2026-10-24

Making MLLM Latents Matter: Factor-Aware Predictive Learning for Cinematic Video Generation

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10/22 16:43

Cinematic video generation requires both temporal inference from limited inputs (i.e., sparse rather than frame-by-frame guidance) and factor-aware control of character, scene, action, and camera. Multimodal large language models (MLLMs) offer useful priors for both capabilities, but their represent

Inherited, Not Invented: Tracing the Provenance of Wait in Reasoning Models

👍 6

10/22 16:03

Reinforcement learning (RL) is credited with teaching reasoning models to write {wait} before reconsidering a step, yet large RL accuracy gains do not require the word. This view can confuse what RL discovers with what a model inherits from its training data. We trace the word through open models' t

Different Tasks, Different Timesteps: Temporal Task-Aware Quantization for Diffusion Language Models

👍 4

10/22 08:00

Diffusion Language Models (DLMs) introduce unique quantization challenges due to their iterative denoising process. In this work, we reveal that quantization sensitivity is both taskand time-dependent, with different downstream tasks exhibiting distinct precision requirements across denoising steps.

BrickWright: Agentic Creation of Physically Feasible Brick Builds

👍 3

10/22 08:00

Frontier coding agents are becoming increasingly adept at 3D modeling. Yet, they still face challenges when building objects meant to be assembled in the physical world, often creating invalid assemblies with floating, colliding, or disconnected parts. We argue that providing agents with tools for a

FilmFlow: Agentic System for 3D Virtual Film Cinematography

👍 12

10/22 08:00

Complex camera motion is central to visual storytelling, yet translating cinematographic intent into controllable, executable camera trajectories remains challenging. We introduce FilmFlow, an agentic framework that converts natural-language instructions or reference videos into explicit camera traj

RIDAR: Safeguarding Research Integrity in Autonomous Research Agents via Automated Detection and Runtime Intervention

👍 6

10/22 08:00

Autonomous research agents are increasingly used to automate large portions of scientific research, yet they are prone to research integrity violations (RIVs): behaviors that compromise the validity, reproducibility, or faithfulness of the research process. We present RIDAR, a framework for automate

IQuest-Q1: Advancing Foundation Capabilities for Agentic CLI Systems

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10/22 08:00

We present IQuest-Q1, a sparse Mixture-of-Experts (MoE) agentic foundation model with 320B total parameters (15B activated). IQuest-Q1 is developed through a three-stage process: (1) stable and efficient pre-training, combining Stable SplitNorm, Muon, and muP with a two-stage curriculum whose second

What Makes a Good Unmasking Policy? A Controlled Study of Learned Unmasking in Diffusion Language Models

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10/22 08:00

Masked diffusion language models generate tokens in parallel, but their efficiency depends on which predictions are committed. Learned unmasking policies improve the speed--accuracy trade-off, yet differ in supervision, inputs, and capacity, obscuring which choices matter. We view supervised policie

F2G-Pose: Geometry-Aware Foundation Feature Lifting for Direct RGB-D Category-Level Object Pose Estimation

👍 5

10/22 08:00

This paper studies category-level RGB-D object pose estimation, which recovers an object's 3D rotation and translation without instance-specific CAD models or reference views. This task is highly ambiguous due to intra-class variations, symmetries, and partial observations. Current solutions struggl

AnyGameRenderer: Entity-Consistent Generative Rendering Across Games and an Entity-Level Benchmark

👍 11

10/22 08:00

AI coding agents can now build small playable games in minutes, but the results usually look like programmer art: gray blockouts, colored geometric primitives, and flat semantic blobs. We present AnyGameRenderer, a video-to-video generative renderer that turns such footage into high-quality visuals

Cola2: Co-Adaptive Hierarchical Language Modeling with Continuous Semantic Compression and Balanced Discrete Generation

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10/22 08:00

Hierarchical language generation separates continuous semantic modeling from discrete text realization, but its effectiveness depends on what the latent space compresses and how the discrete generator uses it. We propose Cola2, a framework that jointly studies continuous semantic compression, the ba

AgentVQA: A Unified Benchmark for Agentic Visual Understanding

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10/22 08:00

Vision-language models (VLMs) can perform a broad range of tasks across diverse settings, yet their performance in agentic contexts remains poorly understood. Although online evaluations in simulators and real-world environments are essential for measuring interactive agent performance, they are cos

