👍 180
08/10 20:00
After an older adult misses a medication dose, a software agent can send another reminder and an embodied agent can bring the medication. Yet neither explains whether the person forgot, is confused, has side effects, or deliberately refused, nor what support is appropriate. This reveals a structural
中文介绍 提出了一种以人为中心的智能代理的新范式ComBodied Agents,该框架关注老年人用药提醒的有效性。通过分析传统软件代理和具身代理的不足,强调了了解用户背景对于提供适当支持的重要性。该研究对于提升智能代理在复杂人际互动中的表现具有重要意义。
👍 167
08/11 20:00
Turning a research idea into a complete paper requires more than text generation: the system must retrieve literature, design and execute experiments, revise claims according to evidence, produce publication-ready figures, and maintain consistency across a long generation process. We present Spark-t
中文介绍 提出了一种名为Spark-to-Paper的系统,通过整合检索文献、实验设计与执行、证据驱动修订等能力,将研究想法转换为完整论文。该系统不仅仅依赖文本生成,还在整个生成过程中维持一致性,为自动化学术写作做出贡献,可能影响学术与科学研究领域的效率。
👍 159
07/31 20:00
AI agents operate in persistent environments where early state changes can influence decisions far into the future. Unlike conventional language-model interactions, agent behavior is mediated through a shared state that is repeatedly modified and reused across long-horizon workflows. Current safety
中文介绍 探讨了开放式环境演化下的AI代理安全性问题,强调环境变化对agent决策的长期影响。通过引入动态共享状态的方法,旨在提升现有AI代理在复杂持续环境中的适应能力,为安全性研究提供新的视角。此研究可能在智能代理的安全性和可靠性方面带来重要影响。
👍 123
08/09 20:00
Agentic systems are increasingly expected to improve after deployment, yet single-entity self-evolution is often bounded by a static learning context, such as fixed tasks and feedback. This survey focuses on co-evolution in agentic systems, a multi-component form of self-evolution in which multiple
中文介绍 该研究聚焦于agentic系统中的共进化,探讨多组件自我进化的方法,以提升系统在部署后的持续改进能力。通过分析不同个体间的互动与反馈,提出了一种新的自我进化框架,为未来智能系统的设计和优化指明方向,特别是在自动化和自主决策系统中的应用。
👍 78
08/11 20:00
Recent work on distillation transfers the capabilities of large models to smaller ones often by updating the latter's parameters, through teacher forcing, on-policy distillation, and related training-time methods. In this paper, we ask whether such transfer can instead occur at test time. We study s
中文介绍 研究了在测试阶段进行强到弱能力转移的问题,挑战了传统的知识蒸馏方法。通过研究不同训练过程中的策略,探索了如何在大小模型之间实现能力转移,为AI模型在实际应用中的灵活性和效率提升提供了新思路。此研究将对模型压缩和迁移学习领域产生积极影响。
👍 72
08/11 20:00
AI models have achieved remarkable success across diverse domains, yet the mechanisms underlying their capabilities and the risks they may pose remain poorly understood. As AI development becomes faster and increasingly automated, mechanistic exploration remains largely manual, widening the gap betw
中文介绍 阐述了将人工智能视为科学工具的机制探索,关注于理解智能模型能力背后的机制与风险。该研究强调了在快速自动化发展的背景下,机制性探索的重要性,促进了对AI模型可解释性与安全性的关注,对于未来AI研究与开发具重要意义。
👍 71
08/05 20:00
Large Language Models (LLMs) increasingly act as agents whose procedural knowledge is stored in reusable skill packages and loaded at inference time. As skill libraries grow, a central challenge is to expose the smallest sufficient executable context under a limited context budget. Existing systems
中文介绍 提出了SkillZip,一个用于大规模代理技能库的合约保持图压缩方法。该方法旨在提高技能的重用性,并优化限制上下文预算下的执行效率。研究在应对可扩展技能库的重要性上具有广泛的应用潜力,尤其在复杂AI系统的设计中。
👍 26
08/07 20:00
The rapid advancement of Large Language Models (LLMs) is revolutionizing AI for Games by enabling open-ended and fluid interactive storytelling. However, existing research has largely overlooked the critical challenge of maintaining long-horizon logical consistency and narrative integrity against un
中文介绍 针对大语言模型(LLM)在互动叙事中的长期一致性问题,建立了基准测试。研究探讨了保持逻辑一致性与叙事完整性所面临的挑战,并为未来在动态游戏与叙事AI的设计中提供了技术指导,促进了长时间互动中AI的表现优化。
👍 25
08/06 20:00
Self-improving coding agents that iteratively rewrite their own source code have demonstrated impressive performance on coding tasks. However, existing solutions generally derive self-modification from a single failure trajectory at a time, overlooking rich comparative signals available in the agent
中文介绍 研究了一种递归自我改进编码代理的生成方案,Mendel Gödel Machine,通过对比演化来优化自我修改过程,使得代理能够有效学习并改进编码任务的表现。此方法为提高自我进化技术在编程任务中的创新性提供了新的可能性,促进了AI在自动代码生成领域的发展。
👍 16
08/10 20:00
Large language model (LLM) agents are increasingly deployed as personal assistants. Existing evaluations, however, mostly use short, self-contained requests in static environments. Everyday life assistance is different. A task runs for weeks rather than minutes. The world keeps changing while the ag
中文介绍 提出VibeLifeBench,以评估大语言模型(LLM)在动态真实世界中的长期生活辅助能力。该研究强调了现实生活中任务的复杂性与持续性,建立评估标准为改进个性化助手在日常生活中的应用奠定基础,具有广泛的实际应用前景。
👍 12
08/09 20:00
Large language model evaluations typically focus on performance under nominal conditions, creating an illusion of capability where models comfortably walk a narrow, highly optimized generation corridor. In real-world deployments, however, complex system prompts, safety guardrails, and structural con
中文介绍 引入了一种针对大语言模型鲁棒性的新诊断压力测试,解构了模型在实际环境中表现出的潜在能力与限制。通过挑战模型在复杂输入下的生成稳定性,该研究为提高模型在现实部署中的韧性与可靠性提供了新思路,可能影响智能模型在多领域应用时的表现。
👍 12
08/10 20:00
Self-evolving agents accumulate reusable skills by appending successful procedures and failure fixes. Over time, the same requirement is often restated in several branches, examples, and warnings, while common action sequences are copied rather than reused. The resulting skill becomes expensive to i
中文介绍 研究了一种通过发现可重用结构进行无评估的技能压缩方法,旨在提升自我进化代理的效率。该方法强调了技能的模块化,使得代理在不断积累经验的过程中能够降低技能的冗余性,具有助于优化智能代理的长期学习与发展。
👍 11
08/08 20:00
Long-horizon research agents solve open-ended tasks through iterative retrieval, aggregation, and synthesis, but context grows rapidly while the marginal value of additional evidence often declines. This leads to unnecessary token cost, higher latency, and noisier inputs for final report generation.
