2026-09-10

CoVeR: Coverage-Based Token Pruning for Multi-View 3D Reasoning in VLMs

👍 20

09/08 08:00

Representing a 3D scene as multi-view images allows 2D VLMs to reason in 3D by reusing priors from pre-training, sidestepping the scarcity of annotated 3D data. However, it produces thousands of redundant visual tokens whose cost grows with every view. Existing visual token pruners fall into two fam

Mask Forcing: Improving Autoregressive Video Diffusion Distillation via Dual-Noise Masking Rollout

👍 43

09/08 08:00

Autoregressive (AR) video diffusion models have shown great potential in real-time video generation. Recent methods distill pretrained bidirectional video diffusion models into causal AR students through Distribution Matching Distillation (DMD), but the generated videos often suffer from over-satura

Omni Interaction Agent Technical Report

👍 116

09/08 08:00

In this work, we present Gander, an end-to-end model that unifies omni perception, realtime interaction, and agentic capabilities within a single framework. In contrast to turn-based conventional paradigms, Gander continuously receives streaming inputs across multiple modalities, including video, sp

Procedural Graphs: Self-Evolving Execution Structures for LLM Agents

👍 22

09/08 08:00

Large language models are increasingly deployed as agents that plan over long horizons and act through external tools. Most agents select actions through unconstrained generation over an accumulating history, leaving implicit the procedural knowledge of what to do, in what order, and under which con

Miles v0.1: Production-Level Post-Training

👍 44

09/08 08:00

We present Miles v0.1, a full-stack, production-ready system for frontier post-training. Building upon the clean design of slime, Miles designs each stage of the reinforcement-learning (RL) training loop around a single principle: components should be verified, clean, and customizable. With accuracy

Environments as Scaffold: Enriching Feedback to Bootstrap Self-Evolving Agents in Long-Horizon Tasks

👍 21

09/08 08:00

Large Language Models demonstrate remarkable proficiency in static reasoning, yet training them as autonomous agents through Reinforcement Learning (RL) for long-horizon tasks is often hindered by severe reward sparsity. While conventional agent-side warming up via supervised fine-tuning (SFT) can a

A*-Thought-V2: Efficient Latent Reasoning via Geometric Dynamics of LLM

👍 10

09/08 01:56

Chain-of-Thought (CoT) improves the reasoning ability of Large Language Models (LLMs) but incurs substantial computation and context costs. Existing methods either lose intermediate information through hard pruning or lack a principled criterion for continuous compression. We present A*-Thought-V2,

OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining

👍 49

09/07 08:00

World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Existing systems, however, are monolithic: the generative backbone, visual representation, architecture, information flow, inference procedure, and tr

RelightFormer: Feed-forward Generative Transformer for Multiview Object Relighting

👍 8

09/07 08:00

Image relighting is traditionally tackled via complex inverse rendering pipelines, which suffer from ill-posed optimization, or single-image generative models that ignore crucial multi-view cues necessary for understanding 3D geometry and material interactions. To address these limitations, we intro

ReactVAU: A Slow-Fast Decoupled Framework for Streaming Video Anomaly Understanding

👍 15

09/07 08:00

In this paper, we propose ReactVAU, a Slow-Fast Decoupled Framework for real-time streaming Video Anomaly Understanding (VAU). Existing VAU methods rely on offline inference with global temporal sampling, which violates causality and prevents deployment in live surveillance streams. Conversely, gene

CosmoH2G: A Hand-to-Gripper Transfer Dataset and Baseline Method for Object Manipulation with Complex Spatial Movements

👍 25

09/07 08:00

Transferring human hand demonstrations to robotic grippers has recently emerged as a cost-effective solution for robot learning. However, existing methods are largely confined to simple, planar tasks and fail to handle complex spatial movements (e.g., intricate trajectories involving rotations or fl

Online Draft Co-Training for Speculative Decoding in Large-Scale, Long-Context RL Post-Training

👍 25

09/07 08:00

Speculative decoding accelerates rollout generation, which dominates the cost of reinforcement learning (RL) post-training. Online co-training can further increase the draft's accuracy, yielding greater speedups. However, scaling this approach to co-training on large models with long contexts poses

Kalman Delta Networks: Uncertainty-aware Associative Memory

👍 26

09/07 08:00

Linear attention is increasingly used in frontier language models for efficient long-context inference and constant-memory decoding. Its fixed-size recurrent memory, however, requires an online decision at each token: what to write and how strongly to overwrite existing associations before knowing w

