👍 105
06/23 08:00
Memory for large language model (LLM) agents has rapidly evolved from simple retrieval-augmented mechanisms into a data management system that supports persistent information storage, retrieval, update, consolidation, and dynamic lifecycle governance throughout agent execution. Despite this evolutio
中文介绍 探讨LLM智能体记忆系统从检索增强到原生数据管理系统的演进,实现持久存储、检索、更新、整合与动态生命周期治理,为构建智能体原生记忆奠定基础。
👍 50
06/25 08:00
Modern Vision-Language-Action (VLA) models often fail to generalize to novel setups, such as altered camera viewpoints or robot morphologies, because they are typically conditioned only on current observations and language instructions. By ignoring the underlying system configuration as a variable,
中文介绍 提出上下文世界建模方法,将系统配置作为变量纳入Vision-Language-Action模型,使机器人控制能泛化到新颖视角与形态,无需重新训练。
👍 46
06/25 08:00
Outcome-based reinforcement learning provides a stable optimization backbone for language agents, but its sparse trajectory-level rewards provide little guidance on which intermediate decisions should be reinforced or suppressed. On-policy self-distillation offers dense token-level supervision, yet
中文介绍 提出OPID同策略技能蒸馏,结合结果强化学习与自蒸馏,在稀疏轨迹奖励中注入密集token级监督,提升语言智能体训练稳定性与性能。
👍 45
06/24 08:00
Real-world photography requires capture-time guidance for both camera framing and subject pose. Yet existing aesthetic cropping benchmarks mainly evaluate post-hoc crop prediction and overlook subject-side recommendations, leaving the capture-time guidance capabilities of multimodal large language m
中文介绍 提出ShutterMuse,利用多模态大语言模型在拍摄时提供构图与主体姿态指导,弥补现有基准仅评估后期裁剪的不足,验证MLLM在实时摄影引导中的能力。
👍 42
06/25 08:00
While text-to-image (T2I) models have achieved remarkable progress, they struggle with real-world requests that are often underspecified, implicit, or dependent on up-to-date knowledge. We identify this challenge as the Context Gap: the mismatch between the user context and the sufficient generation
中文介绍 提出Qwen-Image-Agent,通过智能体框架弥合用户上下文与生成条件之间的差距,处理隐含、依赖最新知识的真实图像生成请求,提升T2I模型在复杂场景下的表现。
👍 41
06/24 08:00
A classical intuition holds that verifying a solution is easier than producing one. For today's coding agents, this intuition is being inverted: as foundation models develop stronger reasoning capabilities and engineering harnesses grow more sophisticated, generating complex candidate solutions is n
中文介绍 揭示编程智能体面临验证瓶颈:生成复杂代码越来越容易,但验证正确性反而更难,分析现有奖励机制局限,指出无银弹解决方案。
👍 38
06/25 08:00
A unified representation for text and vision is a natural pursuit, as it enables simpler multimodal modeling and more efficient training. However, representing images as discrete signals in the same way as text inevitably introduces severe information loss. Existing work struggles to balance low-lev
中文介绍 提出ViQ,实现文本对齐的任意分辨率视觉量化表示,在保持低层次细节的同时对齐语义,平衡信息损失与多模态建模效率。
👍 34
06/24 08:00
Synthesizing a novel-view video from a monocular reference video along a target camera trajectory requires both geometric consistency and motion fidelity with respect to the reference video. Existing methods based on explicit 3D representations are limited by the accuracy of off-the-shelf reconstruc
中文介绍 提出MVTrack4Gen,利用多视角点跟踪提供几何监督,从单目视频生成新视角4D视频,无需显式3D重建,保持几何一致性与运动保真度。
👍 31
06/25 08:00
Speculative decoding (SD) accelerates autoregressive Large Language Models (LLMs) by drafting multiple tokens and verifying them in parallel, but it faces a scaling limitation: increasing the draft budget improves speed only when acceptance remains high and drafting overhead stays low. This ceiling
中文介绍 提出JetSpec,采用并行树草稿策略突破推测解码的扩展天花板,在保持高接受率与低开销的同时大幅提升生成速度。
👍 28
06/22 08:00
Computer-use agents can execute software tasks through either graphical interfaces or programmatic command interfaces, but existing evaluations confound interaction modality with differences in tasks, initial states, verifiers, and permitted actions. We introduce a matched execution-layer benchmark
中文介绍 构建匹配执行层基准,系统比较图形界面与命令行界面在计算机使用智能体中的执行瓶颈,揭示不同交互模态的优劣与适用场景。
👍 26
