👍 222
08/04 20:00
High-quality long-horizon training data for terminal agents is expensive to produce, often costing hundreds to thousands of dollars per task, because each task must keep the instruction, environment, reference solution, and verifier mutually consistent. Human authoring does not scale, and direct gen
中文介绍 本研究提出了一种递归合成方法,以生成高质量的长时间任务训练数据,解决了当前任务指令、环境、参考解决方案和验证器之间相互一致性的挑战。通过递归合成,能够以更低的成本产生有效的训练数据,从而提升终端智能体的任务执行能力。意义:此方法对提高Agent在复杂任务中的表现具有重要意义。
👍 84
08/05 20:00
Reinforcement learning (RL) with verifiable rewards constructs trajectory-level advantage estimates, yet it often fails to credit the few pivotal decisions that determine outcomes in long-horizon, multi-turn agentic tasks. Recent work introduces privileged self-distillation for credit assignment, pr
中文介绍 本论文提出了AgentOPSD,一种递归自蒸馏方法,以改善强化学习中对长时间多轮任务的信用分配。通过特权自蒸馏,模型能够更有效地识别关键决策,提高任务成功率。实验表明,这种方法在多种环境中显著提升了任务完成的及时性和准确性。意义:对强化学习领域中Agent的决策能力有重要推动作用。
👍 66
07/29 20:00
Computer-using agents (CUAs) are advancing rapidly across the digital world. A CUA trajectory records the agent's actions, states, and reasoning. Verifying whether it fulfilled the task instruction is central to CUA evaluation, data curation, and reinforcement learning. Neither human-written verifie
中文介绍 OSReward提出了一种标准化的评估框架,用于跨平台计算机使用奖励模型,针对计算机使用代理(CUA)的轨迹及其效果进行验证。该方法为评估CUA提供了一种系统化的标准,提升了数据的可靠性和重用性,助力强化学习的进展。意义:对Agent的评估方法和数据质量有着深远的影响。
👍 64
08/01 20:00
Short segments of perceived speech can be retrieved from non-invasive magnetoencephalographic (MEG) recordings by deep networks trained with a CLIP-style objective against wav2vec 2.0 audio embeddings. Yet their weights do not map onto electrophysiological quantities, and it remains unclear which sp
中文介绍 本研究通过非侵入性脑磁图(MEG)记录和深度网络的CLIP风格目标,成功提取出短段感知语音。研究表明,模型的权重与电生理量不匹配,揭示了刺激特征与脑皮层源之间的复杂关系。意义:这一方法在理解语音与认知过程之间的联系中具有潜在价值。
👍 63
08/04 20:00
Long-horizon search agents must make multiple sequential actions (steps) to search, retrieve, verify, and integrate evidence to reach a final answer. However, existing methods for training these agents typically treat all steps within a trajectory uniformly during both supervised fine-tuning (SFT) a
中文介绍 ABSeeker提出了一种新的训练方法,通过回答回溯信用分配来训练长时间搜索智能体。该方法强调了在执行复杂任务过程中对每个步骤的区分处理,以提高最终答案的准确性和任务执行效率。意义:这一创新方法对长时间搜索任务中的Agent智能化训练具有重要意义。
👍 57
08/04 20:00
Generating large-scale, freely explorable 3D worlds from open-ended text remains challenging because a system must jointly maintain global spatial coherence, rich local content, and explicit assets suitable for downstream editing and reuse. We present WorldClaw, a fully agentic, coarse-to-fine frame
中文介绍 WorldClaw是一个新颖的3D开放世界生成系统,通过文本描述生成可探索的3D环境。该系统能够同时保持全局空间一致性和丰富的局部内容,支持下游编辑和重用。实验结果表明,其生成的环境在可用性和多样性上达到了显著的突破。意义:在自动化生成和交互式应用中具有广泛应用潜力。
👍 42
08/05 20:00
Spatial intelligence is fundamental to embodied agents, yet existing benchmarks focus on local spatial perception from single or few viewpoints, overlooking global spatial awareness over continuous, long-horizon visual streams. To address this limitation, we introduce the Global-Spatial-Temporal Ben