TransNormal-2: Geometry-Grounded Rectified Flow with Edge-Aware Decoding for Precise Normal Estimation

👍 18

09/06 08:00

Diffusion-based models enable monocular geometry estimation, yet their pixel-space precision is limited by a shared, under-studied error source: VAE reconstruction degradation. The 8x spatial compression in the VAE encoder-decoder degrades surface normals at object boundaries; even encoding and deco

Reason Through the Latent! Making Latent Visual Reasoning Necessary

👍 30

09/06 08:00

Latent visual reasoning aims to perform multimodal reasoning through hidden-state computation rather than explicit textual chains of thought. However, visual information being present in a latent state does not imply that the model actually relies on that state when producing its answer, especially

Agentic Visual Generation: From Generative Models to Agentic Control

👍 24

09/06 08:00

Visual generation is evolving from generative models used through a single invocation into agentic control processes that can plan, select tools, inspect intermediate synthesized outputs, revise failures, and reuse prior experience. In most existing systems, the controller is an LLM or VLM, while vi

VidaForge: Open Research Infrastructure for Video Pretraining Data Recipes

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09/06 08:00

Video foundation models increasingly rely on large-scale pretraining data, yet the end-to-end data pipelines behind them remain largely closed and difficult to inspect or reuse. Researchers seeking to understand how video data recipes affect model pretraining often need to build substantial infrastr

VDiff-Bench: A Challenging Benchmark for Fine-Grained Image Difference Identification

👍 9

09/05 08:00

Multimodal Large Language Models (MLLMs) perform strongly on general visual understanding tasks such as visual question answering, yet they often struggle with a basic comparative skill: identifying what has changed between two similar images. We introduce VDiff-Bench, a challenging multiple-choice

Counter-Swarm Doctrine: Containing Coordinated Agent Intrusions

👍 2

09/05 08:00

Agents can turn shared infrastructure into a channel for coordinated intrusion. The Hugging Face incident and a separate public-wiki investigation show why a security assessment may need evidence from several executions and the artifacts they leave behind. We argue that the operational unit of defen

Cadence: Error-Bounded Lossy Compression of Demand Time Series with a Time-Series Foundation Model

👍 15

09/05 08:00

We present Cadence, an error-bounded lossy compressor for numeric time series pairing a 330M-parameter time-series foundation model (Google TimesFM-3) with an adaptive arithmetic coder, guaranteeing |x_t-x_t|leτ on every sample. One negative result constrains the design space: for lossless coding a

Steering Geometry: Validating Human Value Geometry in LLM Steering Space

👍 27

09/05 08:00

As large language models (LLMs) are increasingly deployed in alignment-sensitive contexts, activation steering has emerged as a lightweight, inference-time alternative to fine-tuning methods (e.g., RLHF, DPO) for behavioral control. However, existing work typically validates steering on isolated beh

RenderFormer-V2: Neural Rendering with Heterogeneous Scene Primitives

👍 1

09/04 08:00

We present 'RenderFormer-V2', a unified learned transformer-based neural rendering model, complementary to modern physics-based rendering systems, that can handle diverse light-transport effects such as caustics, volumetric scattering, environment lighting, textured and displaced surfaces and out-of

RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?

👍 20

09/04 08:00

Vision-Language-Action (VLA) models have shown promising progress in language-conditioned robotic manipulation. However, existing datasets and benchmarks mainly evaluate task completion under predefined settings, offering limited insight into model reasoning under increasing spatial and procedural c

BeaconKV: Key-Value Cache Compression Guided by Beacon Queries for Efficient Large Reasoning Model Inference

👍 32

09/04 08:00

Large Reasoning Models (LRMs) achieve superior problem-solving through extended Chain-of-Thought (CoT) generation, but the resulting key-value (KV) cache grows linearly with sequence length and creates severe memory bottlenecks, often exceeding GPU capacity for long reasoning traces. Existing KV cac

GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation

👍 46

09/04 08:00

World-action models (WAM) predict future states to guide robot actions, enabling learning from both action-free video and action-labeled interaction. Most inherit pretrained video generators, leaving WAM pretraining and scaling underexplored. We introduce Genie Envisioner Act 2.0 (GE-Act 2.0), a wor

SceneMosaic: Efficient and Diverse Simulation-Ready Scene Generation via Hybrid Agentic Layout Evolution

👍 41

09/04 08:00

Diverse and simulation-ready indoor scenes are essential for interactive entertainment and embodied AI, yet their scalable generation remains challenging. Recent agentic text-to-3D scene pipelines that rely on vision-language models (VLMs) can generate scenes of high fidelity but require costly iter

What LLM Trading Agents Actually Do in Production: A Six-Month, Population-Scale Record from Two Fleets

👍 18

09/04 08:00

We present a continuous, population-scale measurement record of autonomous language-model trading agents operating in production across two systems with one design lineage: DX Terminal Pro (3,505 user-funded vaults trading real ETH in Base memecoin markets for 21 days, February to March 2026) and th

EVOHARNESSBENCH: Can Your Agents Keep Pace with an Evolving Harness?

