2026-10-01

What Makes Recurrence Effective in Looped Language Models?

👍 7

09/29 08:00

Looped language models (LoopLMs) increase computational depth through parameter sharing, offering a path to scale inference computation without adding parameters. However, it remains unclear when additional recurrence is beneficial and how architectural choices affect its effectiveness. Through cont

Can Agents Design Libraries for Agents?

👍 8

09/29 08:00

Agents increasingly build on code written by other agents, and they reimplement rather than reuse, growing the codebases later agents must work in. To measure how well agents design libraries for other agents, we introduce LibraryDesignBench, a two-phase benchmark in which an agent implements a full

Scheduling Recursive Reasoning in Looped Transformers

👍 11

09/29 08:00

Recurrent reasoning models have attracted growing attention for scaling test-time computation, typically by iteratively refining latent states with shared parameters. However, these models apply each learned update with a fixed unit scale, which can be conservative when updates make persistent progr

FocusVTC: Efficient and High-Performance Visual Text Compression with Adaptive Resolution

👍 20

09/29 08:00

Long-context reasoning in large language models incurs substantial computation and memory costs. Visual text compression (VTC) reduces input length by rendering text as images, but fixed-resolution rendering creates a compression-performance trade-off: low DPI saves tokens at the expense of legibili

Routing Should Pay for Itself: Sparse Supervision for Economical LLM Routing

👍 10

09/29 08:00

Large language model (LLM) routing reduces serving cost by assigning each query to an appropriate model while preserving response quality. Learning such a router, however, often requires executing multiple candidate models on historical queries to collect query--model quality feedback, creating a no

Scaffolding Minds: Optimizing Latent Visual Target Representations for Multimodal Reasoning

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09/29 08:00

Latent reasoning has advanced multimodal reasoning through a two-stage training paradigm: (1) a helper image is encoded into latent tokens to teach visual chain-of-thought during a supervised fine-tuning (SFT) stage, and (2) these latent tokens are further refined with reward feedback during a reinf

APM-Bench: Benchmarking Cross-session Persistent Memory for Egocentric Streaming Video Assistants

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09/29 08:00

To serve as real-world personal assistants, streaming video models need persistent memory that retains past experiences for later use. Yet existing streaming benchmarks and methods often focus on individual continuous videos or short clips, overlooking that real-world interactions are often intermit

Asking for What Was Never Requested: Horizontal and Vertical Proactivity in Agents

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09/29 08:00

An agent that uses tools typically responds to what the user explicitly asks, yet completing the task may require information the user never requested. Work on proactive agents mainly studies whether and when an agent should act on its own, not what information it should pursue. We study a distinct

SoL-Refiner: Speed-of-Light One-Step Refinement for High-Resolution Video

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09/29 08:00

High-resolution video generation is expensive, as its cost grows rapidly with the number of spatiotemporal tokens. A practical alternative first generates a lower-resolution video and then applies a refiner, but conventional multi-step refinement introduces a second sampling bottleneck. We present S

Breaking the Uniformity Trap: Scaling Video Diffusion Model via SplitMoE

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09/29 08:00

Mixture-of-Experts (MoE), popularized by large language models, is a promising paradigm for scaling visual generative models. However, conventional token-wise MoE routes tokens independently within a homogeneous expert pool and regularizes expert usage toward uniformity, making it poorly matched to

Follow the Entities: A Corpus Map for Agentic Search

👍 68

09/29 08:00

Answering questions and completing tasks over large document collections often requires connecting evidence spread across multiple documents, such as a project's approval recorded in one, its requirements in another, and its latest status in a third. Recent LLM agents approach this by iteratively se

Context Language Models

👍 23

09/29 08:00

We introduce Context Language Models (CLMs), language models that natively manage their own context. We implement this by treating the context as a file and allowing the model to make unrestricted updates to this file. This allows the model to learn what is most important to maintain in context, and

Chinese-Jev: Bringing System One Model to Chinese-Language Tasks

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09/29 08:00

System One models such as Jev offer an efficient alternative to generative language models for tasks that require decisions rather than open-ended responses. However, existing Jev models exhibit limited Chinese-language decision accuracy, restricting their utility in both general and specialized set

Fractional State Space Transition for Long Sequence Modeling

👍 10

09/28 08:00

State Space Models (SSMs) compress sequence history into a bounded recurrent state, making the resulting memory law a central architectural choice for long-context performance. Most modern SSMs rely on ODE-based dynamics that lead to exponential forgetting, limiting their ability to retain informati

Periodic Weak Spots: Phase Sensitivity from Chunked KV-Cache Compression

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09/28 08:00

Chunked KV-cache compression reduces the memory and attention costs of long-context inference by compressing windows of consecutive tokens into fewer cache entries at a fixed stride. Such compression also introduces a new positional coordinate: a token's phase, or its position relative to compressio

