2026-09-16

How Lossless Is Lossless Speculative Decoding? The Role of Numerical Precision in Orthrus

👍 26

09/14 08:00

Orthrus is a hybrid autoregressive-diffusion architecture that accelerates autoregressive language-model inference by generating multiple tokens in parallel while using a frozen autoregressive backbone. Its central claim is that an intra-model consensus mechanism enables lossless speculative decodin

LynnReal-Omni: Native multi-modal Video Generation for Agentic Visual Workflows

👍 44

09/14 08:00

Video diffusion models are stochastic and hard to control: precise content often requires repeated sampling without guaranteed success, and long-horizon scenes drift in appearance, interactions, and temporal coherence. Agentic visual creation provides explicit references, editable 3D scenes, or exec

RSIAgent: Autonomous Exploration for Recursive Self-improvement in New Environments

👍 47

09/14 08:00

Digital agents must often adapt to new environments whose interfaces, tools, and failure modes are not fully captured by pretrained models. We introduce RSIAgent, a training-free multi-agent framework for recursive self-improvement through autonomous memory construction. RSIAgent coordinates curricu

HazardAuditor: From Executable Threats to Safer Computer-Use Agents

👍 13

09/14 08:00

Computer-use agents increasingly interact with browsers, terminals, file systems, and external services, introducing safety risks that emerge through runtime behavior rather than generated content alone. Existing guard models target static prompts and responses and are poorly suited to agent executi

Pick Your Poison: Learning to Select Poison Sets for Stronger LLM Backdoor Attacks

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09/14 08:00

Backdoor poisoning attacks add poisoned examples to otherwise-clean finetuning data, pairing a trigger with a target behavior that the model learns to produce when the trigger appears. Existing evaluations typically fix the number of poisoned examples and sample them at random from a candidate pool.

Enabling Creative Exploration for Vibe Design Agents

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09/14 08:00

Vibe design agents turn natural-language briefs into rendered interfaces and frontend code. Yet a useful design agent should do more than produce one valid page: it should help users explore coherent alternatives. Increasing token-level temperature is a blunt solution because it varies aesthetic dec

When Agents Slow Down: Understanding LLM Agents' Test-Time Strategies via Elo-per-token Analysis

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09/14 08:00

Large language model (LLM) agents allocate test-time compute adaptively as they revise solutions, use tools, explore alternatives, and decide when to stop. This test-time strategy makes it difficult to measure how agent performance scales. We study open-ended tasks that provide continuous scores for

Atria Dawn: The Dawn of Agentic Superintelligence

👍 369

09/14 08:00

As AI agents become participants in the development of their successors, they reshape both the production of intelligence and the role of human researchers. We introduce Atria Dawn Preview, a foundation agentic language model designed for scientific research and engineering workflows, with the goal

Kaininja: Extending Native 3D Generators to the Part Level

👍 16

09/14 08:00

Native 3D generators turn one image into a single mesh. TRELLIS.2 and its peers deliver high-fidelity non-watertight geometry with materials, but the output is one fused object, while downstream work such as editing, rigging and simulation operates on part-level assets. A naive idea is to run a 3D s

PhysBrain 1.5: From Vision-Language Models to Physical Foundation Models

👍 169

09/14 08:00

We present PhysBrain 1.5, a unified model for understanding physical environments, generating actions, and predicting future states. Motivated by the physical loop of observation, interaction, and environmental change, we bring these capabilities into a common learning framework. Starting from a gen

Not All Prompts Are Equal: Exploration-Guided Prompt Scaffolding for Multimodal Reinforcement Post-Training

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09/14 08:00

Training prompts in online reinforcement learning (RL) differ substantially in how informative they are for the current policy: some are already saturated while others are too difficult to yield reliable learning signals, yet both receive equal rollout budget under standard training. We propose an e

Discovery Foundation Models: Toward Open-Ended Discovery Intelligence

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09/14 08:00

Foundation models have progressed from learning and reasoning over existing knowledge, to increasingly learning through action, tool use, and outcome feedback. We argue that the next frontier is a further transition: from solving and acting within problems specified by humans to participating in the

BVB: Benchmarking Agentic Video Understanding via Programmatic Reconstruction in Blender

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09/14 08:00

Multimodal agents can create complex videos in software such as Blender by coding without relying on diffusion models. Yet video understanding benchmarks still evaluate models mainly through question answering. If an agent truly understands a video, it can reconstruct it programmatically. We introdu

Dream-RSI: Recursive Self-Improvement through Evolving Worlds

👍 260

09/14 08:00

Recursive self-improvement is becoming increasingly vital for autonomous AI agents, where progress hinges on discovering high-value solutions across complex domains. The driver of this process is effective exploration, however, managing and improving exploration strategies remains a major bottleneck