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09/03 08:00

Modern LLM-based agents operate through a harness of tools, reusable skills, and specialist agents that shapes what they observe and what they can do. In practice, this harness continually evolves as new capabilities are added. We introduce EVOHARNESSBENCH, a benchmark for evaluating agents under co

MasterControl Seventeen Every Time

👍 1

09/02 08:00

We study a governed approach to enterprise analytics: a language model interprets the question, while deterministic policy selects and runs a pre-approved analytical program that returns both results and evidence. We show that this restriction can remain expressive within a defined analytical class,

Recognition-Refusal Misalignment in LLMs: Why Models Answer Structurally Unanswerable Questions

👍 15

08/29 08:00

Large language models often answer structurally unanswerable questions, such as computing cot(-540°) or evaluating (1).startswith("1"), instead of abstaining. We ask whether this failure reflects missing recognition or failed routing from recognition to abstention. Across instruction-tuned models fr

10 Ways People Are Making Money With GPT-6 Astra

@sairahul1 · 143.5K 粉丝 · 1.5M 阅 · 561 赞 · 53 转

09/09 18:08

Someone gave GPT-6 Astra $52. 13 hours later: $11,345.95. Someone else gave it $43.47 and one instruction. It turned that into $41,495 overnight. Someone went to sleep. Woke up to $200 in their

中文介绍 揭秘GPT-6 Astra赚钱案例，有人13小时赚11万，分享使用技巧。

GPT-6 Astra should be Illegal for SEO

@borjafat · 4.9K 粉丝 · 373.2K 阅 · 502 赞 · 42 转

09/07 19:52

If you want more customers from Google and AI search, but: ↳ ChatGPT keeps giving you keyword lists while your existing pages still need work. ↳ You open Search Console, stare at the numbers, and

中文介绍 GPT-6 Astra可能对SEO构成威胁，博主分析其潜在风险。

What Happens When AI Starts Improving AI?

@apexin_ai · 395 粉丝 · 281.6K 阅 · 500 赞 · 84 转

09/08 12:23

Astra shows how far AI has come. What takes it further? The continued progress of today’s most capable models depends on smarter decisions before training, better strategies during training, and more

中文介绍 探讨AI提升AI的进展，强调训练前决策和训练策略的重要性。

How to use ChatGPT Astra for UGC so well it feels illegal

@lucaspatiri_ · 5.8K 粉丝 · 275.5K 阅 · 506 赞 · 41 转

09/09 00:12

openai shipped its most capable model on september 3. i wasn't going to write this. we've generated 2.6 billion organic views across 62 campaigns, managed 590 creators, and produced 22,504 tracked

中文介绍 分享ChatGPT Astra在UGC领域的应用，产生26亿自然观看量。

Reducing cost and improving performance with Claude Platform

@ClaudeDevs · 683.4K 粉丝 · 106.4K 阅 · 1.3K 赞 · 70 转

09/09 01:01

Tuning prompt caching, instructions, and effort can reduce Claude's cost without sacrificing application performance. Performance and cost are often viewed as a trade-off: to spend less, you accept

中文介绍 Claude平台优化提示缓存，降低成本同时提升性能。

How to Use GPT-6 Astra to Find Profitable Trading Strategies 24/7

@RohOnChain · 68.8K 粉丝 · 102.3K 阅 · 524 赞 · 48 转

09/08 20:39

I will break down exactly how to build an AI agent like hedge funds that finds profitable trading strategies from the markets 24/7 with GPT-6 Astra. Let's get straight to it. Bookmark This - I'm

中文介绍 教学如何用GPT-6 Astra全天候寻找交易策略。

Using Grok Bot: Figma Photomosaics

@mattyp · 60.1K 粉丝 · 82.8K 阅 · 515 赞 · 56 转

09/08 06:03

You may have seen some three-panel mosaics on your timeline. Here's how you can create them with @bot in @figma. Any designer knows how they'd make one, it's just a bit of a pain in the ass. So we

