👍 77
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 本研究探讨如何使用深度结构推理技术来理解结构与性质的关系,核心方法是通过分析结构证据来解释这些关系,从而增强生物、化学和材料科学中的科学理解。该方法不仅提高了跨学科的透明性,还在分析的准确性上取得了显著的进展。意义:推动了在科学推理和材料设计方向的研究进展。
👍 50
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 提出双重潜在记忆模型,以解决视觉-语言-行动(VLA)模型在长时间依赖任务中的不足。通过扩展观察窗口并从记忆中检索历史信息,显著提高了模型在复杂任务中的表现。实验结果表明该模型在长时间任务中的准确率得到提升,推动了机器人操作的智能化。意义:为机器人推理和长期任务处理提供新思路。
👍 43
07/01 20:00
The inherent complexity of video understanding makes it difficult to determine whether Video-LLM benchmark performance stems from visual perception, linguistic reasoning, or knowledge priors. While many benchmarks have emerged to assess high-level reasoning, shared criteria for evaluating video unde
中文介绍 研究视频理解的评估方法,指出现有基准无法有效区分视觉感知、语言推理和知识先验的贡献。提出一个全新的视频理解评估框架,通过引入共享标准,提高视频-LLM基准的有效性,力求建立一套综合的评估体系。意义:推进了视频理解技术的标准化与应用。
👍 27
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 提出LingBot-World 2.0,通过四个升级版实现无限交互范围,保持输出质量的一致性。核心技术是精心设计的因果预训练策略,能够在复杂环境中自如处理多种交互。实验表明,该模型在模拟真实环境中的表现明显提升,推动了智能体与环境的交互研究。意义:为智能体在开放世界中的应用奠定基础。
👍 25
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 针对非可验证的强化学习(RL)任务,提出了一种新的策略感知提示适配方法,通过动态调整提示以优化训练过程。实验结果显示,这种方法提升了模型适应不同策略的能力,有效改善了任务完成率。意义:在智能体的适应性和灵活性方向上具有重要启示。
👍 22
07/08 20:00
The rapid development of large language models and multimodal large language models has accelerated the emergence of proactive agents capable of operating everyday tools and assisting users in real-world environments. However, existing benchmarks struggle to evaluate such agents effectively, as they
中文介绍 提出UniClawBench,一个通用基准评估现实任务中的主动智能体。该基准旨在解决现有评估难度大、覆盖面不足的问题,结合多模态数据,提供全面的性能评估。应用实验显示,新的基准可以有效评测主动智能体的实用性。意义:促进了智能体应用的标准化与广泛应用。
👍 22
07/08 20:00
Scientific ideas rarely start from a blank page. They inherit mechanisms, repair known limitations, and recombine pieces of earlier work, much like biological genomes. Current benchmarks still say little about whether AI systems can follow this inheritance structure. We present IdeaGene-Bench (IG-Be
中文介绍 本研究通过IdeaGene-Bench提出了一种科学思想的生成和推理基准,重点关注科学思想的继承特性。该基准能够有效评估AI系统在遵循科学思想传承结构上的能力。实验结果显示,AI系统在模拟中能显著提升创意生成的效率。意义:丰富了科学推理和知识生成领域的研究。
👍 19
07/08 20:00
Recovering high-quality video from sparse event streams is a challenging task. Regression methods often blur textures, while existing generative models struggle with long-term stability. We propose LongE2V, a novel approach that leverages pre-trained video diffusion priors to jointly handle event-ba
中文介绍 提出LongE2V,一种基于视频扩散模型的新方法,旨在从稀疏事件流中重建高质量视频。该方法结合了预训练的视频扩散先验,解决了生成过程中模糊和长时间稳定性的问题,展现出优异的性能。实验结果显示,其在视频重建和预测上的准确率明显提高。意义:为视频处理和生成技术的发展提供新的视角。
👍 14
07/08 20:00
In this work, we present Canvas360, a two-stage framework for in-context panoramic generation that combines geometry-aware pretraining with downstream task-specific fine-tuning. To address the lack of large-scale, high-quality training data tailored to in-context panoramic tasks, we propose Canvas36
中文介绍 提出Canvas360,一个基于几何感知预训练的全新框架,用于上下文全景生成。该方法通过两阶段的训练策略,克服了现有数据集不足的问题,提升了生成的多样性与真实性。实验结果显示,生成的全景效果显著优于传统方法。意义:为计算机视觉中的背景生成提供了新的解决方案。
👍 14
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 AIIC是一个工业规模的LLM/VLM中心解决方案,专注于商品理解与管理。通过开发高质量的商品知识体系,显著提升了用户体验并降低运营成本。系统在处理千万级SKU时展现出卓越性能,推动电商技术的变革与应用。意义:在电子商务智能化与资源管理方面具有重要影响。
👍 10
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 本研究提出单回合异步优化方法以提升代理强化学习(RL)效率。在执行时,以非同步方式进行训练,克服了传统同步方法的效率瓶颈,显著提升了模型在长时间任务中的表现。实验结果表明,该方法降低了训练时间,提高了任务完成率。意义:为强化学习的应用与实践提供了新的方向。
👍 8
07/03 20:00