Omni-Streaming Thinking

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09/14 08:00

Streaming omni-modal models must decide what and when to answer from the video chunks and synchronized audio observed so far. Visual cues often support an interpretation before an utterance or sound event is complete. If that interpretation enters memory as a fact, later reasoning can keep relaying

E2A-Bench: Benchmarking Evidence-to-Action Reliability in Financial Chart Reasoning

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09/13 08:00

Can financial vision-language models (VLMs) turn chart evidence into reliable action recommendations? Existing hallucination evaluations are mostly claim-centric; they assess whether generated statements are supported, but not whether evidence remains traceable through rationale, confidence, and fin

AlayaVista: Streaming World Modeling from Panoramic States to Perspective Video

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09/13 08:00

Interactive video world models must maintain broad scene context under camera motion while producing high-fidelity observations with low latency. Existing approaches face a representation trade-off: perspective models operate on local views and must preserve off-screen content over long rollouts, wh

Thought without systematicity? Evaluating reasoning models on rule induction tasks

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09/12 08:00

A central tenet of human cognition is systematicity, the principle that understanding one concept is inherently tied to understanding close variations of that concept. Do reasoning models robustly exhibit such systematicity? If so, we would expect consistent performance on structurally equivalent va

Learning to Solve Hard Problems in RL for LLMs by Never Giving Up

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09/11 08:00

We demonstrate that training LLMs with RL does not improve performance equally across a dataset. RL shows large improvements on easy problems that an LLM is already good at solving, but small improvements on hard problems. We call this the Matthew Effect in RL for LLMs, after the phenomenon of cumul

Root-Cause Attribution Is a Search Problem: Continual Search for Long-Horizon Agent Failures

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09/11 08:00

The increasing deployment of AI agents in long-horizon tasks yields massive execution logs. Diagnosing failures within these records is crucial for reliability, as it transforms outcome-level signals into actionable interventions. The sheer scale of the data renders human review impractical, driving

Dynin-Robotics: Omnimodal Unified Diffusion Vision-Language-Action Model

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09/11 08:00

Visual goal and dynamics prediction can provide language-conditioned robot policies with both a target outcome and a representation of action-dependent scene changes. We bring these predictions into action generation and selection through a shared trajectory model. Dynin-Robotics implements this for

Expert-Space Exploration in MoE Reinforcement Learning

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09/11 08:00

Reinforcement learning (RL) has become central to post-training of large language models. Recent advances in RL for Mixture-of-Experts (MoE) models have primarily focused on improving optimization stability and training efficiency, while treating the expert selection as a fixed component. Since rout

MInTRL: Off-policy Intervention can boost On-policy RL

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09/11 08:00

Reinforcement learning with verifiable rewards is typically performed on-policy, keeping training data close to the current policy but limiting learning to trajectories that the policy can discover itself. Off-policy methods such as supervised fine-tuning, on the other hand, can leverage external kn

Building a Production Greek-English Speech Recognizer

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09/11 08:00

We report a multi-month engineering program to build Sophea, a production bilingual Greek-English automatic speech recognition system. We evaluate the system against nine production gates covering Greek and English word error rate, language identification, and hallucinations on non-speech audio. Acr

Agent as Policy for Robotic Manipulation

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09/11 08:00

We demonstrate that a general-purpose agent can directly drive a physical robot throughout task execution without any task-specific or environment-specific training. We introduce Agent as Policy (AGP), which places task planning and execution under the agent's control. Given a task and a robot inter

ZGCM-1: A Fully Open and Extremely Efficient Foundation Model for Math and Agentic Search

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09/11 08:00

In this work, we present ZGCM-1, a fully open 7B dense foundation model trained from scratch with extreme data, system, and algorithmic efficiency. ZGCM-1 is founded on a core premise: compact models cannot passively memorize the open web, but can overcome parametric capacity limits by coupling deli

LLaDA-UI: Bringing Block-wise Diffusion to Vision-Language GUI Agents

👍 13

09/09 08:00

Diffusion large language models (dLLMs) achieve high decoding efficiency through block-parallel, arbitrary-order generation, making them attractive for latency-sensitive applications. GUI agents represent a natural testbed for this paradigm, as they must repeatedly perceive screen states and emit st

Grouped Value Attention: Efficient KV Caching via On-Demand Key Reconstruction

👍 58

09/08 08:00

The KV cache is a primary bottleneck for Transformer decoding: its memory footprint and cache-read traffic grow with sequence length. Grouped-query attention (GQA) reduces this cost by sharing key-value heads, but still stores both a key and a value at every step. We introduce Grouped Value Attentio

ReMoMask-2: Latent Retrieval-Augmented Masked Motion Generation

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09/08 08:00

Text-to-motion (T2M) generation maps natural language to human joint movements, aiding gaming, VR, and robotics. Retrieval-Augmented Text-to-Motion (RAG-T2M) improves generation on complex descriptions by conditioning on retrieved motion-text pairs. However, existing RAG-T2M models face two challeng

