2026-09-27

RGBD20K: A Large-Scale Benchmark for RGB-D Semantic Segmentation

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09/24 08:00

In this paper, we propose RGBD20K, a novel dataset for facilitating the development of more robust and general RGB-D semantic segmentation by encompassing abundant categories and high-quality annotations. RGBD20K possesses several attractive properties: (1) Expanded Semantic Space. In particular, it

Your Transformer Can Hold Two Thoughts at Once: Evidence of Linear Superposition in LLMs

👍 64

09/24 08:00

While Large Language Models (LLMs) rely on highly non-linear components, in this work we demonstrate that they exhibit fundamental linearity: when inputs from distinct text streams are linearly combined, the model outputs a superposition of the individual next-token distributions. We term this the S

Just Ask Jev: Reinforcement Learning for Calibrated Decisions as a Zero-Shot Detector of AI Alignment Failures

👍 5

09/24 08:00

Detectors of alignment failures screen deployed language models and score alignment benchmarks. Most are generative judges that spend a decoding pass on every criterion, and classifiers that read token probabilities, such as Llama Guard, still score one fixed label per call. Jev, a model trained wit

Coding Agents for Generalized Task and Motion Planning Problems

👍 9

09/24 08:00

Task and motion planning (TAMP) problems remain difficult even with full observability and object-centric states because discrete decisions are tightly coupled to geometric, kinematic, and dynamic constraints. Generalized TAMP addresses this difficulty by exploiting regularities across problem insta

Rufus-Air: An Open LLM Post-Training Recipe

👍 13

09/24 08:00

Rufus-Air is an open and reproducible post-training recipe on GLM-4.5-Air-Base (106B-A12B), organized as a serial pipeline of eight stages: SFT, Reasoning RL, Coding RL, Instruction-Following RL, General Agent, Coding Agent, Search Agent, and RLHF. We document the data, reward design, infrastructure

IterSynth: Rethinking Deep Search Agents via Role-Decoupled Iterative Synthesis

👍 9

09/24 08:00

Deep search requires LLM agents to decompose complex queries, search for evidence, and synthesize grounded answers, yet existing ReAct-style agents suffer from two limitations: role coupling, where one policy must handle planning, evidence use, and synthesis; and context accumulation, where growing

PUBG Ally: A Conversational Embodied Agent as an AI Teammate

👍 5

09/24 08:00

We introduce PUBG Ally, an embodied agent for PUBG: BATTLEGROUNDS that can reason, act autonomously, and play alongside players as a voice-enabled teammate. Building such a teammate requires combining two difficult capabilities: it must perceive and respond to a constantly changing game world under

World Action Agent: Harnessing VLMs for Robot Manipulation via World Action Rehearsal

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09/24 08:00

General-purpose vision-language models (VLMs) bring broad knowledge and spatial reasoning to robot manipulation, yet existing systems either use them indirectly, to predict constraints or write programs, or give them a view of the scene rather than a world in which to act. We present World Action Ag

Rate-distortion optimization for full-reference image quality metrics via stochastic Hessian estimates

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09/24 08:00

Block-based video codecs select coding parameters based on the input by optimizing a rate-distortion trade-off. The conventional distortion choice, the sum of squared errors (SSE), simplifies parameter selection: the SSE is the sum of block-wise SSEs, so rate-distortion optimization (RDO) can treat

Qwen-Planner-Agent: A Closed-Loop AI-for-AI Framework for Real-World Mobile Planner Agents

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09/24 08:00

The rapid progression of large language models is extending AI from passive content generation into the active workflows of engineering and scientific discovery. This shift raises a compelling question: can AI be both the object of development and an active participant in building next-generation AI

Learning to Discover Interesting Mathematics

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09/23 08:00

Recently, Large Language Models (LLMs) have been increasingly able to solve advanced mathematical problems, including many that have been open for decades. This opens the door to expansion of mathematical knowledge at unprecedented scale. Yet, while LLMs may be able to conjecture and prove more and

DeltaWAM: Delta World Action Models for Bimanual Manipulation

👍 3

09/23 08:00

World-action models (WAMs) transfer visual and motion priors from pretrained video generators to robot control by jointly modeling visual dynamics and actions. Existing WAMs, however, predict dense future frames during training, repeatedly modeling largely unchanged content and coupling action-condi

Training Object Permanence in World Models

👍 197

09/23 08:00

Object permanence and solidity are hallmarks of human cognitive priors. Recent studies show that video generation models, a paradigmatic class of current world models, have begun to show emerged reasoning abilities, making them ideal candidates for building human-like physical intelligence. Do video