中文介绍 GST-Bench引入了针对视频的全球空间时间基准,旨在评估智能体的空间智能。该基准专注于长期视觉流的全球空间感知,填补了现有基准只关注局部感知的空白。初步结果表明,模型在空间理解方面的能力得到了显著提升。意义:对于智能体在复杂环境下的行为决策具有重要的研究效果。
👍 39
08/05 20:00
Training large language model agents for long-horizon tool use typically relies on interactions with real or synthesized executable environments, whose construction and verification are costly, or on external simulators that are difficult to ground. We introduce EnvACE, an agentic reinforcement lear
中文介绍 EnvACE引入了一种新的强化学习方法,通过世界排练实现环境动态的内化,针对大型语言模型代理的长时间工具使用进行优化。实验显示,该方法在不同环境中的学习效率得到了显著提升,降低了构建和验证环境的成本。意义:对Agent在复杂任务中的适应性和效率提升具有重要影响。
👍 37
08/05 20:00
Unified multimodal retrieval aims to identify candidates that satisfy complex user intent expressed through heterogeneous inputs. Although Large Vision-Language Model (LVLM)-based retrievers are efficient and scalable, directly encoding raw multimodal inputs often misses fine-grained discriminative
中文介绍 本研究提出了一种以检索为中心的链式推理方法,通过困难负样本提高统一多模态检索的准确性。实验结果表明,采用此方法能够提高检索候选的精确性,特别是在处理复杂用户意图时的表现。意义:对多模态检索领域有深远的应用价值。
👍 36
08/05 20:00
Multimodal large language models excel at passive perception but struggle with complex visual cognitive tasks requiring multi-step temporal reasoning. This degradation largely stems from the inherent ambiguity of language-based reasoning, which often fails to accurately articulate continuous visual
中文介绍 ChronoVision通过潜在状态重建技术,解决了多模态大语言模型在时间推理任务中的不足。研究表明,该方法显著提高了模型在多步骤时间推理任务中的性能,克服了语言基础推理中的模糊性。意义:对复杂时间关联任务中智能体的推理能力提升具有重要意义。
👍 33
08/05 20:00
As LLMs are increasingly deployed within agentic systems, their capabilities depend not only on the model weights but also on the harness: the prompts, tools, control flow, memory, and orchestration code surrounding them. This makes automated harness optimization -- the iterative and evaluation-guid
中文介绍 HarnessOpt-Bench提出了一种评估LLM的框架,专注于优化智能代理系统中的提示、工具和控制流。通过迭代评估和优化,能够显著提高模型在实际应用中的效果和稳定性。意义:为Agent的高效利用和增强LLM在复杂环境中的表现提供了新思路。
👍 32
08/05 20:00
Economic World Models (EWMs) are generative economic models that simulate how economies evolve from within by modeling heterogeneous agents, their beliefs and actions, and the market and institutional mechanisms through which their interactions produce aggregate outcomes. This paper develops an impl
中文介绍 本研究开发了一种经济世界模型(EWM),旨在模拟经济体的演变,通过多样性代理、信念及行为演示市场机制的作用。该模型展示了复杂经济交互如何影响宏观经济结果,对理解经济动态提供了新的视角。意义:对经济模拟及相应政策制定具有重要启示。
👍 30
08/03 20:00
Data agents enable natural-language analytics over organizational workspaces, where relevant evidence may be scattered across databases, structured files, long documents, and multimedia. Existing benchmarks largely isolate structured querying, retrieval, or open-ended analysis, leaving heterogeneous
中文介绍 DataSpace建立了针对异构工作空间的可验证分析数据代理基准,支持自然语言分析并对分散的数据进行整合。研究显著提升了不同数据源之间的兼容性和有效分析能力。意义:对数据整合和分析方法的发展具有重要推动作用。
👍 29
08/04 20:00
