2026-07-19

LongStraw: Long-Context RL Beyond 2M Tokens under a Fixed GPU Budget

👍 172

07/16 08:00

A growing gap separates inference context lengths from RL post-training: inference systems are approaching million-token contexts, while post-training workloads often remain at 256K tokens or below and rely on length generalization at deployment. The gap is especially important for AI agents, whose

中文介绍 提出LongStraw方法，在固定GPU预算下将RL后训练扩展到2M tokens以上，解决推理与训练上下文长度差距，对AI agent长程任务至关重要。

Boogu-Image-0.1: Boosting Open-Source Unified Multimodal Understanding and Generation

👍 125

07/14 08:00

We introduce Boogu-Image-0.1, an open-source unified multimodal understanding and generation model family, comprising Base, Turbo, Edit, and Edit-Turbo variants. It delivers competitive performance in high-quality text-to-image generation, fast inference, instruction-based editing, and bilingual (Ch

中文介绍 提出Boogu-Image-0.1开源统一多模态理解与生成模型族，含Base、Turbo、Edit等变体，在文本到图像生成、快速推理和指令编辑上表现竞争力，支持双语。

VideoChat3: Fully Open Video MLLM for Efficient and Generalist Video Understanding

👍 120

07/16 08:00

Recent advances in video understanding have spanned motion, long video, and streaming interaction, driving this field toward real-world applications. Despite this progress, current open-source models remain limited in several ways. They often struggle to generalize across diverse video types, making

中文介绍 提出VideoChat3，全开放视频MLLM，专注于高效通用视频理解，解决现有开源模型在多样化视频类型上泛化能力不足的问题，推进实际应用。

Ring-Zero: Scaling Zero RL to a Trillion Parameters for Emergent Reasoning

👍 90

07/14 08:00

Reinforcement learning with verifiable rewards without human-annotated data, often referred to as zero RL, has emerged as a powerful paradigm for eliciting chain-of-thought reasoning. However, due to computational constraints, existing studies are largely restricted to small models, leaving the trai

中文介绍 提出Ring-Zero，将无人类标注的强化学习（Zero RL）扩展到万亿参数模型，突破小模型限制，实现涌现式思维链推理。

SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning

👍 82

07/16 08:00

Large language models are increasingly trained as interactive agents for long-horizon tasks involving multi-turn interaction, tool use, and environment feedback. Outcome-based reinforcement learning (RL) provides a practical optimization paradigm, but its sparse trajectory-level rewards offer limite

中文介绍 提出SEED，一种自演化在线策略蒸馏方法，用于agent强化学习，通过将稀疏轨迹奖励转化为密集信号，改进长程多轮交互任务的学习效率。

SearchOS-V1: Towards Robust Open-Domain Information-Seeking Agent Collaboration

👍 58

07/16 08:00

Recent advances in Tool-Integrated Large Language Models have made web search a core capability of information-seeking agents. However, as interaction histories grow, agents increasingly struggle to track task progress. When search attempts fail to yield useful evidence, current single- and multi-ag

中文介绍 提出SearchOS-V1，鲁棒的开放域信息搜索代理协作框架，解决搜索失败任务跟踪问题，通过协作机制提升证据获取能力。

BadWAM: When World-Action Models Dream Right but Act Wrong

👍 44

07/16 08:00

World-action models (WAMs) are emerging as a promising foundation for embodied control: rather than predicting actions alone, they learn representations that couple action generation with future world prediction. This coupling is often viewed as a source of robustness, interpretability, and safety,

中文介绍 揭示世界-动作模型（WAM）中动作生成与未来预测的耦合缺陷：模型预测正确但动作错误，质疑了耦合表征的鲁棒性与安全性。

AgentCompass: A Unified Evaluation Infrastructure for Agent Capabilities

👍 38

07/15 08:00

As Large Language Models (LLMs) evolve into autonomous agents, the need for unified evaluation infrastructure becomes critical. However, current evaluation pipelines remain highly fragmented and tightly coupled, hindering reproducibility and causing redundant engineering. To address this, we introdu

