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Daeun Lee, Jaeah Lee, Woosung Kim +2 authors
A rest-state framework reconstructs articulated objects from a single closed configuration by fusing vision-language outputs into consistent part meshes and validating synthesized motion hypotheses via geometric consistency.
Zhiwei Li, Yong Hu
SkillHone enables continuous evolution of agent skills by maintaining persistent decision histories and incorporating practice feedback for improved performance across research and tool-mediated analysis tasks.
Qifeng Zhang, Kaixiang Huang, Heng Dong +6 authors
The study introduces a video benchmark requiring global spatial reasoning across long videos and reveals that vision-language models struggle to build consistent global scene representations despite strong local perception.
Chin-Yang Lin, Yang-Che Sun, Cheng Sun +5 authors
Scal3R improves long-video online 3D reconstruction by querying multi-reference relative poses with lightweight tokens and pose-graph optimization, reducing drift without retraining the backbone.
Junyao Yang, Yucheng Shi, Zhongzhi Li +4 authors
T1 is a 122B Mixture-of-Experts model trained with reinforcement learning to execute long-horizon terminal tasks in a cloud sandbox, achieving state-of-the-art results through stable actor-critic optimization and out-of-distribution training.
Kangning Zhang, Yixing Li, Shuai Shao +9 authors
Visual Attribution Distillation uses counterfactual reconstruction to isolate visually supported corrections from mixed teacher signals, improving multimodal on-policy distillation.
Xiaoyang Han, Jianhua Li, Kewang Deng +14 authors
A unified multimodal model formulates computer vision tasks as generation problems using natural language and visual prompts, achieving performance comparable to specialized systems across diverse vision tasks.
Zelin Fu, Bin Tan, Changjiang Sun +6 authors
Boundary modeling enables dense spatial perception by learning sub-pixel representations that enhance depth estimation and support embodied AI applications.
Zelin Gao, Qiuyu Wang, Jiapeng Zhu +17 authors
An advanced world modeling system with extended interaction capabilities, real-time processing, diverse interactive elements, and multi-agent behavior control for collaborative virtual environments.
Junghwan Lim, Joon Son Chung, Sungmin Lee +24 authors
Motif 3 is a large sparse mixture-of-experts language model using grouped differential latent attention and specialized training techniques to achieve strong reasoning, coding, and long-context performance.
Zishan Xu, Zhiyuan Yao, Yuxin Chen +9 authors
EnvACE trains large language model agents via internal world rehearsal instead of external environments, improving long-horizon tool use through joint optimization of action and simulated response.
Zhuoran Zhao, Shengju Qian, Tongtong Liang +7 authors
Mask Forcing mitigates mode collapse in distilled autoregressive video diffusion by injecting masked cleaner signals during self-rollout, improving visual quality without extra training data.
Junyan Ye, Wei Liu, Dongzhi Jiang +9 authors
A coding agent guided by a vision-language model generates editable layered designs by synthesizing isolated visual assets and iteratively refining native HTML/CSS layouts.
Yana Wei, Hongbo Peng, Yanlin Lai +14 authors
PerceptionRubrics presents a rubric-based evaluation framework that identifies gaps between benchmark scores and real-world performance through atomic auditing and gated scoring mechanisms.
Kejian Zhu, Zhuoran Jin, Dongqi Huang +4 authors
Effective multimodal agent training is improved by selecting diverse environments via ability-aware selection and structuring difficulty through hierarchical curriculum learning.
Young-Jun Lee, Seungone Kim, Minki Kang +5 authors
Evolutionary fine-tuning enables large language models to develop cross-task problem-solving capabilities by learning from search trajectories, demonstrating improved performance on mathematical conjectures and optimization tasks.
Xingjian Ran, Xiaoye Mo, Sihao Liu +3 authors
SceneMosaic combines learned image priors with vision-language agents to efficiently generate diverse, physically valid indoor scenes by evolving local units and composing them globally.
Yuhan Wang, Zhengxi Lu, Yuchen Yan +6 authors
PaperGym converts scientific papers into training environments by separating research questions from evaluation rubrics, enabling reinforcement learning that improves research planning across multiple model sizes.
Javier del Pino, Salvador Rodríguez, Alejandro Garabito +2 authors
ENEAS unifies text-prompted instance tracking and open-concept semantic discovery via temporal memory extension and a verification layer that filters visual distractors.
Yijie Jin, Jiajun Xu, Yuxuan Liu +8 authors
Multi-Block Diffusion Language Models extend single-block diffusion to concurrent block decoding with improved training strategies and optimized decoding algorithms.
Yushi Sun, Yanjie Zhang, Rui Sheng
Over-inference of unsupported user attributes is pervasive across personalized LLMs, with self-reported confidence inversely correlating with actual fabrication rates, underscoring the need for external verification.
Zelong Sun, Jun Wang, Kaicheng Yang +3 authors
UniME-R1 improves multimodal retrieval by generating retrieval-centric reasoning guided by initial candidate feedback rather than query-only explanations.
Donghyun Lee, Jitesh Chavan, Duy Nguyen +5 authors
OrbitQuant enables efficient post-training quantization for diffusion transformers by using a normalized rotated basis that eliminates the need for recalibration across different timesteps and modalities.
Jiajun Shi, Siyuan Tao, Yuhao Wu +18 authors
S³Gym evaluates whether large language model agents can self-test, self-judge, and self-improve through interaction experience across text-based games, revealing that effective self-improvement depends on task structure and experience representation.
Chengqian Ma, Wei Tao, Haoyu Zhang +1 authors
Motion-Omni is an end-to-end framework that jointly generates spoken dialogue and full-body co-speech motion from shared hidden states, using scalable pseudo-labeling and a unified evaluation protocol to achieve real-time, aligned responses.
Soslan Kabisov, Gennadiy Savrasov, Maksim Elistratov +9 authors
CADENA reconstructs 3D meshes into parametric CAD programs step-by-step with intermediate geometry checks and introduces a benchmark for mechanical part reverse engineering.
Yifan Shen, Jian Xu, Boyi Li +6 authors
ChronoVision improves visual temporal reasoning by aligning latent imagery with logic through reconstructive prediction, ROI attention, and reinforcement learning, achieving strong results on video reasoning benchmarks.
Zican Hu, Xuyang Hu, Yiming Liu +10 authors
BRAID framework enables unified multi-modal reasoning by casting text-image interaction as a Markov decision process, allowing joint optimization through reinforcement learning with vision-language model guidance.
Chunji Lv, Yangguang Wei, Junlin Liu +6 authors
Persistent Consistency Self-Distillation improves reinforcement learning for language model agents by weighting token-level teacher guidance according to sustained local support, yielding stronger results on interactive tasks.
Zilong Chen, Chaorui Deng, Kunchang Li +2 authors
Structured language in prompts drives diffusion loss scaling, enabling improved visual generation through annotated prompts and a trained prompter.
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