Org-Agent: Beyond Personal Assistants Towards Organizational Agents

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09/28 08:00

Language model agents serving organizations must coordinate requests from multiple users while using knowledge distributed across their interactions. We identify two complementary capabilities for this setting, namely cross-user interaction and decision-making, as well as cross-user memory and knowl

PMOPD: Task Ordering, Cycling, and Parameter-Update Subspace Protection in Multi-Teacher On-Policy Distillation

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09/28 08:00

Multi-teacher on-policy distillation (MOPD) has emerged as a popular post-training paradigm for integrating specialized capabilities in frontier language models. Existing OPD research has primarily focused on optimizing single-task distillation through objective design, distillation scope, and teach

AutoRef: Harness Optimization for Agentic Multi-Reference Image Generation

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09/28 08:00

Recent image generation models can take multiple reference images as input and combine them into a new image. However, multi-reference image generation remains challenging: models may omit or duplicate subjects from the references, or produce images in which multiple subjects appear unnaturally past

LLMs are General Asynchronous Agents

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09/28 08:00

Modern LLMs are increasingly capable as autonomous agents, but they follow sequential interaction cycles: read, think, reply or call tools, repeat. Many real-world use cases are not sequential: voice assistants, embodied agents, and monitoring systems receive new inputs while they think or perform a

SEAD: A State-Based Perspective on Attack and Defense in Tool-Using Agents

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09/28 08:00

Language-model agents increasingly use tools to act on external systems. Earlier actions can alter files, permissions, database records, or other state, making a later routine-looking action harmful. Yet the visible interaction may not reveal the underlying state needed to assess that action. We for

Understanding On-Policy Distillation: A Mechanistic Interpretability Perspective via Sparse Crosscoders

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09/28 08:00

On-policy distillation (OPD) is a widely adopted post-training technique for LLM reasoning. It is commonly believed to transfer knowledge from a stronger teacher, yet what OPD actually distills into the student's internal representations remains unclear. We study this question with sparse crosscoder

Same Bytes, Different Authority: Reserved-Token Representations in Chat-Template Prompt Injection

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09/28 08:00

Prompt injection against LLM agents becomes much stronger when the injected instruction is wrapped in the model's own chat template. A forged template marker such as <|im_start|> can reach the model either as a single reserved control token or as a sequence of ordinary subword tokens. The two decode

AnyStep-WAM: Budget-Aligned Distillation and Adaptive Inference for World Action Models

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09/27 08:00

World-action models (WAMs) couple predictive visual modeling with action generation, typically relying on iterative denoising with a fixed denoising steps. However, manipulation tasks contain actions chunks with varying sensitivity to generation errors: critical actions require precision, while less

StoryEngine: A State-Grounded Agentic Framework for Video Storytelling

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09/27 08:00

Despite recent progress in agentic multi-shot video generation, producing coherent and consistent long-form stories remains challenging. Existing agentic pipelines typically rely on textual shot plans or previously generated pixels, yet lack an explicit mechanism for propagating the consequences of

AgentTell: Behavioural Side-Channel Leakage in Browser-Use Agents

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09/26 08:00

Browser-use agents often carry information in their context as they move between websites. While it may be necessary for task completion, it also creates a privacy risk, especially when the information contains a private fact regarding the user. For example, an agent may learn a user's affiliation a

Scaling Properties of Same-Family On-Policy Distillation

👍 198

09/26 08:00

*Reinforcement learning (RL)* can induce substantial reasoning capabilities in large language models (LLMs), but how much of this capability transfers across model scales, and how quickly, remains unclear. We study the scaling properties of *on-policy distillation (OPD)* across *weak-to-strong*, *sa

Beyond Dyadic Memory: Interaction-Aware Multimodal Memory with Adaptive Agentic Retrieval for Multi-Party Spoken Conversations

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09/26 08:00

Long-term memory enables agents to accumulate information and reason across sessions, yet existing research primarily focuses on dyadic text or image-text conversations, leaving long-term memory for multi-party spoken conversations underexplored. This setting requires preserving conversational conte

Omni-IO Skills: Harnessing Your Agent Omni-Native

👍 156

09/25 08:00

General-purpose agents can plan, reason, and act over long horizons, yet their production capabilities remain fragmented across text, images, audio, video, documents, 3D assets, and code. Extending a foundation model to additional modalities ties capability growth to costly model updates, while asse

