2026-10-04

Ego2Act: Evaluating Goal-Directed Manipulation in Egocentric Video Generation

👍 21

10/01 08:00

Video generation models are increasingly being explored as world simulators for embodied planning and learning. To do so effectively, these models must not only generate visually appealing frames, but also predict how environments dynamically evolve when executing goal-directed actions. While evalua

ScholarCatalyst: A Benchmark for Retrieving Papers That Inspire New Research

👍 9

10/01 08:00

What makes great scientists great? Even as AI systems start to make progress on open problems, scientists remain far ahead of them at sensing which prior idea, buried in an ever-growing archive of research, a new problem needs. To study this skill, we draw on researchers who know firsthand which ear

Where-OPD: Spatially Guided On-Policy Self-Distillation of MLLMs with Synthetic Scenes

👍 14

10/01 08:00

On-policy self-distillation has recently emerged as an effective approach for improving language-model reasoning by supervising students with a frozen or EMA version of themselves that receives privileged information. Its application to multimodal large language models (MLLMs), however, remains larg

Decoding Looped Transformers Better for (Almost) Free

👍 25

10/01 08:00

Looped Transformers achieve parameter efficiency by repeatedly executing a shared block across recurrent loops. Each loop yields an intermediate representation decodable for the same next token, yet standard decoding discards earlier states. Because earlier loops embody less computation, recurrence

Generalization Is Stability, Not Accuracy: Multi-Axis Evaluation of LLMs

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10/01 08:00

Generalization in large language models (LLMs) is the ability to produce consistent and semantically stable outputs when the same input is expressed in different ways. Existing work typically evaluates generalization through aggregate accuracy on a single prompt format, task, or set of variations, w

Before It Fades: Reinforcing Temporal Representations at Inference Time in VideoLLMs

👍 5

10/01 08:00

Video Large Language Models (VideoLLMs) receive frames in sequential order and interpret how visual content evolves along the temporal axis, yet temporal reasoning remains a persistent weakness across architectures. Reversing the frame order of a video, a transformation that should invert temporal a

Fewer Tokens, Better Action: GPT-6 Astra Robot Agents with 14% Higher Success Rate but 65% Fewer Tokens

👍 34

10/01 08:00

Vision language model (VLM) agents can control robots through visual feedback and action primitives, but repeated model invocations and redundant observations incur substantial token overhead. We introduce PyRUA-Lean, an interactive code-execution framework that couples feedback-driven primitive com

OneStreamer: Unifying Perception, Memory, and Proactive Response in Streaming Video Interaction

👍 160

10/01 08:00

Streaming video LLMs must retain evidence before its relevance to future tasks is known and respond when sufficient evidence becomes available. The challenge is to form reusable factual memory without compromising real-time perception. We introduce OneStreamer, which jointly learns query-independent

VTR-Bench: A Systematic Benchmark for Evaluating Visual Text Rendering in Video Generation

👍 10

10/01 08:00

Recent video generation models can produce highly realistic videos from natural language instructions, with visual quality approaching cinematic standards. Existing evaluation benchmarks, however, predominantly assess visual quality, aesthetic appeal and physical plausibility, while paying limited a

Omni-Embed-Mini: Binding Modalities Without Forgetting via Dense Distillation

👍 19

10/01 08:00

Extending a text embedding model to new modalities typically degrades text retrieval quality, and existing omni-modal embedders compensate with multi-billion parameters. We present Omni-Embed-Mini, a 0.9B-parameter model that maps text, speech, audio, images, video, and visually-rich documents into

AgSpec: Pushing the Limits of Retrieval-Based Speculative Decoding in Coding Agent Pipelines

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10/01 08:00

Retrieval-based speculative decoding (SD) drafts tokens by copying continuations from existing text, which suits coding agents that repeatedly reproduce code, logs, and earlier attempts. Yet existing methods fall short in agent pipelines: much of the reusable text is missing from their corpora or st

KaliBench: A Fine-Grained Benchmark for Cybersecurity Tool Use on Kali Linux with Runtime-Free Verifiable Rewards

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10/01 08:00

LLMs are increasingly applied to cybersecurity workflows, where they are expected to translate analysts' intent into tool invocations. However, existing evaluations focus on knowledge-based assessments or end-to-end agentic tasks, and do not directly measure LLMs' ability to generate executable comm

Honeycomb: Constant-Size Scene Memory Representation for Video World Models

👍 5

09/30 08:00

Video world models require persistent scene memory to maintain consistency during long-horizon video generation. Existing spatial memories accumulate RGB observations or latent features, increasing storage requirements as generation proceeds. We introduce Honeycomb, a video world model built on HexM