Agent-Editing World Model: Rethinking World Modeling for LLM Agents

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09/23 08:00

Recent advances in large language models (LLMs) have enabled agents to tackle long-horizon tasks across diverse environments. To further improve agent performance, existing language world models typically predict environment observations, yet reconstructing high-entropy, execution-dependent tool res

FLEET: From Logits Entropy to Enhanced Trajectories in Text Generation

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09/23 08:00

Solutions based on large language models (LLMs) often rely on temperature sampling to improve accuracy and stability by aggregating multiple samples from the completion distribution. However, this memoryless approach is inherently suboptimal: because it lacks awareness of prior generations and their

Just-in-Time Memory: Learning to Curate Task-Adaptive Memory for LLM Agents

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09/23 08:00

Agentic memory systems reuse past experience to improve future performance, yet most existing designs curate memory at write time: once a task is completed, its trajectory is distilled into a fixed artifact, such as a reflection, workflow, skill, or reasoning strategy, that is later retrieved by sim

EmbodiedSWE: Coding Agents for Long Horizon Dexterous Robotics

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09/23 08:00

We study coding agents for long-horizon, dexterous robotics and ask whether their solutions can provide scalable supervision for learning general robot policies. To test this, we develop EMBODIEDSWE-BENCH, a simulation benchmark for coding agents spanning contact-rich manipulation, deformable object

StudentBench: AI and human tutoring yield equivalent GRE learning gains

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09/23 08:00

Artificial intelligence offers an unprecedented opportunity to augment human capabilities, yet progress at the frontier has focused primarily on advancing model capabilities. We introduce StudentBench, a suite of AI teaching evaluations and a public platform that enables large-scale data collection

Knowledge Pull Requests for Continual Document Authoring

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09/22 08:00

We introduce Knowledge Pull Requests (KPRs), a framework for continual document authoring that makes each change interpretable. Documents require ongoing revision as new knowledge surfaces from other sources, languages, or times, but existing approaches either edit with no account of what knowledge

Capable yet Parsimonious: Extracting and Characterizing Hidden Chain-of-Thought in Frontier Models

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09/22 08:00

The rapid capability gains of frontier language models are widely attributed to improved reasoning abilities, yet this cannot be verified as raw CoT traces in closed-source systems are hidden. By registering a simple custom tool through a standard API feature, we induce frontier models to externaliz

Calibration as a First-Class Criterion in LLM Evaluation

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09/22 08:00

Calibration of language models -- the alignment between expressed or implicit confidence and empirical correctness -- is a well-studied subfield within NLP. Methods to measure it already exist. The problem is adoption: outside this subfield, NLP research regularly introduces new models, datasets, an

MemoryAthena: Adaptive Routing over Latent and Generated Memories

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09/22 08:00

Learned-memory methods store information in an explicit table and consume it through a separate reader, allowing addressing, storage, and reading to be modified independently. We study whether useful memory can also be generated rather than only retrieved. MemoryAthena uses three pathways: direct En

X-Planner: Event-Structured Task Planning for Embodied Intelligence

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09/21 08:00

Task planning bridges high-level instructions and executable behavior in long-horizon manipulation, yet modern Vision-Language-Action (VLA) systems often leave this intermediate structure implicit. Existing chain-of-thought (CoT) planners also tend to rely on coarse task-level annotations or seriali

HappyWorld-Bench

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09/21 08:00

Evaluating world models requires assessing both the quality of the worlds they generate and their consistency and responsiveness under exploration, interaction, and modification. We introduce HappyWorld-Bench, a comprehensive benchmark that evaluates whether generated worlds remain reliable as agent

OmniEcho: Spatial Audio Understanding for Embodied Agents

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09/20 08:00

Humans can effortlessly localize the direction of a sound source and integrate it with visual cues for reasoning, yet this remains challenging for embodied agents. In particular, it is still unclear how to effectively evaluate and model spatial audio understanding in embodied settings. To address th

PackLab: A Comprehensive Framework for Developing, Training, and Evaluating MLLMs in Robotic Bin Packing

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09/20 08:00

Robotic bin packing requires long-horizon sequential decision-making, as each object placement affects the available space for subsequent packing. Existing methods primarily rely on hand-crafted geometric heuristics that optimize predefined objectives or reinforcement learning policies learned throu

Neural Spectral Capacity: Measuring and Designing Architectures from Network Specification Alone

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09/19 08:00

Modern Transformer design and compression both reduce to allocating capacity under a budget. The standard scalars for these decisions, #Params and #FLOPs, capture size and compute but not architectural structure: two architectures with identical parameter budgets but different depth-width, head, or