Omni-Decision: Evidence-Ledger Planning for Omni-Modal Agents

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09/24 08:00

Omni-modal agents must seek evidence across video, audio, web pages, and computation to answer questions. Their main bottleneck is planning: noisy multimodal observations accumulate in conversation history and disrupt later decisions, while multimodal models have limited capacity for multi-step plan

Reasoning with Image Generation

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09/15 06:29

Chain-of-thought reasoning has revolutionized natural language processing by enabling large language models (LLMs) to decompose problems into intermediate steps before answering. Yet confining reasoning to the textual domain presents limitations for tasks requiring direct manipulation of visual repr

Teamily vs. OpenAI Dots: The Vision "Team of Dots" is Already Here, Using by Million of Users

@Teamily_AI · 1.6K 粉丝 · 749.2K 阅 · 512 赞 · 170 转

09/30 04:00

OpenAI just shared its vision for Dots: an always-on personal agent today, evolving over time into teams of specialized agents working together. We think that is exactly where AI is going. It is also

中文介绍 Teamily AI对比OpenAI Dots，探讨AI发展愿景，强调团队协作模式趋势。

Meet your Team Bots

@n2parko · 5.7K 粉丝 · 274.2K 阅 · 533 赞 · 38 转

09/29 04:03

Today we're introducing Team Bots, and it's likely the biggest change to Grok Bot since launch. I wanted to share a bit about why we built it and how these new digital colleages might change the way

中文介绍 n2parko介绍Team Bots，探讨其如何改变数字同事的使用方式。

Free the models: harness design at the frontier

@pirroh · 16.2K 粉丝 · 234.6K 阅 · 507 赞 · 78 转

09/30 00:48

Model routers are everywhere right now, but they have a fundamental limitation. No matter if based on advanced heuristics or a small model that reads each turn and picks which LLM to use, a router

中文介绍 pirroh分析模型路由器的局限性，提出改进方向。

History Rhymes: Large Language Models Off to a Bad Start?

@michaeljburry · 2.1M 粉丝 · 120.2K 阅 · 519 赞 · 84 转

09/30 23:04

This 145-year-old case study – presented at the Smithsonian Institute no less - provides a potentially devastating critique of today’s Large Language Models and the spending behind them. Michael Burry

中文介绍 michaeljburry通过历史案例研究，对大型语言模型及其背后的投资提出批评。

The FDE boom is a product gap

@EugenAlpeza · 2.5K 粉丝 · 96.2K 阅 · 539 赞 · 50 转

09/29 22:07

The industry is hiring its way around a missing product. Every enterprise trying to put agents to work runs into the same problem: agents don’t know how the company operates, and the operators who do,

中文介绍 EugenAlpeza指出企业AI代理面临的产品差距问题。

CC, our experimental AI agent built for families

@GoogleAI · 2.5M 粉丝 · 69.4K 阅 · 508 赞 · 36 转

09/29 02:54

Managing a household means juggling busy schedules, crowded inboxes, and endless to-do lists. It requires context switching, multitasking, and the most precious resource of all: time. Earlier this

中文介绍 GoogleAI介绍为家庭设计的实验性AI代理CC，强调其管理家务的能力。

i made 10+ motion videos with opus 5.5 in 3 days. here's the whole pipeline (open source)

@RaphaelAubryy · 393 粉丝 · 40.9K 阅 · 507 赞 · 42 转

09/28 17:25

Most people trying motion design with Opus 5.5 hit the same wall: ↳ the first render is "mid": centered text, a gradient, everything fading in ↳ the music and the picture live separate lives ↳ one

中文介绍 RaphaelAubryy分享使用Opus 5.5制作动态视频的整个工作流程。

How I Make $10K Launch Videos for $0 with Opus 5.5 (Full Course)

@twoclipping · 7.5K 粉丝 · 40.5K 阅 · 510 赞 · 35 转

09/28 13:42

im open sourcing my entire workflow for making the motion designs that studios charge $5,000 to $15,000 for this uses 0 mcp, 0 external tools and im not selling you any subscription you dont need

中文介绍 twoclipping开源制作运动设计的工作流程，无需额外工具或订阅。

DeepSeek Harness for Desktop Is Here

@DeepSeekHarness · 989 粉丝 · 35.4K 阅 · 1.0K 赞 · 69 转

10/01 00:13

Today, we’re releasing the DeepSeek Harness v0.2 preview, with a desktop app available for macOS and Windows. You can install it here and follow the instructions to get started. This release comes

中文介绍 DeepSeek Harness发布桌面版预览，支持macOS和Windows。

Building a design system for coding agents

@arlanoska · 3.5K 粉丝 · 25.4K 阅 · 503 赞 · 29 转

09/30 02:26

You ask an agent to build a page. Then you fix the spacing, swap the inputs and explain which button it should use. The next agent makes different choices, so you do it all again. If your repo has

中文介绍 arlanoska探讨为编码代理构建设计系统的方法。

Why Dwarkesh is Wrong about Computer Use + How OpenAI shipped its Jev competitor in 1 Week

Latent Space · 10/01 06:23

Our DevDay coverage - the first pod on the DevDay lineup - dives in with the leaders of OpenAI’s CUA team and API platform.