中文介绍 提出AgentCompass，统一agent能力评估基础设施，解决当前评估管线碎片化、耦合度高的问题，提升可重复性并减少冗余工程。

KeyFrame-Compass: Towards Comprehensive Evaluation of Keyframe-Conditioned Video Generation

👍 35

07/15 08:00

Video generation increasingly relies on keyframe-based workflows, where creators specify a sequence of reference images to guide generation. Although recent models support multi-keyframe conditioning, it remains unclear whether they can faithfully reproduce the prescribed keyframes while maintaining

中文介绍 提出KeyFrame-Compass，综合评估关键帧条件视频生成，测试模型能否忠实再现指定关键帧同时保持流畅性，揭示现有模型的局限。

PolicyShiftGuard: Benchmarking and Improving Policy-Adaptive Image Guardrails

👍 35

07/07 08:00

Image guardrails are typically trained and evaluated under a fixed safety policy, implicitly treating safety as an intrinsic property of an image. Real deployments are different: the same image may be allowed in one product, restricted in another, and newly disallowed when a policy boundary changes.

中文介绍 提出PolicyShiftGuard，基准和改善策略自适应的图像护栏，处理同一图像在不同安全策略下的允许性变化，推动动态政策场景下的安全。

MetaView: Monocular Novel View Synthesis with Scale-Aware Implicit Geometry Priors

👍 33

07/13 08:00

Current visual generation models are capable of producing high-quality content, yet they lack a coherent perception of the spatial structure. Existing generative novel view synthesis methods typically introduce explicit geometry priors, which enforce spatial consistency but inherently restrict gener

中文介绍 提出MetaView，单目新视角合成方法，利用尺度感知隐式几何先验，在保证空间一致性的同时不牺牲生成多样性。

MultiRef-Compass: Towards Comprehensive Evaluation of Multi-Reference-to-Audio-Video Generation

👍 31

07/15 08:00

Multi-reference-to-audio-video (MR2AV) generation aims to generate coherent audio-video content conditioned on multiple references and textual instructions. Existing benchmarks mainly focus on text-driven generation, single-reference subject preservation, or isolated audio-video alignment, leaving t

中文介绍 提出MultiRef-Compass，首个多参考到音频-视频生成（MR2AV）的综合评估基准，填补现有基准在条件多样性和联合对齐上的空白。

UniVR: Thinking in Visual Space for Unified Visual Reasoning

👍 28

07/14 08:00

Learning broad world knowledge directly from raw visual data is a fundamental capability of intelligence. We introduce UniVR, the first investigation into simultaneously learning complex reasoning, fine-grained physical dynamics, and long-term planning from pure visual demonstrations. At its core, U

中文介绍 提出UniVR，首次从纯视觉演示中同时学习复杂推理、物理动力学和长期规划，在视觉空间中进行思考，无需文本标注。

Concurrent Image Understanding and Generation: Self-Correcting Coupled Markov Jump Processes

👍 27

07/14 08:00

Human cognition does not separate understanding and generation. A teacher at a whiteboard speaks and draws together, each modality reshapes the other. In this paper, we bring this coupled loop to artificial systems. Masked Diffusion Models (MDMs) are ideally suited to this task, yet existing sampler

中文介绍 提出自纠正耦合马尔可夫跳跃过程，让图像理解与生成同时进行，类似人类教学中言语与绘图的相互塑造，使用掩码扩散模型。

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch

👍 26

07/15 08:00

World Action Models (WAMs) improve robot policy learning by jointly modeling actions and future visual observations, using future scene evolution as dense supervision for physically grounded action generation. However, a common design in existing WAMs is to explicitly generate future videos at infer

中文介绍 提出GigaWorld-Policy-0.5，更快更强的世界-动作模型（WAM），通过AutoResearch自动研究增强，避免显式生成未来视频，提升效率。