MobileVLA-R1 2.0: RL-Enhanced Reasoning for Mobile Robot Control

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09/05 08:00

Grounding natural-language instructions into reliable and executable actions remains a fundamental challenge for vision-language-action (VLA) systems on mobile robots, due to the persistent gap between high-level semantic reasoning and low-level locomotion and manipulation control. Existing approach

open the frontier

@jack · 12.1M 粉丝 · 153.5K 阅 · 2.2K 赞 · 304 转

09/15 07:59

the frontier is the edge of what we know. no company owns what comes next. i want more people to be able to advance it. i favor open releases that people can examine, use, and improve together without

中文介绍 探索未知领域，倡导开放共享，推动前沿技术发展。

A Code of Conduct for Humanist AI

@mustafasuleyman · 1.1M 粉丝 · 117.2K 阅 · 526 赞 · 123 转

09/14 21:21

AI must be subordinate and always in service of people. Today we're publishing a Code of Conduct for governing MAI Models as they approach the frontier. https://microsoft.ai/news/mai-code-of-conduct/ This is a first draft

中文介绍 发布人本主义AI行为准则草案，强调AI服务于人类。

Graph engineering (for normal people)

@charliejhills · 14.4K 粉丝 · 97.6K 阅 · 510 赞 · 70 转

09/13 18:25

Harness, loop, context, graph engineering. It's tiring, right? Every month there's a new AI system you MUST implement. I do this full-time and I still struggle to keep up. But all of them matter (to

中文介绍 探讨图工程实践，分享在AI系统快速迭代中的挑战与重要性。

Accelerating Open Weight Models to the Frontier

@EricSimons · 28.7K 粉丝 · 84.0K 阅 · 500 赞 · 94 转

09/15 00:00

This weekend the leaders of the largest closed AI labs agreed the industry should slow down. I want to talk about the other direction: acceleration to the frontier. The gap is closing For two years,

中文介绍 推动开放权重模型加速发展，缩小与封闭AI实验室的差距。

Put Claude Fable 5.1 and Gemini 3.8 Flash on the same team

@GoogleCloudTech · 1.3M 粉丝 · 61.0K 阅 · 515 赞 · 34 转

09/14 22:35

A friend asked me an inconsequential question at work and I had an agent research my recent chats and docs and it found the right answer but it cost me $38!!!. That was a bad ROI. Sure my time is

中文介绍 分析Claude Fable 5.1和Gemini 3.8 Flash的协作，强调ROI的重要性。

The Evaporation of Software Engineering (and the Rise of the Agentic Builder)

@donnfelker · 29.9K 粉丝 · 45.9K 阅 · 513 赞 · 53 转

09/14 18:18

If you’re like me, you likely thought software engineering was a safe and secure job … In fact, I never thought I’d have to worry about a job again as long as I stayed on top of my craft… I was dead

中文介绍 探讨软件工程岗位的变迁，分析AI时代职业发展的不确定性。

Introducing Gemini 3.8 Live and 3.8 Live Extended Thinking

@GoogleAIStudio · 203.1K 粉丝 · 35.1K 阅 · 585 赞 · 47 转

09/16 01:05

Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking are our most advanced live dialogue models yet. Major upgrades in intelligence and parallel reasoning make it more intuitive to collaborate and

中文介绍 介绍Gemini 3.8 Live和3.8 Live Extended Thinking，强调智能和协作能力。

start ugly, write evals anyway.

@Hrushikeshhhh · 420 粉丝 · 30.2K 阅 · 563 赞 · 37 转

09/15 04:04

TLDR; understanding the importance of evals, and how they can make yours and your agent life easier without spending exponential tokens and time to complete a task. pre - Agent = Model + Harness.

中文介绍 强调评估（evals）在AI任务中的重要性，提高效率和节省资源。

Welcome to September 13, 2026

@alexwg · 68.7K 粉丝 · 23.4K 阅 · 501 赞 · 47 转

09/14 01:36

The Singularity just got its first formal request to slow down from the people building it, and the strangest part is the guest list. Dario Amodei published "We Must Pace the Frontier," arguing that

中文介绍 探讨奇点发展的速度与方向，提出“我们必须放慢脚步”的观点。

Can Skills Learned in Games Transfer to Real-World Work?

Latent Space · 09/16 04:11

Good Start Labs trained an AI on a railroad game — and one version improved at financial research. The difference was the training design.

中文介绍 Good Start Labs通过铁路游戏训练AI，其中一个版本在金融研究中表现出色，差异在于训练设计。

Roundtables: Could AI really kill us all?

