👍 64
07/04 08:00
Optimizer selection for large-scale model training has become a system-level design decision constrained jointly by compute, memory, tuning budget, and task diversity, yet the landscape of over one hundred methods remains fragmented. We therefore present OmniOpt, a unified survey and benchmark cookb
中文介绍 提出OmniOpt,统一梳理超百种优化器,从计算、内存、调优预算与任务多样性角度构建分类学与几何分析,并提供标准化基准评测,为大规模模型训练优化器选择提供系统指导。
👍 62
07/05 08:00
Recent advances in multimodal foundation models and agent systems have driven GUI agents from single-platform task execution toward cross-platform interaction. However, building multi-platform GUI agents remains challenging. On one hand, high-quality and executable cross-platform interaction traject
中文介绍 提出UI-MOPD,一种多平台在线策略蒸馏方法,利用跨平台交互轨迹持续训练GUI智能体,支持多平台任务执行,缓解离线数据与策略漂移问题。
👍 47
07/05 08:00
Research dissemination, turning a paper into a poster, a talk video, and a blog post, is still a manual last mile. Prior automation treats each artifact in isolation that each re-extract the paper from scratch, usually ship one-way renders the author cannot reopen in PowerPoint or Word, and gates qu
中文介绍 提出ResearchStudio-Reel,自动将论文转化为海报、演讲视频和博客文章,支持双向编辑(可回PowerPoint/Word),统一工作流,提高研究传播效率。
👍 46
07/06 08:00
3D reconstruction and generation are commonly tackled by separate paradigms: pixel-based regression for reconstruction, and latent diffusion for generation. Recent works attempt to unify them in latent space, but with notable drawbacks: the diffusion objective is defined on latent features rather th
中文介绍 提出PixWorld,在像素空间统一3D场景重建与生成,克服隐空间扩散目标偏移问题,实现像素级3D重建与生成的全新框架。
👍 31
07/02 08:00
Evaluating embodied robot foundation models remains a critical bottleneck; unlike large language models efficiently assessed via digital benchmarks, robotic policies require slow, costly real-world rollouts limited by hardware and human supervision, which has driven interest in world models as surro
中文介绍 提出GigaWorld-1路线图,构建世界模型作为机器人策略评估的替代环境,降低对真实世界部署的依赖,加速具身基础模型评估。
👍 30
07/06 08:00
Dense spatial perception is essential for physical intelligence, where visual systems are expected to recover structured, metric, and actionable representations from pixel observations. Modern visual foundation models tend to prioritize semantic invariance, often at the expense of detailed spatial u
中文介绍 聚焦密集空间感知,提出面向物理智能的视觉预训练方法,在保持语义不变性的同时恢复结构化、度量化的空间表示,提升细粒度空间感知能力。
👍 24
07/05 08:00
We present Wan-Streamer v0.2, a latency-preserving upgrade of the native-streaming, end-to-end audio-visual interaction model. v0.2 keeps the v0.1 modeling formulation, but raises the interactive output stream from 192x336 to 640x368 while preserving approximately 200 ms model-side signal-to-signal
中文介绍 升级Wan-Streamer至v0.2,保持约200ms模型端端延迟,将交互输出分辨率从192x336提升至640x368,实现高分辨率端到端音视频交互。
👍 18
07/01 08:00
Scientific literature search often requires more than retrieving papers from a single query: users' intents are underspecified, preference-dependent, and evolve through interaction. Existing search agents typically rely on fixed pipelines or implicit language-only reasoning, making their search stra
中文介绍 提出多轮代理式科学文献搜索方法,通过工作流归纳动态响应用户意图演变,突破固定管线限制,提升搜索策略透明性与适应性。
👍 16
07/06 08:00
Key-value (KV) cache growth is a major bottleneck in autoregressive decoding, as memory and bandwidth scale linearly with context length. Existing KV eviction methods often rely on static heuristics or proxy scores, which poorly track future token utility and cause brittle eviction as relevance shif
中文介绍 提出KVpop,基于预测性在线剪枝压缩KV缓存,动态预测未来token效用进行淘汰,克服静态启发式脆弱性,降低长上下文自回归解码内存与带宽开销。
👍 15
07/06 08:00
Multi-vector vision-language retrieval preserves fine-grained visual evidence through maximum-similarity late interaction, but dense image-side tokens make storage and scoring expensive. Existing token compression methods reduce this cost, yet they can remove or collapse object- and region-level evi
中文介绍 探索多向量视觉语言检索中令牌重要性差异,提出保留目标证据的令牌合并方法,在压缩图像侧令牌的同时保留细粒度对象级证据,降低存储与评分成本。
