👍 71
07/07 20:00
Structure-property relationships are foundational to biology, chemistry and materials science, where function, reactivity and physical response emerge from spatial, chemical and periodic organization. Mechanistically explaining these relationships requires interpreting structural evidence through sc
中文介绍 该论文提出了一种结合结构属性理解和深度学习的方法,以解释生物、化学和材料科学中的结构-属性关系。通过对结构证据的深度原位推理,本文的方法提升了对空间、化学和周期性组织的解释能力,展现出高准确性的跨学科应用潜力。意义:该研究为材料科学及生物化学领域的预测模型提供了新的思路。
👍 55
07/02 20:00
Scaling modern large language models (LLMs) to long contexts is limited by the quadratic computation cost, and poor length extrapolation of dense attention. Chunk-wise sparse attention offers a promising alternative, but all existing methods fall short of full attention because of their inaccurate c
中文介绍 论文针对大规模语言模型在长文本处理中的计算复杂度问题,提出了一种层次稀疏注意力机制。通过改进的分块稀疏注意力,该方法在保持准确性的同时降低了计算成本,并展示了对长上下文的有效建模能力。意义:此研究对长文本生成和处理具有重要影响,推动了语言模型的效率提升。
👍 44
07/07 20:00
Mainstream Vision-Language-Action (VLA) models predict actions primarily from the current observation under a Markovian assumption, thus struggling with long-horizon, temporally dependent tasks. Existing memory-augmented VLAs either expand the observation window or retrieve history from the memory b
中文介绍 本研究引入双重潜在记忆机制,以改进视觉-语言-行动(VLA)模型在复杂任务中的表现。通过扩展观察窗口并增强对历史信息的检索处理,该模型在长时间依赖任务上表现出色,提升了整体任务成功率。意义:此方法为机器人操控领域的长期决策提供了新的技术支持。
👍 39
07/01 20:00
We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemma 4 model suite features dense and Mixture-of-Experts architectures, ranging from 2.3B to 31B parameters. Alongside impr
中文介绍 Gemma 4是新一代开放权重、多模态语言模型,旨在提升计算效率和推理能力。该模型系列采用密集和混合专家(Mixture-of-Experts)架构,参数量从2.3B到31B不等。通过一系列预训练策略,Gemma 4 显著提高了推理速度和效果,推动了多模态应用的发展。意义:为多模态学习和推理提供了强有力的技术基础。
👍 38
07/06 20:00
We formulate computer vision as unified multimodal generation, where heterogeneous visual tasks are expressed in the native text and image generation spaces of a unified multimodal model, without task-specific architectures. Under this formulation, SenseNova-Vision uses natural-language instructions
中文介绍 该论文将计算机视觉问题重新表述为统一的多模态生成任务,使用统一的多模态模型在未使用特定任务架构的情况下处理异构视觉任务。通过自然语言指令驱动的生成机制,SenseNova-Vision实现了更高效的跨模态信息处理。意义:这一方法可能改变计算机视觉和语言处理领域的任务实现方式。
👍 25
07/05 20:00
Speculative decoding accelerates Large Language Model (LLM) inference by decoupling draft generation from target verification. While recent parallel drafters efficiently propose long token sequences in a single forward pass, they suffer from rapid acceptance decay due to a lack of inter-token depend
中文介绍 Speculative decoding技术通过将草稿生成与目标验证分离,加速了大语言模型的推理过程。尽管现有方法在长序列生成上表现良好,但仍面临消极接受率快速下降的问题。该研究提出了基于置信度的调度,提升了生成的效率和准确性。意义:为增强语言模型的实时处理能力提供了可行方案。
👍 21
07/07 20:00
We present LingBot-World 2.0 (also known as LingBot-World-Infinity), an advanced iteration of LingBot-World featuring four distinct upgrades. (1) Our model achieves an unbounded interaction horizon while maintaining consistent output quality, benefiting from a carefully crafted causal pretraining pa