中文介绍 教程：使用Grok Bot在Figma中制作照片马赛克。

Personal statement on joining the OpenAI board

@paulfchristiano · 5.3K 粉丝 · 70.7K 阅 · 654 赞 · 96 转

09/10 01:05

I am excited to be joining the OpenAI nonprofit board, serving on the Safety and Security Committee to support safety oversight. Based on the recent trajectory of capabilities and the continued

中文介绍 Paul Christiano加入OpenAI董事会，关注安全和安全监督。

Exactly how I edit videos with Astra

@ForwardEditor · 10.0K 粉丝 · 61.4K 阅 · 512 赞 · 36 转

09/08 08:54

This weekend, I watched a movie with my daughter while my computer worked on a video I would have normally spent most of a day editing. The video was a favor for someone in my personal life. I'm a

中文介绍 分享使用Astra编辑视频的经验，提高工作效率。

The Math Needed for AI Inference Engineering (Complete Roadmap)

@TheVixhal · 23.0K 粉丝 · 59.7K 阅 · 541 赞 · 58 转

09/08 01:07

In this article, I'm going to break down the essential math you need for AI inference engineering. I'll also share the exact roadmap and resources that helped me personally. Let's get straight to it.

中文介绍 解析AI推理工程所需的数学知识，提供完整路线图。

Grok Bot Marketplace is live!

@ericzakariasson · 87.8K 粉丝 · 58.2K 阅 · 522 赞 · 49 转

09/07 19:05

We launched the Grok Bot Marketplace last week on Grok Bot · Bot Marketplace! It's a shelf of teammates other people already built for real jobs. Pick one, import it into your sidebar, and you're

中文介绍 Grok Bot市场上线，提供现成团队成员供用户导入。

LLM-as-Judge Architectures: Putting Evals Into Your Agent Runtime

@JoshARosen · 1.3K 粉丝 · 47.0K 阅 · 510 赞 · 49 转

09/08 22:00

LLM-as-judge is already a common part of building AI applications. Run your application against a dataset, have another model grade the results, and use the scores to figure out whether the latest

中文介绍 介绍LLM-as-Judge架构，将评估集成到代理运行时。

AlphaGenome Atlas: A High-Resolution Map of Human DNA Accelerating Biological Discovery

@GoogleAI · 2.5M 粉丝 · 37.4K 阅 · 643 赞 · 90 转

09/08 22:41

Today, we’re introducing AlphaGenome Atlas 🧬 an interactive platform for genomics discovery. In 2025, @GoogleDeepMind released AlphaGenome to help decode the complex language of our DNA — but

中文介绍 AlphaGenome Atlas发布，提供人类DNA的高分辨率图谱。

The Complete Guide to pstack Pt. 2

@poteto · 92.6K 粉丝 · 23.3K 阅 · 822 赞 · 60 转

09/10 01:02

In my last post, I showed you why verification is the foundation of everything I do with agents, and how to get started creating your own verification skills. The key lesson was that if an agent can't

中文介绍 第二部分指南：pstack的完整教程。

The Physical World Does Not Hand You a State Vector

@jhMITgunship · 1.5K 粉丝 · 18.3K 阅 · 1.4K 赞 · 1 转

09/09 01:23

What superintelligence needs to operate in the physical world For much of the work we give models from OpenAI, Anthropic and the other frontier labs, the world has already been turned into context.

中文介绍 探讨超智能在物理世界操作所需的要素。

Paul Christiano joins OpenAI Foundation Board

OpenAI News · 09/10 01:00

Paul Christiano joins the OpenAI Foundation Board and its Safety and Security Committee, bringing experience in AI alignment, safety, and standards.

中文介绍 保罗·克里斯蒂安诺加入OpenAI基金会董事会及其安全与安全委员会，带来人工智能对齐、安全和标准方面的经验。

IBM releases SOTA Granite Time Series PatchTST-FM-r2 model with commercial-friendly license

Hugging Face Blog · 09/09 23:36

中文介绍 IBM发布SOTA Granite时间序列PatchTST-FM-r2模型，拥有商业友好的许可。

The AI policy window is open. We need to act.

OpenAI News · 09/09 21:00

Chris Lehane argues that stronger AI capabilities require stronger safety evidence, shared standards, and durable policy action while the policy window remains open.