Self-Improvements in Modern Agentic Systems: A Survey

👍 23

07/14 08:00

Self-improving autonomous agents are moving from research prototypes to deployed systems. The primary goal is controllable evolution, or adaptation, from experience with minimal or even no human input. This survey frames modern self-improving agents as adaptive systems that convert experience into a

中文介绍 综述现代自主agent的自我改进系统，将系统定义为将经验转化为可控进化的自适应系统，讨论其设计原则与当前进展。

Spectral Rewiring for Exploration, Purification, and Model Merging

👍 22

07/03 08:00

Reinforcement learning has become a standard post-training recipe for large language models, but dense full-parameter updates create two deployment-relevant bottlenecks: suppressed reasoning performance, often reflected by premature saturation of test-time scaling, and interference when consolidatin

中文介绍 提出频谱重连（Spectral Rewiring）方法，用于探索、净化和模型合并，缓解RL后训练中全参数更新导致的推理饱和与干扰问题。

RxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination

👍 21

07/15 08:00

Embodied cognition requires agents to connect high-level task reasoning with the physical states to be achieved. We introduce Hy-Embodied-RxBrain, an embodied cognition foundation model with joint language-visual reasoning and imagination. Unlike vision-language models that emphasize scene understan

中文介绍 提出RxBrain具身认知基础模型，联合语言-视觉推理与想象，连接高层任务推理与物理状态，超越传统视觉语言模型对场景的理解。

Hallo4D: Multi-Modal Hallucination Mitigation for Consistent Spatio-Temporal Generation

👍 18

07/15 08:00

While recent advances in 3D generation have enabled impressive visual synthesis, existing methods often rely on 2D diffusion supervision without explicit mechanisms for geometric consistency, leading to spatial hallucinations such as duplicated structures and misaligned geometry. These issues become

中文介绍 提出Hallo4D，多模态幻觉缓解方法，解决3D生成中的空间幻觉（如重复结构、几何错位），实现一致的时空生成。

Demystifying On-Policy Distillation: Roles, Pathologies, and Regulations

👍 17

07/15 08:00

On-policy distillation (OPD) has become a key paradigm in LLM post-training, yet its training dynamics remain poorly understood. We present a systematic study examining the role, pathologies, and regulations of OPD. We first clarify the role of OPD as an exploration catalyst: it steers the student t

中文介绍 系统研究在线策略蒸馏（OPD）在LLM后训练中的角色、病理和调控机制，揭示其作为探索催化剂的作用及常见病态。

GLM 5.2 With Vision

@part_harry_ · 1.5K 粉丝 · 225.6K 阅 · 503 赞 · 46 转

07/16 12:24

GLM 5.2 is one of the best currently available open source language models. However, unlike other flagship models like Qwen, Kimi and Minimax, GLM 5.2 does not support image inputs. We took this as a

中文介绍 开源模型 GLM 5.2 原本不支持图片输入，博主通过改造使之具备视觉能力，填补与 Qwen、Kimi 等竞品的差距。技术教程类内容。

The Self-Driving Company

@amasad · 472.6K 粉丝 · 223.7K 阅 · 560 赞 · 65 转

07/17 01:07

We are beginning to see what happens when a company learns to operate itself. In the past six months, engineers at Replit have nearly tripled code output. Review times held steady. Reversions and

中文介绍 Replit 工程师在6个月内代码产出几乎翻三倍，评审时间稳定，回滚率下降。博主分享「自驱动公司」现象，关键在于 AI 赋能团队协作效率提升。

The Next Horizon in Agents

@btaylor · 158.6K 粉丝 · 144.3K 阅 · 511 赞 · 40 转

07/16 22:48

Introducing Horizon Today, Sierra is announcing Horizon, a platform that enables agents to pursue long-horizon goals, like originating a loan or getting prior authorization for a healthcare procedure.