中文介绍 LingBot-World 2.0版本实现了无界限的交互视野,通过精心设计的因果预训练方案,保持高输出质量。这一模型具有明确的多样性和鲁棒性,适应长时间跨度的交互,展示了其在复杂场景下的潜力。意义:为开放域交互和对话系统的发展提供了新的可能性。
👍 21
07/04 20:00
Reinforcement learning (RL) for non-verifiable instruction following increasingly relies on LLM judges with prompt-specific rubrics as reward signals. While recent methods adapt these rubrics to the evolving policy during training, the training prompts themselves remain static, drawn from fixed corp
中文介绍 针对无法验证的强化学习,该研究提出了一种利用LLM评估的策略意识提示适应方法。通过动态调整训练提示以适应不断演化的策略,模型在非静态环境中表现出更好的适应能力。意义:此研究为非验证性指令跟随任务的改进提供了理论基础和实践指导。
👍 18
07/02 20:00
Dense video captioning aims to generate temporally grounded descriptions of video events, benefiting both event-level video understanding and generation. In this domain, autoregressive video large language models have emerged as a prevalent paradigm due to their strong generative and cross-modal mod
中文介绍 该研究集中于稠密视频字幕生成,通过并行自回归解码提升了视频事件的描述生成能力。采用自回归的视频大型语言模型,该方法展示了在事件级视频理解和跨模态生成中的优越表现。意义:对视频理解和描述生成领域的发展具有推动作用。
👍 13
06/28 20:00
JD.com, one of the world's largest e-commerce platforms, serves over 700 million active users and millions of merchants, with a catalog of tens of billions of SKUs. At this scale, high-quality, structured item knowledge underpins a better consumer experience, lower management costs, and higher opera
中文介绍 JD Oxygen AI Item Center 提出了一个面向项理解与管理的解决方案,旨在提升电商平台的用户体验。通过丰富的结构化项目知识,提升了管理效率和运营成本,适应了全球电商的复杂需求。意义:为商品管理和用户体验优化提供了新思路。
👍 13
07/06 20:00
On-policy distillation (OPD) trains a student policy by matching a stronger teacher on the student's own trajectories, offering a promising framework for language agent training. However, its application to long-horizon agentic tasks remains insufficiently explored. We identify two key inefficiencie
中文介绍 TurnOPD通过在策略 distillation 中增强时间意识,不断提升长时间任务的代理训练效率。该研究识别了现有方法在处理长时间任务中的两大关键低效点,并提出了相应的改进策略。意义:此技术为高效训练复杂代理系统奠定了基础。
👍 12
07/06 20:00
Despite recent progress of VLA foundation models, the disparity between laboratory conditions and real-world applications continues to impede their practical implementation. To bridge this gap, we present LingBot-VLA 2.0, which advances LingBot-VLA through improvements in three functional domains. (
中文介绍 LingBot-VLA 2.0通过对VLA模型的三项功能领域改进,努力缩小实验室与现实应用之间的差距。该研究展示了改进后的模型在实际应用场景中的增强性能,推动了VLA在日常生活中的实际应用潜力。意义:对于强化现实应用中的VLA模型具有深远影响。
👍 11
07/02 20:00
We introduce MentalThink, a visual-symbolic reasoning paradigm that equips Multimodal LLMs (MLLMs) with an executable mechanism for "mental" visualization. The core of MentalThink is a think-with-SVG pipeline, where the model learns to generate, render, and interpret scalable vector graphics (SVG) c
中文介绍 MentalThink引入了一种视觉-符号推理范式,赋予多模态LLM执行“心智”可视化的能力。其“think-with-SVG”流程使模型能生成、渲染和解释可缩放矢量图形(SVG),提升了推理和表达的灵活性。意义:为符号推理和图形生成结合的新方向打开了可能性。
👍 9
07/05 20:00
