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Исследования1 мин

Compiling VGDL into Causal Models

arXiv:2609.05459v1 Announce Type: new Abstract: Reinforcement learning and large language models often struggle to accurately capture the causal mechanics of game environments. Standard reinforcement learning agents tend to rely on spurious correlations, while large language…

arXiv — cs.AI
Исследования1 мин

RAPID: Reliability-Aware Pair Importance Distillation

arXiv:2609.05481v1 Announce Type: new Abstract: Inter example relational distillation transfers a teacher's representation geometry by matching relations among examples within a mini batch. Computing all pairs has quadratic complexity in the batch size, whereas uniform…

arXiv — cs.AI
Исследования1 мин

When and What to Teach: Budget-Aware Online Adaptation for Web Agents

arXiv:2609.05513v1 Announce Type: new Abstract: Web agents have achieved significant success in automating complex internet tasks but deploying them in real-world environments requires continuous online adaptation. Given that deploying powerful proprietary models remains…

arXiv — cs.AI
Исследования1 мин

Deep belief networks are exact

arXiv:2609.05572v1 Announce Type: new Abstract: We prove that every strictly positive probability distribution on \(\{-1,1\}^n\) is represented exactly by a sigmoid belief network with finite parameters. This answers a question of Sutskever and Hinton. The proof upgrades their…

arXiv — cs.AI
Исследования1 мин

EnvCraft: Synthesizing Executable Environments in Agentic RL for Claw-like Agent

arXiv:2609.05576v1 Announce Type: new Abstract: The paradigm of LLMs has rapidly shifted from passive language interfaces to autonomous Claw-like agents that execute long-horizon tasks across stateful workspaces. While Agentic Reinforcement Learning (Agentic RL) provides a…

arXiv — cs.AI
Исследования1 мин

Planning and Scheduling Business Processes under Control-Flow Uncertainty

arXiv:2609.05578v1 Announce Type: new Abstract: Scheduling activities in business processes can improve efficiency (e.g., reduce makespan), but is challenging because the exact sequence of activities required to complete a case is often uncertain due to decisions based on data…

arXiv — cs.AI
Исследования1 мин

Damage-Aware Bandit Pruning for Vision and Language Transformers

arXiv:2609.05448v1 Announce Type: new Abstract: Structured post-training pruning of transformers requires selecting complete functional units whose suppression causes limited degradation. We formulate structured-unit selection for language and vision transformers as a…

arXiv — cs.AI
Стартапы1 мин

Recovering Temporal and Geographic Signals from Language Model Embeddings

arXiv:2609.05721v1 Announce Type: new Abstract: Understanding whether language-model embeddings encode structured real-world information is important for both representation analysis and information retrieval. We study this question for temporal and geographic signals using a…

arXiv — cs.AI
Исследования1 мин

CUSP: Decomposable Collective Uncertainty for Multi-Agent Multimodal Reasoning

arXiv:2609.05708v1 Announce Type: new Abstract: Aggregating heterogeneous vision-language models (VLMs) can improve multimodal reasoning, but neither an individual model's confidence nor that of the aggregated answer measures reliability at the system level. We present CUSP…

arXiv — cs.AI
Исследования1 мин

Beyond Prompts: Measuring and Optimizing LLM Tool-Agent Harnesses

arXiv:2609.05736v1 Announce Type: new Abstract: LLM tool agents can be improved without retraining by modifying the runtime harness around a fixed model: prompts, tool interfaces, middleware, state handling, and recovery logic. We study this setting as resource-bounded harness…

arXiv — cs.AI
Исследования1 мин

CriticGen: Generation-Aware Evaluation as Actionable Feedback

arXiv:2609.05439v1 Announce Type: new Abstract: Current evaluation methods for large language models are coarse-grained and decoupled from generation, producing generic explanations that fail to provide actionable feedback for model improvement. We propose CriticGen, a…

arXiv — cs.AI
Исследования1 мин

What OpenAI’s latest controversy tells us about the future of math

OpenAI’s latest mathematical milestone has quickly become mired in controversy. Today, the company announced that its agents have solved one of the Millennium Prize Problems, some of the most important open problems in mathematics. Under normal circumstances, that solution would…

MIT Technology Review — AI (topic feed)
База знаний1 мин

DHH on OpenClaw, Grok Bot, and personal AI agents | Lex Fridman Podcast Clips

Lex Fridman Podcast full episode: https://www.youtube.com/watch?v=NYFGCESmikA Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/cv10038-sb See below for guest bio, links, and to give feedback, submit questions, contact Lex, etc. *GUEST BIO:* DHH…

YouTube — Lex Fridman Podcast
Исследования1 мин

Why this month's Microsoft patch release is a doozy

Microsoft’s patch for September is a doozy, with a record number of roughly 972 vulnerabilities fixed and 112 of them meeting the high critical-severity threshold. It was only two months ago that Microsoft patched a then-record 570 vulnerabilities. Then, last month, Microsoft…

Ars Technica — AI
Исследования1 мин

Drama swirls around OpenAI’s legendary mathematical milestone

OpenAI says it found a solution to a major math problem that has remained unsolved for around 90 years, as reported earlier by The New York Times and Wired. In a blog post on Tuesday, OpenAI announced that it discovered a solution to the Navier-Stokes problem - which relates to…

The Verge — AI
Исследования1 мин

ChatGPT Sketch turns your bad drawings into detailed AI images

I used ChatGPT and its Sketch tool to make this AI-generated image of a cat. OpenAI announced ChatGPT Images 2.5 on Tuesday and is adding a new way to tell ChatGPT what you want it to make an image of: by drawing a doodle. With a new feature called Sketch, you can just draw…

The Verge — AI
База знаний1 мин

Claude + Higgsfield: How to Make Motion Graphics with AI (Full AI Workflow)

Try Seedance 2.5 on Higgsfield https://higgsfield.ai/s/seedance-2-5-iamaimaster-DzjKTy 🎬 Learn more about AI video creation → https://aimaster.me/yt/motion_graphics 🤝 Exclusive brand partnership - https://aimaster.me/collab I ran 6 AI motion graphics builds back to back inside…

YouTube — AI Master
База знаний1 мин

Introducing GPT-Image-2.5 in the API

Meet Sunburst and Flare, our two new GPT-Image-2.5 models. Sunburst brings sharper details, more natural lighting, and greater control across edits. Flare delivers high quality images over 50% faster. Both support transparent backgrounds for assets ranging from infographics to…

YouTube — OpenAI Official