JevSpawn: Adaptive Agentic Inference through Compositional Action Spaces

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09/30 08:00

LLM agents generate intermediate reasoning and actions token by token, making extended interactions slow and computationally expensive. Jev-style models offer fast probabilistic predictions over finite fields, but require those fields to be specified in advance. This requirement limits autonomous ta

Architect-Ant: Editable Automatic Furnishing of Architectural Floor Plans

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09/30 08:00

Furnished floor plans support real-estate visualization, interior design, and architectural workflows, yet automatic furnishing remains challenged by limited real-world data and the need to satisfy interacting geometric and functional constraints. We ask whether professional furnishing knowledge can

PhysVista: Benchmarking Physical Intelligence in VLMs via a Perception-Reasoning-Assessment Loop

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09/30 08:00

Vision-Language Models (VLMs) have shown strong multimodal reasoning capabilities, yet whether they truly capture the physical consistency underlying real-world dynamics remains unclear. Existing benchmark paradigms often suffer from fragmented evaluation, focusing on isolated cognitive stages while

EgoTools: Towards Tool-Centric Reasoning in Real-World Egocentric Videos

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09/30 08:00

Real-world embodied tasks, from everyday activities to professional procedures, require agents to act under physical constraints while tracking evolving object and task states. Tool use sits at the heart of such tasks, as many everyday and professional activities are tool-mediated. Understanding the

Better Supervision Is Nearby: Neighborhood On-Policy Self-Distillation

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09/30 08:00

On-policy self-distillation (OPSD) trains mathematical reasoning models using a privileged teacher that sees a reference solution and supervises student-sampled prefixes. Standard OPSD uses one fixed parameter setting at every state, but nearby settings may offer additional supervision. We find that

MemFold: Learning Compact Soft Memory for Long-Context Personalization via On-Policy Optimization

👍 6

09/29 08:00

An assistant that serves the same user over a long horizon has to answer from what that user has revealed: which preferences still hold, which were revised, and which constraints apply now. Retaining that information is not the same as acting on it, and the two are usually optimized as if they were.

RLE-Bench: A Qualifying Exam for Coding Agents as Robot Learning Engineers

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09/29 08:00

Coding agents are beginning to move beyond purely digital tasks to tackle physical-world challenges, particularly in robotics. Existing robotics benchmarks, however, primarily focus on the performance of individual artifacts, such as policies or controllers, offering limited coverage of coding agent

Removing the NEEDLE in the Haystack: Backdoor Removal in LLMs via Weight Orthogonalisation

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09/29 08:00

Backdoor attacks can be implanted in Large Language Models (LLMs) during training, causing unwanted behaviour when a trigger appears in the input. Existing backdoor defences for LLMs attempt to remove the backdoor but inadvertently shift the model's output distribution to benign prompts, which can r

CorrGRPO: Correlation-Normalized GRPO for Multi-Reward Learning

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09/29 08:00

Group Relative Policy Optimization (GRPO) is widely used to train reasoning language models, where it computes advantages by centering and normalizing rewards across rollouts of the same prompt. For multiple rewards, GRPO sums the reward components and normalizes the total reward by its within-group

E-MoE: Enhanced Mixture-of-Experts for Non-Factorized Diffusion Language Models

👍 57

09/29 08:00

Masked diffusion models (MDMs) generate sequences by progressively unmasking several tokens per denoising step, but their reverse process is typically factorized over positions, limiting sample quality in the few-step regime where diffusion's speed advantage over autoregressive decoding matters most

Devils in Question Relay: Source-Conditioned Relay Steering to Mitigate Hallucinations in Audio-visual Large Language Models

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09/29 08:00

Audio-visual large language models (AVLLMs) have made remarkable progress in multimodal understanding and reasoning through interactions among visual, auditory, and linguistic information. However, recent studies show that AVLLMs face a critical challenge: source-confused grounding hallucination, wh

On-Policy or Off-Policy Learning? A Systematic Study of Distillation Dynamics

👍 153

09/28 08:00

On-policy learning has been argued to reduce catastrophic forgetting, produce sparser parameter updates, and improve generalisation. However, existing comparisons between supervised fine-tuning and reinforcement learning vary many factors simultaneously, making the contribution of rollout policy dif

When Does Correction Become Repair? Mechanistic Auditing of Internal Interventions in Tool-Using LLMs