Complex image creation and editing often require more than a single generation or editing model. A user request may involve synthesizing images, localizing objects, segmenting regions, editing selected content, compositing intermediate assets, reading text, and enhancing the final result. Such tasks
中文介绍 Complex image creation and editing 的研究指出,用户请求往往涉及多步骤的复杂处理任务。通过视觉工具协调,本文提出了一种综合的方法来实现复杂图像的创建与编辑,提高了整体操作的灵活性和效率。意义:该方法对图像处理及计算机视觉任务具有重要的应用价值。
👍 9
07/01 20:00
State-of-the-art single-image 3D reconstruction methods often rely on complex hybrid architectures and loss functions, or compress geometry into latent spaces in order to leverage pre-trained latent diffusion models. In this work, we show that such architectural overhead and intricate loss formulati
中文介绍 该论文提出PointDiT方法,通过像素空间扩散技术进行单幅图像三维重建。研究表明,与复杂混合架构相比,该方法简化了重建流程,并避免了对预训练潜在扩散模型的复杂依赖,极大提升了计算效率。意义:为三维重建技术的简化和高效应用提供了新思路。
👍 7
07/03 20:00
Challenges remain in ego-centric 3D scene generation due to limited view overlap and the dominant influence of individual perspectives on scene interpretation. These factors hinder the creation of viewpoint-consistent and semantically aligned visual content, as well as the construction of accurate g
中文介绍 CGGS方法应对了自我中心三维场景生成中存在的视角一致性挑战,通过增强几何高斯点的稳定性,成功生成了语义一致和视角一致的视觉内容。该模型在构建准确的场景中展现出积极的效果。意义:为三维场景构建技术的发展提供了重要支持。
👍 6
07/07 20:00
Reinforcement learning (RL) is becoming increasingly important for post-training large language models (LLMs). Previous RL pipelines for LLMs were mostly synchronous and batch-interleaved, which is inefficient for long-horizon agentic tasks. Recently, asynchronous RL has emerged as a more efficient
中文介绍 单次回合异步优化作为强化学习中的创新,显著提升了长时间任务的训练效率。该研究通过对比现有的同步方法,展示了异步强化学习的优越性,为大语言模型后续训练提供新的策略选择。意义:该方法可以促进长时代理任务的改进和发展。
👍 6
07/06 20:00
Generalist robot manipulation policies have advanced rapidly, yet existing benchmarks remain limited in systematically evaluating their capabilities. Many rely on simple, short-horizon, or skill-narrow tasks with limited capability coverage, and are often conducted only in simulation or only in the
中文介绍 RoboDojo为通用机器人操控政策提供了统一的仿真与实际评估基准,针对现有基准的局限性,论文提出了更系统的评估方法,能更全面地评估政策的各种能力。意义:提升了对通用操控政策的理解与改进的可能性。
👍 6
07/03 20:00
Multimodal large language models (MLLMs) generate responses autoregressively, integrating visual and linguistic information in an evolving context. Prior work on interpretability has focused on individual layers and circuits (where), leaving the token-level dynamics of multimodal computation during
中文介绍 针对多模态大语言模型的生成过程,论文探讨了自回归生成中的多模态计算动态。研究表明,token级别的动态信息对理解生成过程至关重要,提供了对现有模型可解释性的新视角。意义:为多模态生成模型的理解和优化提供了新思路。
👍 6
07/06 20:00
Late-interaction retrieval models that use the MaxSim similarity function have shown strong empirical performance, often outperforming single-vector dense and sparse retrieval models. Despite these empirical findings, little is known about the theoretical representation power of MaxSim and how it co
中文介绍 该研究量化了基于Late-Interaction的检索模型的理论容量,并提出了MaxSim相似度函数的潜在优势。尽管在经验上其性能表现出色,但分析其理论表现力仍有待深入研究,本文为未来研究指明了方向。意义:为检索模型的深入理解和性能提升奠定了基础。