Is Complex Agentic Memory Always Needed? Naive RAG Is Stronger Than We Thought

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10/22 08:00

LLM memory is widely used in long-term conversation understanding. Agentic memory systems often use mutation, structural organization, learned retrieval strategies, or other complex operations. Is this complexity always necessary? We study Raw-RAG, a naive RAG baseline using dense retrieval and rera

Skeleton-Grounded Latent Action Model for Robot World Models

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10/22 08:00

Robot world models simulate how environments evolve in response to robot actions. Latent action models enable learning dynamics from videos by encoding visual transitions as proxy actions. However, reconstruction-driven latent actions mix robot motion with object responses and other scene changes, c

Beyond Watching and Searching: Benchmarking Agents for Video-centered Deep Research Reports

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10/22 08:00

Deep research agents synthesize open-web evidence into long reports, but current benchmarks do not evaluate research centered on a source video. We introduce Video-Centered Deep Research Report Generation. Given a video and user request, an agent identifies research questions, retrieves external mul

SCOPE: Compiling Natural-Language Policies into Neurosymbolic Predicate Programs

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10/22 08:00

Policy enforcement for LLM agents has shifted from single-turn content moderation to compound, application-specific policies evaluated over multi-turn transcripts and tool-call trajectories. Fine-tuned guardrail models are efficient but degrade on compound policies, and while LLM-as-a-judge approach

Agent Mosaic: Recognizing Confidentiality Leaks in Agentic LLM Systems

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10/21 08:00

Modern LLM agents can retrieve information from accessible documents, and then disclose a sensitive conclusion assembled from them. This mosaic effect creates a critical risk for agents operating over confidential data. We quantify its realization with 30 synthetic cybersecurity, medical, and milita

Toward Recursive Self-Improvement in Physical AI

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10/21 08:00

Recursive self-improvement (RSI) describes a system that improves not only its behavior but also the process by which it improves. Recent digital agents test this idea by rewriting their own code and checking each version with executable tests. Bringing these mechanisms into the physical world requi

LaLa-World: Scaling Latent World Models with Natural Language Actions

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10/21 08:00

This paper shows that JEPA-style latent world models (LWMs) can learn across diverse domains and data sources by adopting the language-conditioned interface of video generation models. We establish this approach as an effective and efficient basis for planning with imagination and downstream policy

RLSplat: Resource-Linear Budget Control for Feed-forward 3D Gaussian Splatting

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10/20 08:00

Feed-forward 3D Gaussian Splatting (FF3DGS) reconstructs 3D scenes from images in a single forward pass, making it well-suited to applications that must operate within limited resource budgets. To further improve its practicality, recent budget-controllable FF3DGS methods allow the number of Gaussia

Meta Expert: Cross-Layer Expert Sharing for Storage- and Retrieval-Efficient MoE

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10/20 08:00

As model parameters scale up, sparsely activated Mixture-of-Experts (MoE) approaches have become essential for model scaling. However, mainstream models currently adopt hierarchical architectures, where experts in different layers, although topologically independent, exhibit substantial similarity a

Code2Video-Compass: A Comprehensive Benchmark for General-Purpose Code-Based Video Generation across T2V, I2V, and V2V

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10/20 08:00

Code-based video generation offers fine-grained control, targeted editing, and component reuse compared with direct video generation. This approach requires multimodal large language models (MLLMs) to translate visual and temporal requirements into executable programs that produce complete videos. H

Who Takes the Lead? Model Ability and Task-Conditioned Collaboration with Humans

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10/19 08:00

As language-model agents grow more capable, they can carry more of a task without asking anyone for help. Falling reliance on a human partner is easy to read as a failure of collaboration when it may instead be a correct division of labor, and the rate of human involvement alone cannot tell the two

RouteWeaver: Weaving Mode Selection and Execution into Unified LLM Routing

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10/19 08:00

LLM routing dynamically selects and coordinates heterogeneous language models across diverse tasks. However, existing approaches are largely built around a predefined execution paradigm, such as single-round, multi-round, or agentic routing, which fixes how model calls are organized and limits adapt

Heartbeat Thinking: Speculative Reasoning and Tool Execution While Listening in Realtime Voice Agents

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10/19 08:00

Tool-using voice agents often leave users waiting after speech ends, even when actionable information arrives earlier in the request. Speculative approaches begin work during speech, but chunk-bounded or interrupt-on-update generation can truncate a tool call before its arguments are complete. This

