👍 218
08/05 08:00
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 针对终端智能体长时程任务训练数据昂贵且难以保证指令、环境、参考解与验证器一致的问题,提出递归合成方法,自动生成高质量长时程任务数据,缓解人工编写不可扩展的瓶颈,降低任务级数据成本。
👍 75
08/06 08:00
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 针对长时程多轮智能体任务中轨迹级优势估计难以对少数关键决策进行信用分配的问题,提出AgentOPSD递归自蒸馏方法,通过递归蒸馏关键决策信号改进智能体强化学习,提升信用分配的准确性。
👍 63
08/05 08:00
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 长时间搜索智能体需通过搜索、检索、验证和整合证据等多步行动得到答案,现有SFT与RL常对所有步骤一视同仁。提出ABSeeker,利用答案回溯进行信用分配,区分关键步骤,提升长时程搜索智能体训练效果。
👍 60
07/30 08:00
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 提出OSReward,为跨平台计算机使用智能体(CUA)的奖励模型建立标准化评测。聚焦CUA轨迹是否完成任务指令的验证问题,覆盖动作、状态与推理,支撑CUA评估、数据筛选和强化学习。
👍 58
08/02 08:00
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 针对深度网络从MEG信号解码语音但权重无法对应电生理量、驱动特征不明确的问题,采用可解释性分析定位皮层来源和关键刺激特征,揭示CLIP式训练结合wav2vec 2.0嵌入所依赖的语音表征。
👍 50
08/05 08:00
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 提出WorldClaw,一个完全智能体化的从粗到细框架,从开放式文本生成大规模可自由探索的3D世界,兼顾全局空间连贯性、丰富局部内容以及可供编辑复用的显式资产。
👍 37
08/06 08:00
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 针对现有空间基准仅评测单或少数视角的局部感知、忽视连续长时程视觉流中全局空间意识的问题,提出GST-Bench,系统评估视频大模型能否发展出全局空间-时间认知能力。
👍 34
08/06 08:00
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 提出EnvACE,通过世界排演(world rehearsal)内化环境动态,用于长时程工具使用智能体的强化学习,减少对真实或合成可执行环境及外部模拟器的依赖,降低构建与验证成本。
👍 33
08/06 08:00
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 多模态大模型在需要多步时间推理的视觉认知任务上表现不佳,源于语言化推理难以准确表达连续视觉过程。提出ChronoVision,通过潜在状态重建进行时间推理,减少语言歧义,提升复杂视觉任务表现。
👍 31
08/06 08:00
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 针对统一多模态检索中直接编码原始输入难以捕捉细粒度判别信息的问题,提出基于硬负样本的检索中心思维链(Retrieval-Centric CoT),让LVLM检索器从失败中学习,提升复杂用户意图下的检索能力。
👍 28
08/06 08:00
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 提出经济世界模型(EWM)的系统蓝图,从经济智能体迈向智能体经济,通过建模异质智能体的信念、行动以及市场与制度机制,生成式模拟经济体从内部演化的过程。
👍 28
08/06 08:00
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 提出HarnessOpt-Bench,评估LLM在智能体系统中对harness(提示、工具、控制流、内存、编排代码)进行自动化优化的能力,指出模型能力不仅取决于权重,还取决于外围编排的迭代优化。
👍 25
08/04 08:00
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 提出DataSpace基准,面向数据库、结构化文件、长文档和多媒体等异构工作空间,评测数据智能体基于自然语言进行可验证分析的能力,弥补现有基准在结构化查询、检索与开放分析上的割裂。
👍 24
08/05 08:00
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 针对现代希腊语在NVIDIA Nemotron检索模型和多语言基准中缺失的问题,端到端适配Nemotron检索栈,包括语料挖掘、检索适配与生成接地,覆盖法律、能源、金融、医疗等专业领域的RAG应用。
👍 24
08/06 08:00
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 研究On-Policy Distillation(OPD)及其高级变体On-Policy Delta Distillation(OPD²)在多语言数学推理中的效果,作为RL后训练的替代方案,检验其在英语等多语言设定下的有效性。
👍 24
08/04 08:00
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 提出GDPevo,面向真实商业任务评估智能体自我进化能力,即从先前经验更新持久状态并复用于相关任务,弥补现有基准在经济价值任务覆盖和训练测试设计上的不足。
👍 18
08/06 08:00
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 针对电脑使用智能体重复推导用户已执行操作而浪费推理的问题,提出Activity Frames,用确定性零模型流水线将被动捕获的屏幕活动编译进智能体记忆,记录用户行为而非言语,支持记忆与回放。
👍 18
08/05 08:00
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 针对3D场景理解中视觉与几何等模态相关性随查询而变化的问题,提出SmartMage,动态编排多模态信息,使多模态大模型按查询选择最相关模态,从而提升3D场景理解能力。
👍 18
08/05 08:00
This technical report presents K-EXAONE 2.0, an open-weight multilingual foundation model developed by LG AI Research as a step in our effort toward global frontier-scale foundation models. Rather than training from scratch, we upcycle K-EXAONE and expand its architecture, yielding a Mixture-of-Expe
中文介绍 介绍LG AI Research开发的开源多语言基础模型K-EXAONE 2.0。采用upcycling策略在已有K-EXAONE基础上扩展架构,得到混合专家(MoE)模型,而非从零训练,向全球前沿规模模型迈进。
👍 16
08/06 08:00
Video object removal must eliminate not only the target object but also its induced effects while maintaining high-fidelity and spatiotemporally coherent restoration. Existing methods mainly learn object-effect correspondences implicitly from predefined effect categories and fixed data distributions
中文介绍 提出EffectLearner,通过世界感知的对象效果推理实现真实世界视频对象移除,在删除目标物体的同时消除其诱发效果,避免依赖预定义效果类别和固定数据分布,保持高保真时空一致修复。