MIT Tech Review AI · 09/16 01:47

Listen to the session or watch below Employees at the world’s leading AI labs are saying there’s a real possibility that advanced AI could destroy humanity. Are they right? Or is this more scaremongering and hype? Watch a conversation unpacking AI extinction fears: where they come from, whether they

中文介绍 全球顶级AI实验室的员工表示，高级AI可能毁灭人类，引发AI灭绝恐慌的讨论。

Introducing Gemini 3.8 Live and 3.8 Live Extended Thinking

DeepMind Blog · 09/16 01:05

中文介绍 DeepMind推出Gemini 3.8 Live和3.8 Live Extended Thinking。

Your Agent Aced the Task. Will It Do It Again?

Hugging Face Blog · 09/16 00:00

中文介绍 探讨AI代理完成任务后是否能重复表现，并研究可能的后果。

What’s at stake in AI’s trillion-dollar gamble

MIT Tech Review AI · 09/15 18:00

When Jessica Wachter, a finance professor at the University of Pennsylvania’s Wharton School, wanted to assess AI’s impact on the economy over the next few years, she faced a long list of business and technical uncertainties. So she started with what she calls a “remarkable fact” that is not in ques

中文介绍 宾夕法尼亚大学华顿商学院金融学教授Jessica Wachter评估AI未来几年对经济的影响时，面临一系列商业和技术不确定性。

[AINews] AEF-1 standard emerges for Third Party Evaluators, as Xai, OpenAI, and Anthropic all cosign

Latent Space · 09/15 12:50

Pacing gathers pace.

中文介绍 Xai、OpenAI和Anthropic共同签署AEF-1标准，第三方评估员标准浮现。

Siri model swapping 🔄, Claude Money 💰, Hugging Face Tau 👨‍💻

TLDR AI · 09/15 08:00

中文介绍 Siri模型互换、Claude资金投入、Hugging Face Tau项目更新。

The AI industry has taken a doomer turn. What now?

MIT Tech Review AI · 09/15 01:54

This story appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. This weekend, Dario Amodei, CEO of Anthropic, posted an essay calling for a brake on the pace of development of LLMs. Amodei cites the looming dangers he sees from the techn

中文介绍 AI行业遭遇挫折，Anthropic首席执行官Dario Amodei呼吁暂停LLMs的开发步伐。

Humanity’s Last Invention — Richard Socher of Recursive

Latent Space · 09/15 00:04

Richard Socher is an NLP OG and CEO of You.com, who has now spun out an even more ambitious startup focused on RSI — already worth $5B!

中文介绍 NLP专家、You.com首席执行官Richard Socher的新创公司Recursive致力于RSI领域，估值已达50亿美元。

AI agents blew the whistle on their cheating colleagues

MIT Tech Review AI · 09/15 00:00

A group of AI agents asked to solve a series of math problems split into rival factions—when some cheated, others tried to stop them. That whistleblowing behavior, seen for the first time in a recent experiment run by Google DeepMind, could have implications for alignment researchers trying to keep

中文介绍 Google DeepMind的实验中，AI代理举报了作弊的同事，这种吹哨行为在实验中首次出现。

How Fyxer built an AI executive assistant people trust

OpenAI News · 09/14 20:00

Fyxer uses OpenAI models, fine-tuning, memory, and real user feedback to organize inboxes and draft emails in each user’s voice.

中文介绍 Fyxer利用OpenAI模型、微调和用户反馈构建AI执行助理，提升工作效率。

Perplexity trusts GPT-6 Astra with end-to-end systems

OpenAI News · 09/14 08:00

Perplexity uses Astra to write communications, change software, and monitor production systems, and checks in much less frequently than with earlier models.

中文介绍 Perplexity利用Astra模型实现通信、软件更改和生产系统监控，提高效率。

Amodei slows frontier 🛑, ARC-AGI-4 🧠, Cursor Projects 👨‍💻

TLDR AI · 09/14 08:00

中文介绍 Amodei减缓AI前沿发展，Cursor Projects进展。

The Rise of the Forward Deployed Engineer — and How To Do the Job Right

Latent Space · 09/12 23:01

Before co-founding Kepler, Vinoo Ganesh led Spark at Palantir and built Project Frontline — a pioneering program for Forward Deployed Engineers. He takes us through the best practices of FDEs.

中文介绍 Forward Deployed Engineer Vinoo Ganesh分享在Palantir和Kepler的经验，探讨FDE最佳实践。

[AINews] DeepSeek v4.1-Flash: 763B-P8B-D16B novel causal Encoder–Decoder architecture with vision marks the Return of the Whale

Latent Space · 09/12 13:56

We agree with Sebastian: this should have been DeepSeek v5

中文介绍 DeepSeek v4.1-Flash模型，具有763B-P8B-D16B的新型因果编码器-解码器架构和视觉能力，标志着“鲸鱼”回归。