👍 83
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 论文关注于生物学、化学和材料科学中的结构-性质关系,通过深度结构推理提供透明且跨学科的解决方案。核心方法是解释结构证据,通过深度学习模型建立结构与属性之间的机制解释。研究成果显示,该方法在相关领域具有重要意义,能够推动科学推理和材料设计的发展。
👍 51
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 针对主流视觉-语言-行动(VLA)模型在长时间依赖任务中的局限,提出了一种双潜在记忆框架。该方法通过扩展观察窗口和高效检索历史信息来改进决策过程,增强了对复杂任务的解决能力。实验表明,该模型在任务执行效果上优于现有方法,具有更强的适应性,在机器人操作领域展现潜力。
👍 47
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 针对视频理解的复杂性,提出了一个新的评估框架Video-Oasis,以应对现有基准无法有效评价视觉、语言和知识推理的局限性。研究表明,该基准能够更全面地评估视频理解模型的推理能力,推动视频处理和理解技术的发展。
👍 28
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是LingBot-World的升级版本,突破了交互范围的限制,保持输出质量的一致性。该模型通过精心设计的因果预训练策略,实现了长期互动,适用于更复杂的对话系统,推动人机交互的进一步发展。
👍 26
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 IdeaGene-Bench(IG-Bench)作为一个新的基准,旨在评估科学思想的传承和生成过程,灵感来源于生物基因的继承结构。该研究揭示了当前AI系统在继承结构方面的能力,为科学建模与知识创新提供了新的方法论。
👍 26
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场景,提出了一种政策感知的提示适应方法。该方法动态调整提示以适应训练中不断变化的策略,提升了策略优化的效率。研究为非监督学习环境下的AI决策提供了新的思路,具有实际应用价值。
👍 25
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 UniClawBench是一个针对现实世界任务的通用基准,旨在有效评估积极性代理的能力。研究填补了现有基准的空白,提供了评估代理在日常工具使用中的表现的新途径,对智能助手和自动化应用具有重要意义。
👍 24
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 LongE2V是一种新颖的方法,通过视频扩散模型实现基于事件的长时间视频重建和预测。该方法在高质量视频恢复方面,尤其是在处理稀疏事件流时显示出优势,为视频生成领域的长期稳定性提供了新的解决方案。
👍 15
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 Canvas360提出了一种结合几何感知预训练与特定下游任务微调的两阶段框架,致力于提升上下文全景生成的质量。此方法能够有效解决训练数据稀缺的问题,为生成高质量的全景图像提供了支持,具备广阔的应用前景。
👍 15
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 (Oxygen AIIC) V1为商品理解与管理提供了一种工业级解决方案,支持数十亿SKU的数据管理,通过高质量、结构化的商品知识提升用户体验及运营效率,推动电商智能化发展。
👍 13
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 针对长时程任务的强化学习,提出了单回合异步优化方法,极大地提高了训练效率。相比传统的同步批处理方法,本研究的异步RL能够更好地适应大规模的策略学习任务,为强化学习在大模型中的应用提供了新思路。
👍 11
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提出了一个统一的模拟与实际基准,以便全面评估通用机器人操作策略的能力。研究揭示了现有基准在系统性评估上的不足,推动机器人通用性与操作能力的深入发展,适用于实际应用场景。
👍 10
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致力于在移动设备上实现图像到视频的扩散,专注于电影镜头效果的生成。虽然Diffusion Transformers在视频生成上表现优异,但此方法通过优化参数和流程,解决了现有方案的局限,为移动内容创作提供了新方案。
👍 10
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 Jet-Long通过动态双焦RoPE实现了高效的长上下文扩展,为训练中的上下文处理提供新方案。该方法使得在长上下文应用中,提高LLM的零-shot表现,具有显著的性能提升,对实时应用具有重要意义。
👍 10
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 该研究提出了稀疏Delta记忆,通过稀疏性提升线性RNN的状态规模,解决了与softmax注意力模型相比在长时记忆召回上的不足。研究成果为高效的时间序列学习模型发展提供了新思路,具有较强的实用性。
👍 9
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 OpenCoF通过视频生成学习推理,将推理能力的实现与时间相关的帧连接起来,为理解逻辑后果提供了一种新路径。该方法在复杂决策模型中展现出潜力,有助于推动推理与生成的结合。
👍 9
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 自动化设计的思想通过模块化组合感知、记忆、规划与行动,展现了建设具身智能体的新思路。该研究展示了在选择信息存储和处理过程中如何减少人为因素,使得构建更智能的代理成为可能,推动人工智能的架构设计革新。
👍 8
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构建了一个城市级的真实世界测试平台,旨在让AI建立相应的空间表示。该平台为进一步发展场景重建和具身智能提供了新的环境支持,展现出在大规模建模能力上的潜力。
👍 8
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在生成时的token级动态,提出了一种通过逐token处理的方式解析多模态生成过程。该研究为提升生成效能提供了新视角,推动视觉与语言的深度融合。
👍 7
07/08 20:00
In long-horizon tasks, decision-relevant state is often scattered across an expanding trajectory, while the action agent must surface it and act. As trajectories grow, task requirements, environment facts, prior attempts, diagnoses, and open subgoals can be buried in the context window or pushed bey
中文介绍 该研究提出了一种主动记忆代理,用于长时间任务中的决策支持。利用历史决策信息,该方法有效地提升了长程任务的决策质量,为长时程代理的智能化提供了新的解决路径,具有重要的实际应用价值。