中文介绍 Sierra 发布 Horizon 平台，专为 AI Agent 设计以实现长周期目标，如贷款申请或医疗预授权。产品发布类，聚焦 Agent 在复杂流程中的应用。

Gemini API Managed Agents: free tier, triggers & more

@GoogleAIStudio · 186.6K 粉丝 · 111.0K 阅 · 512 赞 · 51 转

07/17 01:05

Today we’re announcing new capabilities for Managed Agents in Gemini API, including free tier availability, budget control guardrails, and scheduled triggers. Building on our previous release of

中文介绍 Gemini API 的 Managed Agents 新增免费层、预算控制护栏和定时触发器。开发工具更新，降低 Agent 使用门槛并增强可控性。

How we built our knowledge base

@cerebras · 60.4K 粉丝 · 70.7K 阅 · 509 赞 · 38 转

07/17 02:27

Authors: @hi_im_isaac_, @learnwdaniel, @gaozenghao note: the interactive version of full technical blog available: https://www.cerebras.ai/blog/how-we-built-our-knowledge-base Employees ask our internal knowledge base more than 15,000

中文介绍 Cerebras 分享构建内部知识库的技术博客，员工每日查询超15,000次。涉及架构设计、交互式演示链接，适合关注企业级 RAG 的读者。

Kimi K3 on KernelBench

@elliotarledge · 40.7K 粉丝 · 69.3K 阅 · 506 赞 · 45 转

07/17 17:24

This is the Kimi K3 post you guys have been waiting for. I got some early access to this model and have been testing it on kernels, and even before seeing the benchmark scores I was impressed with its

中文介绍 博主提前体验 Kimi K3 模型，在 KernelBench 测试中表现令人印象深刻，性能超越预期。模型评测类，关注其在底层计算任务上的能力。

From Loop Engineering to Graph Engineering?

@IntuitMachine · 62.3K 粉丝 · 50.7K 阅 · 552 赞 · 47 转

07/18 18:00

What the shift in AI agent architecture is really about Peter Steinberger just posted nine words that gathered thousands of likes: https://x.com/steipete/status/2078277297791189132 "Are we still talking loops or did we

中文介绍 讨论 AI Agent 架构从「循环工程」转向「图工程」的趋势，引用 Peter Steinberger 的九字流行语。观点分享，引发对 Agent 构建范式变革的思考。

[AINews] not much happened today

Latent Space · 07/18 12:30

a quiet day

中文介绍 当日AI领域消息平淡，无重大事件发生。

Fine-tune video and image models at scale with NVIDIA NeMo Automodel and 🤗 Diffusers

Hugging Face Blog · 07/17 23:57

中文介绍 NVIDIA与Hugging Face联合推出通过NeMo Automodel和🤗 Diffusers大规模微调视频与图像模型的方案。

A scorecard for the AI age

OpenAI News · 07/17 18:00

Sarah Friar, CFO of OpenAI, introduces a practical AI scorecard to measure ROI through useful work, cost per successful task, dependability, and return on compute.

中文介绍 OpenAI首席财务官Sarah Friar提出AI时代记分卡，从有用工作、每次成功任务成本、可靠性和计算回报率等维度衡量AI投资回报率。

The risk of weather data sabotage is rising

MIT Tech Review AI · 07/17 16:57

Every morning, airline dispatchers, grid operators, and farmers around the world make decisions based on the same thing: a weather forecast. While these forecasts are something that most people glance at for two seconds, weather predictions influence major strategic decisions in many industries, wit

中文介绍 MIT Technology Review文章指出，天气数据遭到蓄意破坏的风险上升，全球航空调度、电网运营商和农民依赖天气预报做关键决策，数据安全需警惕。

not much happened today

Smol AI News · 07/17 13:44

**Moonshot's Kimi K3 release** has sparked a reassessment of **Chinese open-weight models**' proximity to the frontier, with strong performance in coding, agentic tasks, and long-horizon knowledge work. The strategic focus has shifted from a "compute moat" to an "efficiency stack" involving **MoE ro

中文介绍 Moonshot AI发布Kimi K3引发业界重新评估中国开源模型的前沿性，其在编程、智能体和长程知识任务中表现强劲，战略重心从算力护城河转向效率堆栈。

[AINews] Kimi K3 2.8T-A50B: the largest open model ever released; Opus 4.8-class at Sonnet 5 pricing

Latent Space · 07/17 09:46

a great week for open models continues.