Deep Search in Real-World Web Environments

👍 149

10/19 08:00

Despite substantial progress in Deep Search agents, their ability to conduct end-to-end research in real-world open Web environments remains insufficiently evaluated. Unlike static retrieval settings, information on the real-world Web is distributed across diverse sources, modalities, and heterogene

Deep Fusion Memory: A Chunk-Level Parametric Memory for Large Language Models

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10/18 08:00

Large language models need effective ways to acquire and use external knowledge beyond what they retain from pretraining. Continued pretraining risks catastrophic forgetting, while retrieval at inference time can add substantial overhead. External parametric memory avoids online retrieval, but const

Bridging Exploration and Persona: Information-Directed Dueling for Test-Time Agent Personalization

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10/17 08:00

Effective test-time personalization requires LLM agents to adapt to query-dependent user preferences from lightweight interaction. We study persona selection with binary comparisons between candidate responses as the online signal. We present ID-TAP, a scalable, IDS-inspired neural dueling-bandit fr

IF-MAP: Influence-Function-Inspired Agent Prioritization in Multi-Agent Systems

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10/17 08:00

Improving every agent in an LLM-based multi-agent system can be prohibitively costly, making it important to identify which agent should be prioritized to achieve the greatest system-level gain with limited resources. Failure attribution can inform this decision, but an agent's responsibility for fa

MolLean: A Process-Verifiable Language for Chemical Reasoning

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10/14 08:00

Chemical chain-of-thought can contain hallucinated structural and property claims. We thereby introduce MolLean, a process-verifiable language that grounds chemical reasoning in an explicit molecular state. A layered Lean-based kernel checks state transitions and assertions over molecular readouts,

How Harvey is Building a Frontier Marketing Org

@gabepereyra · 13.4K 粉丝 · 111.8K 阅 · 505 赞 · 47 转

10/22 01:06

Recently, @figma asked us what Harvey was building with its MCP server. This is the long answer. Between the MCP and better frontier models, agents now run whole design projects end to end across our

中文介绍 探讨 Harvey 如何构建前沿营销团队，涉及 MCP 服务器和前沿模型应用。

Grok Bot as Your Head of Content (FULL GUIDE)

@ryangrowthh · 5.6K 粉丝 · 74.8K 阅 · 519 赞 · 27 转

10/22 22:29

My team of 11 Grok Bots helped me generate ~2M impressions in my first two weeks of posting on 𝕏. Today, I'm revealing the entire system. Firstly, the elephant in the room - proof of the results:

中文介绍 分享使用 Grok Bot 生成 200 万次曝光的完整系统，揭秘内容创作策略。

AI Is Creating Modern Vampires

@BrianDEvans · 1.3M 粉丝 · 50.8K 阅 · 826 赞 · 34 转

10/23 04:31

AI is going to create some ridiculously cracked people. Imagine someone who built a hundred-billion-dollar company around their own invention, won Olympic gold, and directed an Oscar-winning film.

中文介绍 讨论 AI 可能导致的极端现象，如个人成就的过度依赖。

Fuck Higgsfield : why we launched a 0% markup API

@davidim · 7.6K 粉丝 · 47.8K 阅 · 532 赞 · 31 转

10/23 03:57

Today we launched Sume API with a 0% markup, which means you get the same models at exactly the price the original model provider charges. A lot of people have asked me why we'd do something that

中文介绍 介绍 Sume API 的 0% 加成策略，分析推出无利润 API 的原因。

3 markdown architecture patterns that boost agentic productivity

@GoogleCloudTech · 1.3M 粉丝 · 38.7K 阅 · 502 赞 · 68 转

10/23 09:33

There is a running joke in modern software engineering that the hottest programming language isn't Rust, Zig, or Python: it’s Markdown. As coding agents become entrenched in developer workflows, many

中文介绍 介绍三种提升代理生产力的 Markdown 架构模式，探讨 Markdown 在软件工程中的应用。

Banks Built Controls for People. AI Agents Are Walking Right Through Them.

@puneetmehtanyc · 4.0K 粉丝 · 37.2K 阅 · 577 赞 · 57 转

10/23 05:40

Major U.S. banks are detecting third-party AI agents operating inside customer accounts without the banks’ approval, Axios reported this morning. Some of those agents appear to be acting beyond their

中文介绍 报道美国大型银行检测到未经批准的第三方 AI 代理在客户账户中的活动。

Rapidly scaling online storage to serve over 1 billion ChatGPT users (Part II)

OpenAI News · 10/24 01:00

Learn how OpenAI scaled Habitat with reliable multi-tenancy, global caching, and Azure Cosmos DB to deliver 12× faster reads for ChatGPT.