Self-Organizing Agent Teams Learn to Reason Together

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09/19 08:00

Collective intelligence depends not only on what team members know, but also on how they organize their work. When the structure of a solution is unknown, useful roles and divisions of labor cannot be specified in advance; teams must learn from experience how to organize reasoning as it unfolds. Hum

Spatial-Interactor: Learning Spatial Reasoning through Interaction with the Observable Physical World

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09/19 08:00

Spatial reasoning is essential for vision-language models (VLMs) to understand and act in the physical world. Reasoning in dynamic environments requires VLMs to perceive local state transitions caused by object motion and viewpoint changes and integrate them over long trajectories to maintain an upd

AgentKernel: The Trust-Native Agentic Operating System

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08/29 08:00

Modern AI agents routinely cross trust boundaries: they ingest untrusted content, combine it with privileged instructions, persist intermediate beliefs in long-term memory, and invoke privileged tools. This creates an attack surface in which malicious payloads can enter through model inputs and caus

The New Copilot

@jacobandreou · 7.8K 粉丝 · 521.0K 阅 · 500 赞 · 77 转

09/25 21:02

The bottleneck is no longer intelligence. Over the last six months, intelligence has accelerated dramatically. But smarter models are not enough for everyone to benefit from novel intelligence. New

中文介绍 博主讨论了人工智能发展的瓶颈，指出智能模型加速但仍需更多创新以使所有人受益。

We're open sourcing the company brain, Here's how we designed the multi-player harness

@DhravyaShah · 63.2K 粉丝 · 112.4K 阅 · 608 赞 · 45 转

09/26 10:08

It's been just 2 weeks since we discontinued the company brain harness. We had to offboard tons of people to other products, but many of our customers, and others suggested us to open source our work

中文介绍 公司开源了其多用户协作工具，并分享了设计思路，尽管之前停止了相关服务。

Why AI is booming, but productivity isn't

@chamath · 2.4M 粉丝 · 97.8K 阅 · 551 赞 · 44 转

09/26 02:06

In June, I wrote that vibe coding was dead and that ROI-driven analysis of AI was about to go from a nice-to-have to a necessity. Here's what AI ROI is and why it's tricky to see in GDP numbers so

中文介绍 博主分析了AI繁荣但生产力未提升的原因，探讨了AI投资回报率在GDP数据中的难以体现。

Prescriptions for Prosperity in the Digital Economy

@saylor · 5.2M 粉丝 · 96.2K 阅 · 661 赞 · 98 转

09/26 21:11

Artificial intelligence will make it possible for individuals and companies to produce far more than they can today. That makes the freedom to create, finance, own, and exchange things more important.

中文介绍 博主提出了数字经济发展中创造、融资、拥有和交换物品自由的必要性，认为人工智能将极大提升生产效率。

Jev is a state-of-the-art search reranker

@ErikKaum · 2.0K 粉丝 · 75.0K 阅 · 501 赞 · 44 转

09/25 01:06

We evaluated Jev as a reranker for search results in turbopuffer. The results may surprise you. Jev isn’t just a good reranker, it performed better than existing state-of-the-art rerankers in our

中文介绍 博主评估了Jev作为搜索结果重排器的性能，指出其在某些方面超越了现有最佳重排器。

Using Claude Code: Spending your effort

@trq212 · 354.7K 粉丝 · 62.7K 阅 · 965 赞 · 52 转

09/26 04:04

One of the best parts of our newest Claude models is how they respond to effort without breaking the prompt cache in Claude Code, but I’ve received a lot of questions on this from users. What is

中文介绍 博主解答了关于Claude模型如何处理用户努力的问题，并讨论了相关功能。

We built a 20x faster Grok bot

@cerebras · 76.6K 粉丝 · 37.6K 阅 · 554 赞 · 28 转

09/25 23:28

Written by @milksandmatcha and @0xSero A personal assistant should save you time and effort. Over the past few weeks, we’ve been obsessively testing AI personal assistants on everyday tasks, from

中文介绍 介绍了一款速度提升20倍的Grok机器人，强调了个人助理在日常任务中的时间节省功能。

Ghast AI Season 3 Starts September 25

@Ghast_AI · 10.0K 粉丝 · 6.3K 阅 · 542 赞 · 31 转

09/24 22:29

We just introduced the Capability Economy, a market where private AI work can be bought and verified without exposing the method behind it. Every Capability in that market starts as a workflow someone

中文介绍 Ghast AI推出新功能“能力经济”，允许用户购买和验证私人AI工作流程而不透露方法。

OpenRouter: from Seed to Stripe — with OpenRouter’s Alex Atallah & AMP’s Anjney Midha

Latent Space · 09/26 07:14

In 2023 most people doubted that there could be more than 1 or 2 frontier model labs. Now there are dozens.... and Stripe just bought the best known one for $7B.