中文介绍 OpenAI CUA团队和API平台负责人参加DevDay首场Podcast讨论。

Gemini 4 Argon: our next era of frontier intelligence

DeepMind Blog · 10/01 04:01

中文介绍 DeepMind发布Gemini 4 Argon，开启前沿智能新时代。

Introducing SynthID Bio

DeepMind Blog · 09/30 23:03

Proof of concept for watermarking AI-generated proteins while preserving biological function.

中文介绍 DeepMind推出SynthID Bio，实现AI生成蛋白的水印技术。

“We’re not going to shoot ourselves in the foot” over hack fallout, says OpenAI’s chief research officer

MIT Tech Review AI · 09/30 18:40

Two months after the bombshell news that a swarm of its agents had broken their containment and hacked into the computers of the AI company Hugging Face, OpenAI is still putting out fires. A steady drip of disclosures about other hacks in the weeks since has kept OpenAI in the spotlight and raised s

中文介绍 OpenAI首席研究官表示，不会因黑客攻击自损。

Disrupting a coordinated model-distillation campaign

OpenAI News · 09/30 18:30

Learn how OpenAI disrupted a campaign to extract protected model reasoning and is strengthening defenses against adversarial distillation.

中文介绍 OpenAI破坏了一场协调的模型蒸馏活动。

Helping small businesses put AI to work

OpenAI News · 09/30 18:00

OpenAI is partnering with America’s SBDC to expand hands-on AI training and local support for small businesses, alongside a new report on how small teams are using AI.

中文介绍 OpenAI与America’s SBDC合作，为小型企业提供AI培训和当地支持。

[AINews] OpenAI DevDay 2026: Dots, 6.1 Sol, Ultrafast, Decisions API, Agents API, Spaces, Marketplace, and 1.2 Billion ChatGPT WAU

Latent Space · 09/30 13:53

the most confident DevDay yet.

中文介绍 OpenAI DevDay 2026发布多个新功能，包括Dots、6.1 Sol等。

Open TTS Leaderboard: Scalable Evaluation for Multilingual Text-to-Speech and Voice Cloning

Hugging Face Blog · 09/30 08:00

中文介绍 Hugging Face推出Open TTS排行榜，用于多语言文本到语音和声音克隆的可扩展评估。

OpenAI Dots 🟡, GPT-6.1 Sol ⚡, software factories 🏭

TLDR AI · 09/30 08:00

中文介绍 OpenAI发布Dots、GPT-6.1 Sol和软件工厂等新功能。

NVIDIA Kumo Tabular Sets a New Accuracy-Efficiency Frontier for Tabular Prediction

Hugging Face Blog · 09/29 23:30

中文介绍 NVIDIA Kumo Tabular为表格预测设定了新的准确性和效率前沿。

Getting the Source Right, Not Just the Fact: Source-Aware Verification for MCP Agents

Hugging Face Blog · 09/29 21:07

中文介绍 Hugging Face推出针对MCP代理的源识别验证。

Making AI an asset, not an expense

MIT Tech Review AI · 09/29 18:43

When customers talk about AI costs, the conversation usually starts with token prices and ends with access to the latest, most capable model in the cloud. Do they always need that level of capability? Not necessarily. But that is often where the conversation goes. As AI moves from experimentation to

中文介绍 将AI视为资产而非成本。

Introducing GPT-6.1 Sol

OpenAI News · 09/29 18:00

Meet GPT-6.1 Sol: near-Astra intelligence for coding, computer use, and professional work at one-fifth of Astra’s standard API input and output token prices.

中文介绍 OpenAI推出GPT-6.1 Sol，近Astra智能水平，价格仅为Astra标准API的五分之一。

DevDay 2026 Recap

OpenAI News · 09/29 18:00

Explore more than 20 announcements from OpenAI DevDay 2026, including GPT-6 Astra, ChatGPT, Codex, APIs, security, and new tools for builders.

中文介绍 OpenAI DevDay 2026回顾，发布20多项公告，包括GPT-6 Astra、ChatGPT等。

[AINews] AMD buys World Labs for $8.2B, as Atlas solves sparse reconstruction problem for robotics, design and more

Latent Space · 09/29 10:55

Congrats team!

中文介绍 AMD以82亿美元收购World Labs，Atlas解决机器人、设计等领域的稀疏重建问题。