Modern Greek is absent from NVIDIA's Nemotron retrieval models and from major multilingual retrieval benchmarks, despite being important for retrieval-augmented generation (RAG) in legal, energy, financial, and medical applications. We present an end-to-end adaptation of the Nemotron retrieval stack
中文介绍 本研究针对现代希腊语的检索增强生成(RAG)应用,提出了Nemotron检索模型的全链条适应性方案,使其能够在法律、能源、金融和医疗领域有效发挥作用。结果显示,该模型在多个专业领域的检索效果显著提升。意义:对多语种检索和生成任务的普适性扩展有着深远影响。
👍 28
08/05 20:00
On-Policy Distillation (OPD) is emerging as a promising alternative to reinforcement learning for LLM post-training, yet its effectiveness in multilingual settings remains underexplored. We study OPD and its advanced variant, On-Policy Delta Distillation (OPD^2), for mathematical reasoning in Englis
中文介绍 On-Policy Delta Distillation(OPD^2)拓展了政策蒸馏在多语种数学推理中的应用,研究其在强化学习中的有效性。该方法能显著提高语言模型在数学推理任务中的表现。意义:为多语种和数学问题解决提供了新的思路和潜能。
👍 24
08/03 20:00
Agent self-evolution updates an agent's persistent state from prior experience and reuses it to solve related tasks more effectively. Evaluating self-evolution is difficult: existing benchmarks provide limited coverage of economically valuable task domains, do not always design training and test tas
中文介绍 GDPevo探讨了代理自我进化在真实商业任务中的评估问题,针对经济相关任务设计了全面的评估基准。结果显示,采用这种方法能有效提升代理在相关任务中的表现,弥补了现有基准的不足。意义:对代理智能体的自我学习与执行能力提升具有重要启示。
👍 23
08/05 20:00
Computer-use agents pay full frontier inference to re-derive routines their user has already performed, because an agent's memory today records what the user said, not what the user did. We compile passively captured screen activity into agent memory with a deterministic, zero-model pipeline: it seg
中文介绍 Activity Frames提出了一种编译被动捕获的屏幕活动的方法,使计算机使用代理的记忆更加高效。该方法通过确定性零模型管道,显著提升了代理的记忆和回放能力,解决了以往模型对用户行为重构的不足。意义:对Agent在用户行为理解和执行中的表现具有关键性推动。
👍 23
08/04 20:00
Understanding 3D scenes is fundamental to embodied intelligence, requiring joint reasoning over heterogeneous information from multiple modalities, including visual and geometric cues. However, the relevance of these modalities often varies across queries. Existing Multimodal Large Language Models (
中文介绍 SmartMage提出了一种动态模态协调方法,以提升3D场景理解能力。研究表明,针对不同查询类型选择相关模态信息,能够显著提高多模态大语言模型在复杂场景中的表现。意义:对3D场景智能体的交互和决策支持具有重要价值。
👍 21
08/05 20:00
End-to-end document parsers provide a unified interface, but serialize page layouts and regional contents into one autoregressive sequence. This formulation forces independent regions onto a decoding path whose length grows with the total content, whereas crop-based two-stage parsers expose region-l
中文介绍 PaDoc提出了一种基于布局的并行解码方法,以优化文档解析过程。相较于传统的串行解码,该方法更有效地处理区域内容,能够提升文档解析的精确性和效率。意义:对文档智能处理和解析技术的发展具有重要影响。
👍 21
08/05 20:00
Training terminal agents requires executable and verifiable tasks that are not merely solvable, but appropriately challenging for learning. Executable validation establishes feasibility, yet does not reveal how a task behaves relative to a given solver setting. In this paper, we present CalibForge,
中文介绍 CalibForge提出了一种对抗性求解器校准方案,以提升可学习终端任务的可扩展性。该方法通过建立可执行任务的验证机制,确保了任务在学习过程中的适当挑战性,从而提高智能体的学习效果。意义:对智能体在解决复杂任务时的能力提升具有重要意义。