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09/28 08:00

Before invoking external tools, an agentic LLM must select among a K-way action space: executing a call, seeking clarification, answering directly, or declining. While internal activation steering can alter these pre-execution decisions, conventional aggregate metrics obscure where altered states la

Replacing Large Language Models with Jev Decision Models for Low-Latency Edge Service Orchestration

👍 5

09/26 08:00

Natural-language service requests can require a language-model decision before execution starts, consuming part of the request's latency budget. We integrate Jev's decision-oriented application programming interface (API) into edge service orchestration to reduce this overhead while retaining servic

X-Tree: Tokenizing Reusable Experience for Efficient Agent Generalization

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09/26 08:00

Multi-step agents are trained on flat action streams: SFT and RLVR weight every token uniformly and ignore the sub-procedures that recur across tasks, the hierarchy that lets humans plan top-down from reusable routines. This structure sits unused, and flat training uses each scarce trajectory less f

OpenTumorBoard: A Real-World Benchmark of Multidisciplinary Tumor Board Discussion Trajectories

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09/26 08:00

Multidisciplinary tumor boards integrate multimodal clinical observations and longitudinal patient histories through specialist discussions, yet benchmarks rarely capture these real-world trajectories. We introduce OpenTumorBoard, a benchmark with 611 patient cases and 19,157 discussion turns across

Decentralized Master-Mind: Joint Action Refinement through Iterative Intent Denoising in Multi-Agent Pathfinding

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09/25 08:00

Decentralized multi-agent path finding (MAPF) with communication requires agents to reach individual goals without collisions under partial observability. Learnable policies trained on expert data provide an effective approach to this problem. However, when several coordinated joint actions are vali

The Rise of the Automation Engineer

@jakeserval · 1.1K 粉丝 · 406.0K 阅 · 505 赞 · 1.1K 转

10/01 22:00

There is a lot of talk about the jobs AI takes away and very little about the ones it creates. While pessimism might be easier (and certainly gets more clicks), I’m more optimistic. From where I sit,

中文介绍 探讨AI创造的新工作机会，而非取代的工作。

here's how to make viral videos with Seedance 2.5

@0xROAS · 54.6K 粉丝 · 118.6K 阅 · 502 赞 · 56 转

10/02 01:58

Seedance 2.5 is one of the craziest "nano banana moments" of AI VIDEO in 2026. It's the model behind every viral video that you are seeing right now... and it's pretty simple to generate those video,

中文介绍 Seedance 2.5生成病毒视频教程，简单易用。

Own your AI, don’t let it own you

@0xSigil · 56.0K 粉丝 · 79.1K 阅 · 509 赞 · 72 转

10/02 06:12

6 months ago, the #1 AI was Claude Opus 4.6. Our model, Underdog 27B beats it while running on your Mac or iPhone. Most AI will run on your device, not in data centers. Intelligence that recently

中文介绍 介绍Underdog 27B AI模型，在个人设备上超越Claude Opus 4.6。

Designing MCP Gateway Uber's MCP Management Platform

@UberEng · 66.9K 粉丝 · 54.0K 阅 · 529 赞 · 59 转

10/03 01:21

Introduction Uber’s rapid adoption of AI agents has fundamentally changed how teams interact with code, data, and operational systems. Early ad-hoc integrations with the MCP (Model Context Protocol)

中文介绍 Uber的MCP Gateway设计，AI代理如何改变团队与代码、数据交互。

How to build a content machine with Opus 5.5 (Full Course)

@VibeMarketer_ · 37.8K 粉丝 · 31.4K 阅 · 504 赞 · 59 转

10/02 22:06

i'm going to show you how to build a content machine with Opus 5.5 that turns your ideas, research and expertise into articles, posts and newsletters in your own voice. from finding your next topic to

中文介绍 Opus 5.5构建内容机器教程，将想法转化为文章和通讯。

Reinforcement Learning from scratch #1

@goyal__pramod · 11.4K 粉丝 · 24.7K 阅 · 504 赞 · 59 转

10/03 12:45

Now I am aware you must have been looking forward to the second part of my CUDA blog (if you haven't read it yet, check it out!), but hey! A man can have varied interests. And I believe if you are

中文介绍 CUDA博客第二部分，介绍从头开始进行强化学习。

OpenAI Withheld GPT-6.1 Astra. It Exposed AI’s Permission Problem.