中文介绍 提出了一种边际价值估计方法,以提升长期研究代理在开放任务中的效率和有效性。研究聚焦于如何通过迭代检索与合成来降低额外证据的无效成本,从而在生成最终报告的过程中提高速度与准确性,为长期任务的执行策略提供了新视角。
👍 11
08/10 20:00
We study reference-free post-training for multilingual machine translation with open large language models. Starting from the supervised-finetuned MiLMMT-46-v0.1 models, we apply Group Relative Policy Optimization (GRPO) with a reward that averages two reference-free quality estimation models and is
中文介绍 探索了无参考后训练对多语言机器翻译的影响,采用Group Relative Policy Optimization(GRPO)策略对模型进行优化。该研究为多语言跨域迁移提供了新的框架,强调了模式识别与语义理解在翻译任务中的重要性,或将推动机器翻译技术的进步。
👍 10
08/10 20:00
Long-document understanding often requires reasoning over many visually rich pages, making inference costly and prone to context rot. In this work, we propose InSight-doc, an agentic visual perception framework that treats visual resolution as an adaptive reasoning-time resource. InSight-doc starts
中文介绍 提出了InSight-doc框架,以提升长文档理解的视觉感知能力。该方法将视觉分辨率作为适应性推理资源,旨在应对长文档处理中的上下文丧失问题,为信息提取与长文本理解提供了解决方案,尤其适用于法律、医学等领域的应用。
👍 10
08/08 20:00
We present 360CityArena, a benchmark for evaluating the urban exploration capabilities of embodied agents within a photorealistic environment constructed from 360-degree videos. Existing outdoor benchmarks either lack sufficient photorealism or complexity, resulting in a considerable gap from real-w
中文介绍 推出了360CityArena,这是一个针对具身代理在仿真城市环境中的探索能力的评估基准。通过结合360度视频的方法,该研究填补了现有基准在现实感与复杂性方面的空白,可为未来城市导航与代理技术提供重要的研究基础。
👍 10
08/10 20:00
Visual document retrieval (VDR) is dominated by multi-billion-parameter models that are slow to index at full corpus scale and expensive to serve. Prior compression routes either train a smaller multi-vector encoder from scratch or distil only the query side; neither yields a compact single-vector r
中文介绍 DistilVDR提出了一种紧凑的端到端视觉文档检索方法,利用双学生蒸馏技术来缩小模型规模。通过提高单一向量检索的效率,同时保持良好的性能,研究为视觉文档检索领域提供了新的解决方案和思路,以应对大规模文档数据的挑战。
👍 10
08/10 20:00
Large language models (LLMs) are increasingly deployed as mobile assistants, where a key challenge is leveraging personal information scattered across multiple applications (apps) to complete user instructions. However, due to the lack of dedicated benchmarks, their capabilities remain poorly unders
中文介绍 提出了一种针对散布在多个应用中的个人信息的评估框架SPIEval,旨在增强大语言模型(LLM)作为移动助手的能力。该研究通过检验LLM在多源数据整合中的表现,为未来个性化AI助手的开发提供了技术参考,促进智能助手的实用性。
👍 8
08/10 20:00
Embodied agents are increasingly built as systems around foundation models, where performance depends not only on model weights but also on the skills, context, action interfaces, and execution harness surrounding the model. While supervised fine-tuning and reinforcement learning can adapt agents to
中文介绍 探究了通过技能平台进化构建自我进化具身代理的可能性。研究强调基础模型和周边技能之间的协同作用,使得代理能够在各种任务中实现更加灵活的适应性,为设计高效能智能系统提供了新方向,对于具身智能的研究具有重要意义。
👍 8
08/06 20:00
Query-based mask transformers assemble segmentation outputs through pixel-wise competition among query predictions of the final layer, yet this inference process is not explicitly optimized during training. We identify two key mismatches: the query with the highest probability-mask score does not ne
中文介绍 iFAN研究了一种适用于简单遮罩变换器的推理感知学习方法,解决了训练与推理过程中的指标不符问题。通过优化查询与遮罩分数的匹配,增强了模型在图像分割等任务中的表现,为视觉模型的改进提供了新的思路。