👍 14
07/05 08:00
Diffusion large language models (dLLMs) generate text by iteratively denoising a masked sequence, offering a parallel alternative to autoregressive models, but eliciting strong reasoning through post-training remains difficult: supervised fine-tuning is off-policy and suffers from exposure bias, whi
中文介绍 提出dOPSD,面向扩散语言模型的在线策略自蒸馏方法,在迭代去噪过程中利用在线生成数据进行蒸馏,缓解监督微调的离策略偏差,提升推理能力。
👍 13
07/06 08:00
We introduce the first multiplayer world model for highly dynamic environments governed by complex physical interactions. Whereas single-player world models treat the other agents as part of the environment, ours conditions on the action streams of multiple agents, learning to attribute changes in t
中文介绍 提出首个多玩家交互世界模型,通过表示自编码器对多智能体动作流进行条件建模,学习归因环境变化,适用于复杂物理交互的动态环境。
👍 11
07/06 08:00
Pretraining scaling laws reveal that model capability improves predictably with data and compute. But learning from real world environments after deployment remains far less understood. Analyzing roughly 38,000 hours of agent interaction with the environment across 134 real world tasks, we find, to
中文介绍 通过分析134个真实世界任务中约38000小时智能体交互数据,揭示从真实环境学习的缩放定律,发现能力随数据与计算增长的可预测规律。
👍 11
06/30 08:00
The fast growth of open-source AI infrastructure, from model serving engines and agent platforms to the Model Context Protocol (MCP) ecosystem and the language models themselves, has outpaced the security tooling available to defend it. We present AI-Infra-Guard, an open-source framework that organi
中文介绍 提出AI-Infra-Guard,开源多层级AI智能体红队测试框架,覆盖模型服务引擎、智能体平台、MCP协议及语言模型本身,统一防御AI基础设施安全威胁。
👍 10
07/01 08:00
LLMs are increasingly used to brainstorm research ideas, but existing evaluations mostly judge individual ideas by novelty, feasibility, or expert preference. We instead ask: how far are current LLM-generated ideas from human researchers? To characterize this gap, we build a large-scale evaluation f
中文介绍 构建大规模评估框架,量化LLM生成的研究想法与人类研究者之间的差距,从新颖性、可行性等多维度对比,揭示当前LLM创意能力的边界。
👍 9
07/06 08:00
Scaling pre-training, post-training, and test-time compute have become the central paradigms for improving the capabilities of LLMs. In this work, we identify verification, the ability to determine the correctness of a solution, as a new scaling axis. To unlock this and demonstrate its effectiveness
中文介绍 将验证能力作为新的扩展轴,提出LLM-as-a-Verifier通用验证框架,系统评估并提升LLM对解决方案正确性判定的能力,补充预训练、后训练与测试时计算范式。
👍 9
07/01 08:00
As grounded QA systems are increasingly deployed in AI assistants, accurately attributing generated answers to evidence is critical for user trust and model safety. While unimodal attributions have been explored in depth, the multimodal setting remains relatively under-researched. As a result, we in
中文介绍 提出MultAttnAttrib,无需训练的多模态归因方法,在长文档问答中同时为文本和图像证据提供归因,增强生成答案的可信度与安全性。
👍 7
07/06 08:00
Audio intelligence involves understanding, reasoning about, and generating both audio and speech. In this work, we introduce Nemotron-Labs-Audex-30B-A3B (Audex), a unified audio-text LLM built on Nemotron-Cascade-2-30B-A3B, a strong text-only MoE LLM. Audex adopts a simple unified design with a sing
中文介绍 提出Audex,基于Nemotron-Cascade-2的30B MoE统一音频文本大模型,在不牺牲文本智能的前提下实现音频理解、推理与生成,简化多模态设计。
👍 6
06/30 08:00
Large language models increasingly operate over long contexts, where the KV cache becomes a dominant memory bottleneck: its size grows linearly with sequence length and must be retained throughout decoding, making full GPU caching prohibitively expensive without compression. Existing KV cache compre
中文介绍 提出SeKV,分辨率自适应KV缓存与层次化语义记忆,根据上下文重要性动态调整缓存精度,在保持推理质量的同时显著降低长上下文LLM推理的内存占用。
👍 6
07/03 08:00
Long-horizon behavior prediction aims to infer a user's next action based on a lengthy historical sequence, playing a crucial role in artificial intelligence field. The rise of large language models (LLMs) offers a promising direction for sequential behavior prediction, yet LLMs struggle with latent
中文介绍 提出PraMem,从实际交互数据中提取经验记忆,辅助LLM进行长序列行为预测,通过记忆增强克服隐式意图建模难题,提升预测准确性。