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Jintao Zhang, Kai Jiang, Jintao Chen +24 authors
Vidu S1 is a real-time interactive video generation model that supports voice-controlled digital character animation with infinite-length output and high frame rate on consumer hardware.
Shihao Wang, Shilong Liu, Yuanguo Kuang +10 authors
Parallel Box Decoding enables efficient and accurate unified visual grounding and detection by decoding geometric elements as atomic units, improving both throughput and localization quality.
Shijie Lian, Bin Yu, Xiaopeng Lin +10 authors
PhysBrain 1.0 leverages human egocentric video to generate physical commonsense supervision for vision-language-action models, achieving state-of-the-art performance in embodied control tasks through capability-preserving adaptation.
Yijia Fan, Zonglin Di, Zimo Wen +8 authors
RESOURCE2SKILL converts diverse multimedia tutorials and artifacts into structured, executable skills for software agents, improving performance through hierarchical retrieval, composition, and online acquisition.
Dongrui Liu, Yu Li, Zhonghao Yang +47 authors
A lightweight and scalable agent safety alignment framework is proposed to address emerging threats from advanced AI models, featuring taxonomy-guided training with minimal samples and efficient deployment in real-world scenarios.
Yang Liu, Enxi Wang, Yufei Gao +6 authors
MEDS is a memory-enhanced dynamic reward shaping framework that improves sampling diversity in reinforcement learning for large language models by identifying and penalizing recurrent error patterns through clustering of historical behavioral signals.
Jundong Xu, Qingchuan Li, Jiaying Wu +11 authors
EvoArena benchmark and EvoMem memory paradigm address the challenge of dynamic environments in LLM agents by modeling progressive updates and structured memory evolution, showing improved performance on evolving tasks.
Runming He, Zhen Hao Wong, Hao Liang +4 authors
DataFlow-Harness guides LLM agents to build persistent, editable data pipelines via incremental mutations and live platform grounding, achieving high reliability with lower cost and latency.
Alan Arazi, Eilam Shapira, Shoham Grunblat +8 authors
Multimodal tabular learning benchmarks reveal that task-specific embedding tuning improves performance over frozen pretrained embeddings, particularly when modalities provide complementary predictive signals.
Zixuan Huang, Yang Zhou, Kaixuan Wang +6 authors
Proposed multiple-choice planning and deferred trajectory verification reduce reasoning bias and improve verifiable autonomous driving decisions.
Ruofeng Yang, Yongcan Li, Shuai Li
ARIS is an open-source research harness that uses cross-model adversarial collaboration to ensure reliable long-term research outcomes through coordinated execution, orchestration, and assurance layers.
Peng Xia, Jianwen Chen, Xinyu Yang +10 authors
A continual meta-learning framework for large language model agents that jointly evolves policies and reusable behavioral skills while minimizing downtime through opportunistic updates and skill-driven adaptation.
Guoxuan Chen, Chufeng Xiao, Haoran Yang +30 authors
Boogu-Image-0.1 is an open-source unified multimodal model family that achieves strong text-to-image generation, editing, and bilingual rendering with low training cost by improving multimodal understanding, data quality, and agentic inference scaling.
Yihang Chen, Yuxiang Chen, Yuxuan Huang +3 authors
The study formalizes multi-agent LLM coordination via bilevel games and stochastic memory reflection, introducing a grounded evaluation gate and SRMA algorithm with convergence guarantees, validated on SWE-bench.
Aditi, Niket Agarwal, Arslan Ali +288 authors
Cosmos 3 is an omnimodal world model that processes and generates multiple data types through a unified mixture-of-transformers architecture, achieving state-of-the-art performance in various understanding and generation tasks.
Kangsheng Duan, Ziyang Xu, Wenyu Liu +3 authors
A lightweight image inpainting framework achieves high-fidelity results with significantly reduced parameters and inference time through novel local-global interaction blocks and adaptive distillation strategies.
Hengyi Xie, Chenfei Yao, Xianjin Wu +7 authors
TurboVLA replaces the LLM-centric vision-language-action pipeline with direct vision-language interaction and a compact decoder to cut inference costs while maintaining high robotic manipulation performance.
Xiaomin Yu, Yi Xin, Wenjie Zhang +12 authors
Researchers address the modality gap in multimodal learning by proposing a fixed-frame theory and a training-free alignment method that enables efficient scaling of multimodal models using unpaired data.
Haiwen Diao, Jiahao Wang, Chenjing Ding +62 authors
SenseNova-U1.5 is an 8B native unified multimodal model that performs visual understanding, reasoning, and generation without encoders or VAEs, achieving high fidelity and instruction following through patch reconstruction, curated data, expert optimization, and on-policy distillation.
Guochao Jiang, Jingyi Song, Guofeng Quan +3 authors
Dynamic Variance-adaptive Advantage Optimization (DVAO) addresses training instability in multi-reward reinforcement learning by adaptively weighting objectives based on empirical reward variance, maintaining bounded advantage magnitudes and improving multi-objective performance.
Subham Sekhar Sahoo, Lingjie Chen, Khiem Pham +14 authors
Diffusion-augmented autoregressive language models use parallel token sampling via distilled diffusion weights and a specialized sampler to accelerate inference without quality loss or draft models.
Hejun Dong, Junbo Niu, Bin Wang +3 authors
MinerU-Diffusion is a diffusion-based framework that replaces autoregressive decoding with parallel diffusion denoising for document OCR, improving robustness and decoding speed.
Xiangyan Qu, Zhenlong Yuan, Jing Tang +9 authors
Image-CoT methods are extended to image editing with ADE-CoT, which improves efficiency and performance through adaptive resource allocation, edit-specific verification, and opportunistic stopping mechanisms.
Zhifei Xie, Kaiyu Pang, Haobin Zhang +4 authors
Mega-ASR framework improves robustness in real-world speech recognition through compound-data construction and progressive acoustic-to-semantic optimization techniques.
Yuling Shi, Jinghan Xu, Kelin Fu +12 authors
SWE-Bench ProMax is a rigorously curated multilingual benchmark of large-scale code refactoring tasks that reveals substantial unsolved challenges for current AI coding agents.
Qing Zong, Jiayu Liu, Junhao Shen +9 authors
Agentic systems can achieve open-ended improvement through multi-component co-evolution that progressively removes fixed human constraints across agents, environments, and evolution mechanisms.
Yanzhe Chen, Zechen Bai, Zhijun Cao +7 authors
Show-Harness links vision-language models to robot control via discrete semantic actions interpreted by embodiment-specific modules, enabling zero-shot and efficient fine-tuned deployment across robots and GUIs.
Robbyant Team, Zelin Gao, Qiuyu Wang +21 authors
LingBot-World is an open-source world simulator with high-fidelity dynamics, long-term memory capabilities, and real-time interactivity for diverse environments.
Yicheng Zou, Dongsheng Zhu, Lin Zhu +171 authors
Intern-S1-Pro is a one-trillion-parameter scientific multimodal foundation model that enhances general and scientific capabilities through advanced agent functionalities and specialized task mastery across multiple scientific disciplines.
Yuxue Yang, Lue Fan, Ziqi Shi +3 authors
NeoVerse is a scalable 4D world model that enables pose-free reconstruction and novel-trajectory video generation from monocular videos with state-of-the-art performance.
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