中文介绍 OpenAI通过使用可靠的多租户、全球缓存和Azure Cosmos DB将Habitat扩展，为ChatGPT用户实现12倍读取速度。

LitPivot: Developing research ideas through dynamic contextualization within the literature landscape

Hugging Face Blog · 10/24 00:15

中文介绍 Hugging Face Blog讨论了通过文献景观中的动态语境化来发展研究思路。

AI Is Getting Good at Math. Here’s Why.

Latent Space · 10/23 23:19

AI models are solving more mathematical problems. A pattern is emerging in their successes that could help us predict which problems they’ll solve next.

中文介绍 AI模型在解决更多数学问题，其成功模式有助于预测它们接下来能解决哪些问题。

[AINews] Black October

Latent Space · 10/23 18:09

the Cyber onslaught continues.

中文介绍 网络攻击持续，AI领域的“黑色十月”继续。

Securing our frontier model training environment

OpenAI News · 10/23 18:00

OpenAI explains how we strengthened containment for frontier model training and evaluation, including offline environments and high-compute red-teaming.

中文介绍 OpenAI解释了如何加强前沿模型训练和评估的防护，包括离线环境和高计算红色团队。

OpenAI and Poland’s NASK partner to advance AI safety and security

OpenAI News · 10/23 08:00

OpenAI and Poland’s NASK are partnering on AI safety, security, and technical research to strengthen safeguards and support a more resilient digital ecosystem.

中文介绍 OpenAI与波兰NASK合作，共同推进AI安全和网络安全，以加强防护和支持更具弹性的数字生态系统。

Does Your Model Run on AWS Trainium? Look It Up

Hugging Face Blog · 10/23 08:00

中文介绍 探讨AWS Trainium上模型运行的问题。

OpenAI nears $1.25T 💰,  ☁️, 1Password for Agents 🔑, Gemini 3.5 Pro postmortem 🤖

TLDR AI · 10/23 08:00

中文介绍 OpenAI估值接近1.25万亿美元，1Password for Agents发布，Gemini 3.5 Pro回顾。

Turning Database Grading into RL Rewards: Post-Training Agents with ThinkingBox

Hugging Face Blog · 10/23 06:24

中文介绍 通过ThinkingBox将数据库评分转换为强化学习奖励，以进行后训练代理。

Designing an AI serving harness built to last

MIT Tech Review AI · 10/23 05:17

The next competitive advantage in enterprise AI has less to do with which model you choose than with what you build around it. That’s an important shift. For the past several years, much of the AI conversation has centered on model capability: bigger models, better reasoning, larger context windows,

中文介绍 企业AI的下一个竞争优势不在于选择哪个模型，而在于围绕它构建的内容。

Build more responsive apps with the Decisions API

OpenAI News · 10/23 03:00

Fast, focused, low-cost decisions for any application.

中文介绍 Decisions API提供快速、专注、低成本的应用决策。

The Foundations of Scalable AI

MIT Tech Review AI · 10/23 02:48

A scalable AI system requires a strong foundation. Data, engineering, platforms, operating models, and governance must converge to work as one. This session from MIT Technology Review’s EmTech Future conference explores what it takes to build that foundation in a highly regulated environment and how

中文介绍 可扩展的AI系统需要坚实的基础，数据、工程、平台、运营模式和治理必须协同工作。

Why AI Compute Comes in Rectangles — Erik Bernhardsson, Modal CEO

Latent Space · 10/23 01:40

Elastic GPUs, sandbox growth, and the economics of the agent cloud

中文介绍 Modal CEO Erik Bernhardsson探讨了弹性GPU、沙盒增长和代理云的经济。

Beyond tree cover: mapping the world’s forest types

DeepMind Blog · 10/22 22:30

A global map categorizing every 10-meter patch of land on Earth into distinct forest types.

中文介绍 DeepMind发布了一份全球地图，将地球每10平方米的土地划分为不同的森林类型。

You are the Team — Anekha Sokhal, Moshi

Latent Space · 10/22 22:03

How Moshi turns market data into actionable insights, and why AI tools have to fit the trader’s workflow.

中文介绍 Moshi将市场数据转化为可操作见解，并解释了为什么AI工具必须适合交易者的工作流程。