06/24 08:00
Fine-grained visual reasoning requires multimodal large language models (MLLMs) to identify task-relevant visual evidence and ground their reasoning in local image regions. Existing agentic methods typically rely on reinforcement learning with verifiable rewards or supervised fine-tuning on large-sc
中文介绍 提出V-Zero,无需答案标签,通过同策略蒸馏与对比证据门控,使多模态大语言模型在细粒度视觉推理中定位局部图像证据,提升推理可解释性与准确性。
👍 24
06/19 08:00
Generating a coherent multi-shot video requires structured cross-shot memory. Subject appearance, scene context, and speaker identity must persist across cuts. Existing approaches either train end-to-end over fixed-length sequences and cannot scale, generate shot-by-shot with memory banks that grow
中文介绍 提出UnityShots,基于边界感知门控的记忆驱动方案,实现多镜头音频-视频连贯生成,保持主题外观、场景上下文与说话者身份在镜头切换中的一致性。
👍 23
06/24 08:00
Joint-Embedding Predictive Architectures (JEPAs), including recent LeWorldModel (LeWM), have become a promising foundation for reconstruction-free visual world models. For visual planning, however, LeWM evaluates candidate action sequences by repeatedly applying a local one-step latent transition mo
中文介绍 提出Fast LeWorldModel,加速联合嵌入预测架构中的视觉规划,通过并行化单步潜变量转移评估,提升决策效率而不牺牲重建质量。
👍 17
06/25 08:00
As agentic systems continue to evolve and are widely deployed in real-world scenarios, there is a growing demand to faithfully evaluate their capabilities. However, current benchmarks are typically built on popular applications with relatively simple tasks and focus on a narrow set of capabilities w
中文介绍 构建严苛评测基准,全面评估智能体在陌生环境中的能力,覆盖复杂任务与多维度指标,揭示现有系统泛化短板。
👍 16
06/24 08:00
Tool use enables large language models (LLMs) to perform complex tasks, and recent agentic reinforcement learning (RL) methods show promise for enhancing model capabilities. However, RL alone often leads to instability or limited gains in tool-use tasks. In our experiments, some models exhibit catas
中文介绍 分析多步工具使用强化学习崩溃原因(稀疏奖励、策略退化),提出引入监督信号稳定训练,避免灾难性遗忘,提升LLM工具使用能力。
👍 13
06/25 08:00
The prevalent dual-branch paradigm, i.e., training a side network to encode visual conditions and fusing its intermediate-layer features to a frozen pretrained main network, has shown remarkable success in visual-condition controllable generation. Despite its widespread adoption, the role of the sid
中文介绍 提出LISA似然分数对齐,重新审视双分支可控生成中侧网络的作用,通过对齐主网络与侧网络的似然分布,提升视觉条件生成效果,无需复杂训练。
👍 13
06/24 08:00
We introduce Autodata, a general method that enables AI agents to act as data scientists who build high quality training and evaluation data. We show how to train (meta-optimize) such a data scientist agent, so that it learns to create even stronger data. We describe the overall formulation, and a s
中文介绍 提出Autodata方法,训练AI智能体扮演数据科学家自主生成高质量合成训练与评估数据,通过元优化使智能体学会创造更强数据。
👍 9
06/25 08:00
Reasoning capability has advanced rapidly in large language models (LLMs), leading to an increasing size of key-value (KV) cache in both prefilling and decoding stages. Existing KV cache compression methods mainly rely on attention weights to estimate token importance. While attention effectively ca
中文介绍 提出信息感知KV缓存压缩方法,不仅依赖注意力权重,还结合信息论指标评估token重要性,在长推理场景中高效压缩缓存,降低显存占用而不损失性能。
👍 9
06/25 08:00
Video reasoning language models implicitly assume that every input frame is equally reliable. This leads to what we term the Blind Trust Problem: under realistic perturbations such as motion blur, glare, or occlusion, frontier video reasoning models can suffer 15-30%p accuracy drops on real-world em
中文介绍 提出置信度感知工具编排,解决视频理解中的盲目信任问题:在运动模糊、遮挡等扰动下动态选择可靠帧与工具,恢复15-30%的准确率下降,提升鲁棒性。
👍 9
06/25 08:00
We present PhysiFormer, a diffusion transformer for physically-plausible 3D object motion. Unlike video world models that operate in view-dependent pixel space, PhysiFormer represents objects as 3D meshes expressed in world coordinates. Given the initial vertex positions and velocities, as well as o
中文介绍 提出PhysiFormer,基于扩散Transformer的世界空间物理模拟器,以3D网格表示物体,给定初始顶点位置、速度及物理参数,生成符合力学规律的3D运动轨迹。