Publication Catalog

所有文章

All published intelligence, sovereign stack research, ecosystem news, and AI foundation model reviews.

8145
Stories
Исследования1 мин

Anthropic introduced Claude Duet, an autonomous AI agent

Anthropic has introduced a new AI-agent called Claude Duet. It is designed to make everyday work easier for professionals and small business owners: they can schedule meetings, make financial forecasts and develop web applications, reports Tech-news. Claude Duet's main…

Tech-news.kz
Исследования1 мин

Anthropic 推出了 Claude Duet,一款无需永久命令即可工作的个人 AI 代理

⚡️ Anthropic 推出了 Claude Duet,这是一款无需永久命令即可工作的个人人工智能代理。新服务建立在Claude Opus 5.5的基础上,将成为OpenAI和Grok Bot的Dots的竞争对手。 Duet 在云中运行,使用浏览器和连接的应用程序,并执行...

Telegram — GPT Time | Нейросети | ИИ
Стартапы1 мин

社会影响:您现在就可以使用 astanahub.com 平台上的 5 个功能!

💙 社会影响:您今天就可以使用 astanahub.com 平台上的 5 个功能!我们收集了 5 项可供 Astana Hub 生态系统参与者参与的社会影响活动: 📝 分享您的经验 — 关于您在 astanahub.com 平台上参与 AI & Digital Bridge 2026 的经历……

Telegram — Astana Hub
Исследования1 мин

Automating ML for Science: Can Frontier Agents Climb Scientific Hills in the Wild?

arXiv:2610.28763v1 Announce Type: new Abstract: Frontier coding agents are increasingly framed as end-to-end automated researchers, and ML for science offers a demanding test of that promise: improving a scientific model often requires domain insight beyond routine ML…

arXiv — cs.AI
Исследования1 мин

DiffResearch: Accelerating Deep Research with Diffusion Language Models

arXiv:2610.28909v1 Announce Type: new Abstract: Deep research systems iteratively plan, gather evidence, synthesize, and revise, making end-to-end latency a key bottleneck for interactive use. Almost all production systems are built on autoregressive (AR) language models and…

arXiv — cs.AI
Исследования1 мин

Simply Logical -- The First Three Decades

arXiv:2610.28912v1 Announce Type: new Abstract: This paper charts the evolution of the Prolog textbook Simply Logical -- Intelligent Reasoning by Example from print with runnable programmes on a 3.5-inch diskette published in 1994, via various intermediate online versions, to…

arXiv — cs.AI
Исследования1 мин

Self-Improving Agents with World Model Predictive Paths

arXiv:2610.28945v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly expected to interact with environments and improve their decisions during deployment. However, how anticipating future outcomes and drawing on accumulated interaction experience…

arXiv — cs.AI
Исследования1 мин

Speedrunning Relational Foundation Model Pretraining

arXiv:2610.28855v1 Announce Type: new Abstract: Progress on foundation model pretraining is gated by who can afford a trial, and relational pretraining is no exception. Recipes are developed inside individual labs, reported under private protocols, and do not accumulate.…

arXiv — cs.AI
Исследования1 мин

To Manipulate or Not: Opinion Dynamics in LLM Interactions

arXiv:2610.28875v1 Announce Type: new Abstract: Large language models increasingly take part in extended conversations where they can both shape and be shaped by another party's views, yet most persuasion research measures only one side of that exchange. We introduce a…

arXiv — cs.AI
Исследования1 мин

GRAIL: From Saliency to Semantics in Time-Series Explanation

arXiv:2610.29036v1 Announce Type: new Abstract: Explaining a time-series model requires both locating the evidence and extracting meaningful knowledge from it. Yet a single timestep is not a semantic unit: the meaningful patterns live across many samples, not in any one of them.…

arXiv — cs.AI
Исследования1 мин

Does Every Instance Count Equally? Order Effects in LLM Multi-Instance Processing

arXiv:2610.29057v1 Announce Type: new Abstract: Users increasingly rely on large language models (LLMs) to analyse collections of independent inputs, such as product reviews or social media posts, and return a single aggregated answer. This setting requires multi-instance…

arXiv — cs.AI
Исследования1 мин

Behavior Beyond Text: Evaluating Refusal Transfer Failure in LLM Agents

arXiv:2610.28982v1 Announce Type: new Abstract: While large language models are increasingly deployed as tool-calling agents, their safety evaluations still focus primarily on their ability to refuse harmful requests in text. We investigate whether the refusal behavior in text…

arXiv — cs.AI
Исследования1 мин

Fig: Automated Multiagent Behavior Elicitor

arXiv:2610.28891v1 Announce Type: new Abstract: Many social evaluations for multiagent systems study behaviors as they emerge from environments instead of systematically intervening in the environment to elicit such behaviors. We introduce Fig (Finding Interactions in Games), an…

arXiv — cs.AI
Исследования1 мин

GenXR-Bench: Benchmarking Coding Agents for Interactive XR Development

arXiv:2610.29014v1 Announce Type: new Abstract: Coding agents are rapidly advancing from single-file generation to long-horizon repository-scale engineering, yet the evaluation of their capabilities to author interactive extended reality (XR) applications remains an open…

arXiv — cs.AI
Исследования1 мин

Inheritance as an Admission Test for LLM Prompt Merge Operators

arXiv:2610.29023v1 Announce Type: new Abstract: Large language model (LLM) agents are often improved by iterating until a fixed verifier is done. Once that verifier saturates, the loop has nothing left to climb. We instead score agents against the current population, and a…

arXiv — cs.AI