@ActionModelAI · 60.2K 粉丝 · 6.8K 阅 · 501 赞 · 439 转

10/01 21:24

OpenAI has chosen not to release GPT-6.1 Astra after the model failed to meet its safety standards. To be clear, GPT-6.1 Astra is not GPT-6.1 Sol, the model OpenAI released at DevDay. GPT-6.1 Sol has

中文介绍 OpenAI未发布GPT-6.1 Astra，暴露AI权限问题。

The Agent Said It Was Done. The Database Disagreed.

Hugging Face Blog · 10/04 06:56

中文介绍 微软发布思考箱模型，数据库出现分歧。

[AINews] not much happened today

Latent Space · 10/03 16:45

a quiet day.

中文介绍 今日市场平静。

A model guide for the GPT-6 family

OpenAI News · 10/03 00:15

Learn how startups can choose GPT-6 models, tune reasoning effort, improve prompts and skills, coordinate tools, and prepare workflows for production.

中文介绍 OpenAI发布GPT-6系列模型构建指南。

Redefining enterprise intelligence with autonomous AI

MIT Tech Review AI · 10/02 23:49

Enterprise AI is no longer a future ambition. It is in full operational flight. Model capabilities are advancing faster than most organizations can absorb, while the cost of performance continues to fall. Globally, AI investment is set to reach $2.5 trillion in 2026, up 44% from the previous year. F

中文介绍 企业AI应用全面启动，预计2026年全球投资将达2.5万亿美元，增长44%。

Open-sourcing AstaBrief, the fast report-generation model in Asta

Hugging Face Blog · 10/02 23:19

中文介绍 Hugging Face开源AstaBrief快速报告生成模型。

Inside-Out AI: Rebuilding Airbnb Behind the Scenes and Across the Guest Experience

Latent Space · 10/02 22:04

After leading Meta’s Llama models, Ahmad Al-Dahle is now transforming Airbnb with AI — from how its teams develop products to how it serves guests.

中文介绍 Ahmad Al-Dahle领导Airbnb应用AI技术，从产品开发到客户服务全面升级。

Don’t be fooled—LLMs don’t reason

MIT Tech Review AI · 10/02 16:00

On an afternoon in Seoul in March 2016, I watched a program I helped build put a stone on the fifth line of a Go board in what looked like a gift to its human opponent. Move 37 in game two of the five-game match looked so absurd that some commentators thought it was a…

中文介绍 LLM模型不具备推理能力。

[AINews] Pi 1.0, Pi Durable, and AIE NYC

Latent Space · 10/02 14:40

the minimalist harness goes stable... and TypeScript!

中文介绍 Pi 1.0、Pi Durable和AIE NYC发布， minimalist harness稳定，支持TypeScript。

AutoSynthData: Generating Training Data for Enterprise Agents

Hugging Face Blog · 10/02 12:01

中文介绍 Hugging Face发布AutoSynthData，为企业代理生成训练数据。

Academia is for Ambition — Alex Zhang, MIT

Latent Space · 10/02 08:28

We catch up with RLM first author Alex Zhang, MIT PhD, on Jev, PhD masxing, and the future of harnesses.

中文介绍 RLM第一作者Alex Zhang讨论Jev、PhD masxing和未来马具的发展。

Chatham scales its capital markets expertise with OpenAI

OpenAI News · 10/02 08:00

Chatham Financial uses Codex and GPT-5.6 to build technology and redesign workflows, cutting trade validation from 30 minutes to under 4.

中文介绍 Chatham Financial利用OpenAI技术优化资本市场，将交易验证时间缩短至4分钟以下。

Decision models 🤖, Claude-shaped science 🧪, OpenAI safety firings 🚨

TLDR AI · 10/02 08:00

中文介绍 决策模型、Claude-shaped科学、OpenAI安全事件。

The eternal complement

OpenAI News · 10/02 01:00

Advanced AI may matter most for the routine work behind breakthrough ideas. Explore why execution could shape the next economy and the pace of progress.

中文介绍 高级AI在突破性想法背后的日常工作中可能最为重要。

How Albertsons Companies is reimagining retail from the inside out

OpenAI News · 10/02 00:00

Albertsons Cos. is using ChatGPT Enterprise and the OpenAI API to help teams work faster and make grocery shopping easier for millions of customers.

中文介绍 Albertsons Cos.利用ChatGPT和OpenAI API优化零售业务。

[AINews] Gemini 4 Argon: GDM’s answer to Astra/Fable, with 1M output

Latent Space · 10/01 14:45

... but you can’t try it yet unless you are “government users and trusted cyber defenders in the Fairwind Program”

中文介绍 Gemini 4 Argon发布，但仅限政府用户和受信任的网络安全防御者测试。