中文介绍 Kimi K3拥有2.8万亿参数（激活50B），是迄今最大开源模型，性能达Opus 4.8级别，定价与Sonnet 5相当。

Kimi K3 🌕, Gemini 3.5 delayed ⏳, crushing ARC-AGI 3 🤖

TLDR AI · 07/17 08:00

中文介绍 本周AI动态：Kimi K3发布；Gemini 3.5推迟；ARC-AGI 3基准被大幅攻克。

Why teens deserve access to safe AI

OpenAI News · 07/17 00:00

Learn how OpenAI is making ChatGPT safer for teens with age-appropriate protections, learning tools, parental controls, and expert partnerships.

中文介绍 OpenAI阐述为何青少年应获得安全AI访问，通过年龄适宜保护、学习工具、家长控制和专家合作，使ChatGPT对青少年更安全。

🔬 The Lab of the Future Should Feel Like a Data Center — Andy Beam & Rafa Gómez-Bombarelli, Lila Sciences

Latent Space · 07/16 21:30

Lila is betting that science, not the internet, is the last untapped source of training data. We went to find out what that actually looks like in a room full of robots.

中文介绍 Lila Sciences认为科学是最后未开发的训练数据源，其未来实验室应像数据中心一样，充满机器人，将科学转化为AI训练数据。

Newer Models, Same Advantage

Hugging Face Blog · 07/16 19:49

中文介绍 Dharma AI博客指出，新模型在保持原有优势的同时持续进步，并未因迭代而失去既有能力。

Our approach to bioresilience

DeepMind Blog · 07/16 17:30

Google DeepMind and Isomorphic Labs are sharing our joint approach to bioresilience and AI models.

中文介绍 Google DeepMind与Isomorphic Labs公开其生物韧性联合方法，利用AI模型应对生物风险，增强生物防御能力。

[AINews] Thinky's Inkling: 975B-A41B multimodal, new best American Apache 2.0 open model (with Inkling-Small, 276B-A12B)

Latent Space · 07/16 14:18

Thinky's first full LLM release is a banger and bonus: it's open weights!

中文介绍 Thinky发布首个完整大语言模型Inkling（975B参数，激活41B），多模态，采用Apache 2.0开源许可，成为美国最佳开源模型；另有小版本Inkling-Small（276B-A12B）。

not much happened today

Smol AI News · 07/16 13:44

**Moonshot AI** launched **Kimi K3**, a frontier-class open-weights model with **2.8T parameters**, **1M-token context window**, and **native multimodal input**. It features novel **Kimi Delta Attention (KDA)** enabling up to **6.3x faster decoding** and **Attention Residuals** for **~25% higher tra

中文介绍 Moonshot AI发布前沿开源模型Kimi K3，参数2.8T，支持100万token上下文和原生多模态输入，采用Kimi Delta Attention（KDA）技术，解码速度提升至6.3倍。

How Cars24 scales conversations and builds faster with OpenAI

OpenAI News · 07/16 08:00

Cars24 uses OpenAI-powered voice and chat agents to handle 1M+ monthly conversation minutes, recover 12% of lost leads, and bring agentic workflows to teams across the company.

中文介绍 印度二手车平台Cars24利用OpenAI驱动的语音和聊天代理，每月处理超100万分钟对话，挽回12%丢失线索，并在全公司推广智能体工作流。

Security incident disclosure — July 2026

Hugging Face Blog · 07/16 08:00

中文介绍 Hugging Face披露2026年7月发生安全事件，具体细节及影响已在博文中说明。