The growing demand for image-to-video creation on mobile devices has increasingly focused on cinematic motion effects like bullet time, dolly zoom, slow motion, etc. While Diffusion Transformers (DiTs) exhibit strong performance in video generation, their large parameter sizes and multi-step iterati
中文介绍 CineMobile致力于移动设备上的图像到视频的生成,专注于电影级运动效果。尽管Diffusion Transformers在视频生成中表现优秀,但面临着参数庞大和迭代过程慢的问题。提出一种优化方法,大幅提升了生成效率与效果。意义:推动了移动设备图像合成技术的发展。
👍 8
07/07 20:00
Modern LLMs are increasingly deployed in long-context applications such as retrieval-augmented generation, repository-level coding, and agentic workflows whose accumulated reasoning and tool traces routinely push the input an order of magnitude past the pretraining window, making zero-shot context e
中文介绍 提出Jet-Long,通过动态双焦点RoPE实现长上下文扩展,旨在解决现代LLM在长上下文应用中的局限性。该方法优化了输入信息的处理方式,提升了模型在推理与工具使用中的能力。实验验证了该模型在多种任务中的有效性与稳定性。意义:为大规模语言模型的应用与发展开辟了新思维。
👍 8
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提供了一个统一的仿真与现实基准,用于全面评估通用机器人操控策略。此研究旨在填补现有基准在任务复杂性和真实世界应用中的不足,系统评估机器人在多个任务中的表现,推动了智能体发展与评估的规范化。意义:对机器人技术研究与应用提供了重要的评估基础。
👍 7
07/07 20:00
Linear attention models allow a fixed state size and a fixed amount of compute per token. However, due to their limited state size, linear attention models fall behind in long-context recall compared to softmax-attention-based transformer architectures. Increasing the state size of linear attention
中文介绍 提出稀疏增量记忆方法,增强线性RNN在长上下文 recall任务中的表现,该方法通过稀疏性扩展了线性注意模型的能力。实验结果表明,其在处理复杂上下文时的效率显著优于传统方法,为长序列任务的模型设计提供了新思路。意义:对序列模型的优化与发展具有重要推动力。
👍 7
07/02 20:00
Embodied agents are typically built as hand-designed compositions of perception, memory, planning, and action modules. This modularity exposes a large architectural design space, but current systems still rely on researcher intuition to choose where information is stored, how observations are proces
中文介绍 针对建设身体代理的模块化设计现状,提出一种自动化架构设计方法,以减少人工干预。通过智能算法,系统能够自主选择信息存储方式与观察处理机制,优化了代理的整体功能与表现。实验表明,该方法在多模态任务中提升了代理的适应性。意义:促进了智能体架构设计的自动化进程。
👍 6
07/08 20:00
Reasoning has become a core capability for large models, especially when reliable decisions require understanding logical consequences. Recent video generation models offer a reasoning path distinct from previous Chain-of-Thought (CoT): reasoning can unfold through temporally connected frames, known
中文介绍 研究通过视频生成来学习推理能力。采用时间上相关的帧连接生成推理路径,与传统的链式思维(CoT)方法不同,提供了一种新的推理方式。实验结果显示,该模型在逻辑推理任务中的效率明显提升,推动了推理技术的进一步发展。意义:在视频理解与推理领域具有重要的研究价值。
👍 6
07/06 20:00
We present AgentLens, a production-assessed benchmark for interactive code agents. Most code-agent benchmarks reduce a run to a single bit -- did the task pass? -- but the people who actually use these agents experience the entire trajectory: how the agent follows instructions, uses its tools, verif
中文介绍 AgentLens是一个生产评估的交互代码代理基准,旨在全方位评估代码执行轨迹的质量,而不仅仅是任务是否完成。该模型结合多项指标,深入分析智能体的表现,提高了评估的全面性和准确性。实验结果表明,使用该基准的代理在用户反馈中表现更为优秀。意义:为智能体评估的科学化提供了基础,有助于推动技术的普及应用。
👍 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(MLLMs),提出一种逐词关注的生成方法,兼顾视觉与语言信息。通过分析层之间的动态计算,该方法达到提升模型理解上下文的能力,显著提高了生成效果及用户交互质量。实验结果显示,模型在各类生成任务中的表现更优。意义:为多模态生成技术的发展提供了新思路。
👍 5
07/06 20:00
Humans can navigate an unfamiliar city and gradually form a coherent spatial mental map spanning tens of square kilometers. Can AI build spatial representations at a comparable scale? Although recent foundation models have advanced scene reconstruction and embodied intelligence, scaling to entire ci
中文介绍 WildCity项目创建了一个市规模的真实测试平台,致力于渲染、模拟与空间智能的研究。通过将AI在大规模城市环境中的表现与人类的导航能力相比较,推动了智能体在真实世界中的应用与发展。实验显示,智能体能在复杂场景中有效构建空间认知。意义:为城市空间理解与导航技术的发展提供了实证基础。