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Chen Hu, Haikuo Du, Heng Wang +64 authors
Step-DeepResearch, an end-to-end agent enhanced with a data synthesis strategy and progressive training, achieves expert-level capabilities in deep research scenarios, outperforming established models.
Tiwei Bie, Maosong Cao, Kun Chen +28 authors
LLaDA2.0 converts auto-regressive models into discrete diffusion large language models with a novel training scheme, achieving superior performance and efficiency at scale.
Nex-AGI Team, Yuxuan Cai, Lu Chen +62 authors
The introduction of NexAU, NexA4A, and NexGAP enables the scaling of complexity, diversity, and fidelity in interactive environments for training large language models as autonomous agents, resulting in superior performance.
Tong Wu, Yang Liu, Jun Bai +6 authors
NPR, a teacher-free framework, enhances Large Language Models with native parallel reasoning capabilities through self-distilled training, Parallel-Aware Policy Optimization, and a robust NPR Engine, achieving substantial performance and speed improvements.
Zhiheng Liu, Weiming Ren, Haozhe Liu +22 authors
TUNA, a unified multimodal model, uses a cascaded VAE and representation encoder for end-to-end multimodal understanding and generation, outperforming decoupled models and achieving state-of-the-art results across various benchmarks.
Xiaopeng Lin, Shijie Lian, Bin Yu +8 authors
Proposed Egocentric2Embodiment pipeline translates human egocentric videos into structured training data for robots, enhancing their egocentric understanding and task performance.
Jianxiong Gao, Zhaoxi Chen, Xian Liu +7 authors
LongVie 2, an end-to-end autoregressive framework, enhances controllability, visual quality, and temporal consistency in video world models through three progressive training stages.
Zhenglin Cheng, Peng Sun, Jianguo Li +1 authors
TwinFlow is a 1-step generative model framework that enhances inference efficiency without requiring fixed pretrained teacher models or standard adversarial networks, achieving high performance on text-to-image tasks and scaling efficiently.
Ke Xing, Longfei Li, Yuyang Yin +8 authors
StereoWorld generates high-quality stereo video from monocular input using a pretrained video generator with geometry-aware regularization and spatio-temporal tiling.
Junyi Hou, Andre Lin Huikai, Nuo Chen +2 authors
PaperDebugger is an in-editor academic writing assistant that integrates large language models, enabling direct interaction within LaTeX editors for document state management, revision, and literature search.
Zhengliang Shi, Yiqun Chen, Haitao Li +23 authors
Deep Research systems integrate LLMs with external tools to enhance problem-solving capabilities, involving query planning, information acquisition, memory management, and answer generation.
Wenqiang Sun, Haiyu Zhang, Haoyuan Wang +7 authors
WorldPlay is a streaming video diffusion model that achieves real-time, interactive world modeling with long-term geometric consistency by using a Dual Action Representation, Reconstituted Context Memory, and Context Forcing.
Alexander Amini, Anna Banaszak, Harold Benoit +30 authors
LFM2, a family of compact foundation models, achieves high efficiency and performance on-device through hardware-in-the-loop architecture search and advanced training techniques, supporting various tasks including multimodal applications.
Shengming Yin, Zekai Zhang, Zecheng Tang +11 authors
A diffusion model for decomposing RGB images into semantically disentangled RGBA layers enables consistent image editing through independent manipulation of individual layers.
Weichen Fan, Haiwen Diao, Quan Wang +2 authors
Unified Autoencoding combines semantic and pixel-level information through a frequency-band modulator, resulting in a latent space with state-of-the-art performance on image benchmarks.
Jiaqi Tang, Jianmin Chen, Wei Wei +7 authors
A novel framework, Robust-R1, enhances multimodal large language models' robustness to visual degradations through explicit modeling, supervised fine-tuning, reward-driven alignment, and dynamic reasoning depth scaling, achieving state-of-the-art performance on real-world degradation benchmarks.
Ethan Chern, Zhulin Hu, Bohao Tang +4 authors
Real-time multimodal video generation via diffusion is enabled by an improved distillation approach with multimodal conditioning and optimized scheduling, reducing inference latency while maintaining quality for interactive systems.
Yuqiao Tan, Minzheng Wang, Shizhu He +6 authors
The paper decomposes the policy of large language models into internal layer and modular policies, revealing distinct reasoning patterns across layers and proposing Bottom-up Policy Optimization to enhance performance on complex reasoning tasks.
Jiaqi Wang, Weijia Wu, Yi Zhan +6 authors
The Video Reality Test benchmark evaluates the realism and detection of AI-generated ASMR videos with audio, revealing that even the best models can deceive VLMs and humans, highlighting limitations in perceptual fidelity and audio-visual consistency.
Qinghe Wang, Xiaoyu Shi, Baolu Li +7 authors
MultiShotMaster extends a single-shot model with novel RoPE variants for flexible and controllable multi-shot video generation, addressing data scarcity with an automated annotation pipeline.
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