhang +6
Reinforcement Learning with Verifiable Rewards (RLVR) has significantly advanced the reasoning capabilities of Large Language Models (LLMs) and is now being applied to Vision-Langu…
Metis-SPECS: Decoupling Multimodal Learning via Self-distilled Preference-based Cold Start
Kun Chen, Peng Shi, Haibo Qiu +4
Reinforcement learning (RL) with verifiable rewards has recently catalyzed a wave of "MLLM-r1" approaches that bring RL to vision language models. Most representative paradigms beg…
Metis-RISE: RL Incentivizes and SFT Enhances Multimodal Reasoning Model Learning
Haibo Qiu, Xiaohan Lan, Fanfan Liu +4
Recent advancements in large language models (LLMs) have witnessed a surge in the development of advanced reasoning paradigms, which are now being integrated into multimodal large…