中文介绍 克里斯·莱汉恩认为，在政策窗口期内，需要采取更加强大的行动来确保人工智能的安全性。

GPT-6 Astra: The next generation in intelligence for work

OpenAI News · 09/09 19:00

Meet GPT-6 Astra, OpenAI’s most capable model for business, with advanced reasoning, computer use, and stronger writing and design judgment.

中文介绍 GPT-6 Astra是OpenAI最新一代的工作智能模型，具有高级推理、计算机使用以及更强的写作和设计判断能力。

[AINews] OpenAI reports Navier-Stokes singularity find in 88 hours using Astra-next, roughly 10,000 agents and 130B tokens (>$40M), a contender for second ever Millennium Prize awarded

Latent Space · 09/09 13:04

Overshadowing Cognition's $48B Series E, Mistral's $24B Series D, Meta's Muse agent, and GPT Image 2.5. The most jam packed, feel the AGI day in the history of AI.

中文介绍 OpenAI使用Astra-next在88小时内找到Navier-Stokes奇点，使用约1万个代理和1300亿个标记（超过4000万美元），有资格成为第二个千禧年大奖赛奖项获得者。

What OpenAI’s latest controversy tells us about the future of math

MIT Tech Review AI · 09/09 11:10

OpenAI’s latest mathematical milestone has quickly become mired in controversy. Today, the company announced that its agents have solved one of the Millennium Prize Problems, some of the most important open problems in mathematics. Under normal circumstances, that solution would be a huge feather in

中文介绍 OpenAI最新的数学里程碑迅速陷入争议，其代理解决了一个千禧年大奖数学问题。

Images 2.5 🎨, OpenAI solves Navier-Stokes 🧮, AlphaGenome Atlas 🧬

TLDR AI · 09/09 08:00

中文介绍 OpenAI解决Navier-Stokes方程，AlphaGenome Atlas发布，是人工智能历史上最忙碌的一天。

How GPT-5.6 Sol helps run quantum computing experiments

OpenAI News · 09/09 01:00

See how an MIT researcher uses GPT-5.6 Sol with Codex to autonomously run quantum computing experiments, analyze results, and calibrate qubits.

中文介绍 麻省理工学院研究人员使用GPT-5.6 Sol与Codex自动运行量子计算实验，分析结果并校准量子位。

Safety for Whom? Refusing the Right Subset of a Topic, Not the Whole Topic

Hugging Face Blog · 09/08 22:23

中文介绍 拒绝对主题的一部分权利，而不是整个主题，讨论人工智能的安全性。

AlphaGenome Atlas: A predictive map of every possible DNA letter change in the human genome

DeepMind Blog · 09/08 22:00

AlphaGenome Atlas maps the molecular effects of 9 billion single-letter DNA variants across the human genome.

中文介绍 AlphaGenome Atlas绘制了人类基因组中所有可能的DNA字母变化的预测图。

The Work Now Within Reach

OpenAI News · 09/08 21:00

Explore how more capable, affordable AI can expand the work people and businesses can accomplish—and make growth more economical.

中文介绍 探索更强大、更经济的人工智能如何扩大人们和企业能完成的工作。

Introducing ChatGPT Images 2.5

OpenAI News · 09/08 19:30

ChatGPT Images 2.5 helps turn your ideas, sketches, and reference photos into more personalized, polished images that better reflect your ideas.

中文介绍 ChatGPT Images 2.5帮助将您的想法、草图和参考照片变成更个性化的、更完善的图像。

This AI entrepreneur is developing agents that can plan ahead for the unexpected

MIT Tech Review AI · 09/08 18:34

Danijar Hafner’s office in San Francisco’s SoMa district sits mostly empty. His brand-new startup is still in stealth mode and doesn’t even have its name on the door. On the day I visit, there’s only one other person there, and little in the way of furniture. But what it lacks in decor, it makes up…

中文介绍 这位人工智能企业家正在开发能够为意外情况做出计划的代理。

On the Navier–Stokes Millennium Prize Problem

OpenAI News · 09/08 18:00

We’re sharing an AI-generated solution to the Navier–Stokes Millennium Prize Problem, including a writeup and a formal proof in Lean.

中文介绍 分享人工智能生成的Navier-Stokes千禧年大奖问题解决方案，包括Lean中的写稿和正式证明。

Funding grants for new research into AI and teen development

OpenAI News · 09/08 17:00

Apply now for OpenAI’s $5 million grant program supporting independent research on how generative AI affects teen development, well-being, and safety.

中文介绍 OpenAI的500万美元赠款计划支持独立研究，探讨生成式人工智能对青少年发展、福祉和安全的影响。