👍 85
06/23 08:00
A world model predicts environment dynamics based on current observations and actions, serving as a core cognitive mechanism for reasoning and planning. In this work, we investigate how world modeling based on language models can further push the boundaries of general agents. (i) We first focus on b
中文介绍 提出Qwen-AgentWorld框架,基于语言模型构建世界模型用于通用智能体推理和规划。通过预测环境动态,提升智能体在复杂任务中的决策能力。
👍 47
06/23 08:00
We introduce NatureBench, a cross-discipline benchmark of 90 tasks distilled from peer-reviewed Nature-family publications, designed to evaluate whether AI coding agents can move beyond reproduction toward discovery on real scientific problems. NatureBench is built on NatureGym, an automated pipelin
中文介绍 发布NatureBench跨学科基准,包含90个来自Nature系列论文的任务,用于评估编码智能体在真实科学问题上的发现能力。基于NatureGym自动化流水线构建,推动AI从复现走向科学发现。
👍 34
06/18 08:00
MLLM-based mobile GUI agents have made substantial progress in UI understanding and action execution, but adapting them to real target apps remains costly because mobile apps are numerous, frequently updated, and hard to cover with human-written tasks, demonstrations, or reward labels. Existing anno
中文介绍 提出MobileForge,一种无需标注的移动GUI智能体自适应方法。利用分层反馈引导策略优化,使MLLM智能体无需人工编写任务或标注即可适应真实目标应用。
👍 33
06/18 08:00
MLLM-based mobile GUI agents have made substantial progress on short-horizon tasks, yet remain unreliable on long-horizon tasks that require retaining intermediate facts across many steps and app transitions. We attribute this limitation to ReAct-style prompting, which passively accumulates per-step
中文介绍 提出MemGUI-Agent,端到端长时移动GUI智能体,通过主动上下文管理解决多步任务中的中间事实遗忘问题,优于ReAct式被动累积策略。
👍 25
06/22 08:00
AI agents are driving a new software paradigm, with the ability to autonomously call tools, extract information, manage memory, and complete tasks that span applications and data sources. Most existing end-user operating systems, however, are designed for application-centric workflows and offer litt
中文介绍 提出AOHP,开源操作系统级智能体框架,支持个性化、高效、安全的交互。通过统一工具调用、信息提取和内存管理,实现跨应用与数据源的自主任务完成。
👍 25
06/23 08:00
Agentic language models dramatically expand the applications of AI yet little is publicly known about how to curate training data for broadly capable agents. Existing open efforts such as SWE-Smith, SERA, and Nemotron-Terminal typically target a single benchmark, leaving open the question of how to
中文介绍 提出OpenThoughts-Agent,探索面向通用智能体的训练数据配方。通过跨基准数据混合策略,解决现有开放努力仅针对单一基准的问题,提升智能体广泛能力。
👍 20
06/20 08:00
We present BioMatrix, the first multimodal foundation model that natively integrates sequences, structures, and natural language for both molecules and proteins within a single decoder-only architecture. Existing biological foundation models pursue native multimodality and broad entity coverage sepa
中文介绍 提出BioMatrix,首个多模态基础模型,在单一解码器架构中原生整合序列、结构和自然语言,覆盖分子和蛋白质。实现实体覆盖与多模态的统一。
👍 19
06/11 08:00
Mental disorders are highly prevalent worldwide, but the shortage of psychiatrists and the inherent subjectivity of interview-based diagnosis create substantial barriers to timely and consistent mental-health assessment. Progress in AI-assisted psychiatric diagnosis is constrained by the absence of
中文介绍 提出LingxiDiagBench,多智能体框架用于评估LLM在中文精神科咨询与诊断中的表现。弥补AI辅助诊断缺乏高质量基准的空白,促进精神健康评估。
👍 13
06/22 08:00
Modern text-to-image models excel in visual fidelity and prompt adherence. However, this strict adherence comes at the cost of diversity: generated samples tend to collapse into a single visual interpretation. Existing methods to improve diversity produce outputs driven by incidental variations rath
中文介绍 提出Semantic Browsing方法,实现文本到图像生成中的可控多样性。通过语义层次控制,避免现有方法仅产生偶然变化,增强生成图像的视觉多样性。
👍 13
06/23 08:00
Generating explorable 3D scenes from a single image requires strong generative priors and accurate geometric representations suitable for downstream use. Current video diffusion models offer high-quality generation and implicitly encode multi-view geometric structure in latent space. However, existi