中文介绍 Stripe以70亿美元收购了最知名的模型实验室，OpenRouter的Alex Atallah和AMP的Anjney Midha参与其中。

Proaction boosts sales 60% and saves 75+ hours with Codex

OpenAI News · 09/26 03:00

With Codex, GPT-Live-1, and GPT-6 Astra, Proaction builds, operates, and sells modern fleet management faster.

中文介绍 OpenAI的Proaction利用Codex、GPT-Live-1和GPT-6 Astra，将现代车队管理构建、运营和销售速度提高60%，节省超过75小时。

The Pentagon wants $30 million to build an AI-powered lie detector

MIT Tech Review AI · 09/25 17:16

The US government wants to spend $30.3 million over the next five years on an improved form of lie detector, according to a Department of Defense budget request. The program, called Polygraph+ or Polygraph Next, will focus on scoring algorithms that use artificial intelligence and machine learning a

中文介绍 美国国防部请求在未来五年内投资3030万美元，用于改进的测谎仪技术，名为Polygraph+或Polygraph Next。

[AINews] The Future of Latent Space

Latent Space · 09/25 13:37

A quiet day lets us discuss the work behind the scenes - now open for business!

中文介绍 Latent Space开放业务。

Runway’s WorldPrompt and the Engineering of Real-Time Worlds

Latent Space · 09/25 09:30

GWM Worlds 2 uses persistent context and timed actions to steer a world model generating video and audio in real time.

中文介绍 GWM Worlds 2使用持续上下文和定时动作来引导生成视频和音频的世界模型。

ChatGPT Pro Max 🤖, Muse realtime avatar 🎭, DeepSeek $1B ARR 💰

TLDR AI · 09/25 08:00

中文介绍 ChatGPT Pro Max、Muse实时头像和DeepSeek达到10亿美元年度经常性收入。

Foundries vs Navigators: Lowering the Cost of Science

Latent Space · 09/24 23:03

Guest Post: In science, thinking has gotten cheap but doing has not. This asymmetry is reshaping how research companies operate, largely inconspicuously.

中文介绍 科学中思考变得廉价，但执行却不贵，这种不对称性正在重塑研究公司的运营方式。

Accelerating vision-language models with LFM2.5-VL-DSpark

Hugging Face Blog · 09/24 22:08

中文介绍 Hugging Face Blog上发布了关于加速视觉-语言模型LFM2.5-VL-DSpark的博客。

[AINews] Meta Connect 2026: Muse glasses, voice, video, and Charm

Latent Space · 09/24 16:12

Team Zuck is absolutely on fire.

中文介绍 Meta Connect 2026上展示了Muse眼镜、语音、视频和Charm技术。

Gemini TTS 🗣️, Claude’s novel enzyme 🧬, Google private memory 🔒

TLDR AI · 09/24 08:00

中文介绍 Gemini TTS、Claude的新型酶和Google的私有内存。

How to Use NVIDIA Warp and MjWarp to Accelerate Robotics Simulation and Learning Workflows

Hugging Face Blog · 09/24 02:41

中文介绍 NVIDIA Warp和MjWarp用于加速机器人模拟和学习工作流程。

Two years of OpenAI Academy

OpenAI News · 09/24 00:00

Marking two years of OpenAI Academy and bringing AI skills to even more communities.

中文介绍 OpenAI Academy成立两周年，将AI技能带给更多社区。

🔬Bio-security is an AI Arms Race - Eric Nguyen (CEO, Radical Numerics)

Latent Space · 09/23 21:27

Radical Numerics is using biological chain-of-thought and multimodal perception to keep up with the bio-defense arms race, design new genomes and gain insights into biology itself.

中文介绍 Radical Numerics利用生物思维链和多模态感知参与生物防御军备竞赛，设计新基因组，并深入了解生物学本身。

OpenAI extends cyber access to Ukraine for civilian defense

OpenAI News · 09/23 21:00

OpenAI is extending access to its Daybreak program to the Government of Ukraine to support the cyber defense of civilian infrastructure.

中文介绍 OpenAI将其Daybreak项目扩展到乌克兰政府，以支持民用基础设施的网络安全。

Sam Altman’s remarks at the United Nations Security Council

OpenAI News · 09/23 20:00

OpenAI CEO Sam Altman discusses AI safety, human control, and international cooperation in remarks to the United Nations Security Council.

中文介绍 OpenAI首席执行官Sam Altman在联合国安理会讨论了AI安全、人类控制和国际合作。