中文介绍 提出FLAT(前馈潜变量三角形溅射),从单张图像生成几何准确的3D场景。利用视频扩散模型隐式编码多视图几何结构,提升生成场景的准确性和可探索性。
👍 10
06/10 08:00
Scientific discovery workflows usually contain and rely heavily on lab notes, where researchers record observations, interpret uncertain results, and plan follow-up experiments. Such informative lab notes preserve evolving scientific reasoning and author uncertainty, rather than polished final resul
中文介绍 提出Notes2Skills,从实验室笔记中提取不确定感知的科学智能体技能。保留研究者记录的不确定性和推理过程,将原始笔记转化为可执行的智能体能力。
👍 8
06/23 08:00
Experience-driven self-evolution is critical for large language model (LLM) agents to improve through open-world interaction. However, existing experience learning methods mostly rely on single-agent loops, where the same agent executes tasks, summarizes outcomes, and determines memory content. This
中文介绍 提出执行-蒸馏-验证(Execute-Distill-Verify)范式,打破单智能体闭环中的自我确认陷阱。通过分离执行、经验提炼和验证,提升LLM智能体在开放世界中经验学习的可靠性。
👍 7
06/22 08:00
What is an agent? What constitutes agency? With the rise of Large Language Model (LLM) systems marketed as ``coding agents'', ``AI co-scientists'', and other ``agentic" tools that promise to drive up productivity, and at the same time, ``existential" concerns such as AI escaping human control with d
中文介绍 对LLM驱动的智能体概念进行批判性分析,探讨“智能体”定义及其在生产力和安全方面的含义,为理解当前AI系统提供理论框架。
👍 7
06/19 08:00
Open-weight Large Language Models (LLMs) enable scientific progress and broad deployment. However, they make it difficult to control access to sensitive capabilities. Current practice either suppresses dangerous capabilities before release or mediates access through closed services that use speciali
中文介绍 提出分离公开与私有能力的方法,使得开放权重LLM在保留科学进步的同时,控制敏感能力的访问。通过训练时隔离能力,实现风险可控的部署。
👍 6
06/22 08:00
Video diffusion models have enabled remarkable progress in video generation and editing. However, content preservation remains a core challenge: existing methods regenerate every pixel and often alter elements that should remain unchanged, such as characters or background scenes. We introduce Vera,
中文介绍 提出Vera,分层扩散模型用于视频编辑,保持内容不变(如角色、背景)。通过分层结构确保仅修改目标区域,避免重新生成整个像素带来的内容损失。
👍 6
06/19 08:00
As agentic systems tackle increasingly complex multi-step tasks, evaluating their trajectories presents a major bottleneck - human annotation of a single trajectory on popular agentic benchmarks can take hours, making it difficult to scale evaluations for measuring performance or curating training d
中文介绍 提出Counsel,智能体任务元评估数据集。针对复杂多步轨迹提供高效评估方案,减轻人工标注瓶颈,支持自动性能度量与训练数据筛选。
👍 5
06/23 08:00
Text-to-image (T2I) generation models have achieved remarkable progress in producing visually realistic images from natural language prompts. Yet it remains unclear whether their success reflects genuine causal understanding or sophisticated pattern matching over visual-textual correlations. Inspire
中文介绍 构建反事实基准,评估文本到图像模型的因果推理能力。发现现有T2I模型依赖视觉-文本相关性而非真正因果理解,揭示其归纳式学习局限。
👍 4
06/17 08:00
Long-context reasoning is an essential capability for large language models, particularly when they are deployed as autonomous agents that must reason over lengthy trajectories. Reinforcement learning (RL) has recently emerged as a dominant paradigm for improving this ability, yet existing work larg
中文介绍 提出面向长上下文强化学习的数据配方,超越传统奖励工程。通过精心设计的训练数据,提升LLM在长篇轨迹推理中的强化学习效果。
👍 4
06/22 08:00
Reconstructing dynamic non-rigid objects from monocular video requires integrating visual cues from direct observations with data-driven priors over geometry and appearance. Prior approaches either learn to directly predict 4D representations from visual input or initialize a 3D representation that
中文介绍 提出Lift4D,从单目视频重建动态非刚体4D表示。融合直接观测与数据驱动先验,实现野外场景下的高质量4D重建。
👍 3
06/22 08:00
Scaling reinforcement learning for visual mathematical reasoning requires more than generating harder questions: as data volume grows, the reward labels themselves must remain reliable. Yet existing data pipelines scale supervision while trusting the labeller, and policy-side methods assume the unde
中文介绍 提出VeriEvol,通过可验证进化指令扩展多模态数学推理的强化学习。在生成更难问题的同时保证奖励标签可靠性,提升视觉数学推理能力。