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Все опубликованные аналитические материалы, исследования суверенного стека, новости экосистемы и обзоры моделей ИИ.

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Исследования1 мин

InvestigationWorlds: An Agentic Environment for Legal Investigation

We introduce InvestigationWorlds, an agentic environment for legal investigation. We build on an underused artifact of U.S. civil litigation: the summary judgment motion. This motion relies upon a record composed of real evidence exhibits, and results in a court-adopted…

arXiv — cs.AI
Исследования1 мин

The Cost of a Hop: Benchmarking NLIP and A2A

Autonomous agents built on Large Language Models (LLMs) need standardized protocols to interoperate across systems. Several now exist (A2A, MCP, ACP, ANP, NLIP), but the Natural Language Interaction Protocol (NLIP) has not appeared in any controlled performance study, and no…

arXiv — cs.AI
Исследования1 мин

Reinforcement Learning with Comparative Evidence for Social Intelligence

Developing socially intelligent AI remains heavily dependent on human-annotated data, limiting the scale and breadth of social understanding models can acquire. Methods that derive training signals from unlabeled data offer a path beyond this dependence, but social predictions…

arXiv — cs.AI
Исследования1 мин

REACT: Physically and Chemically Consistent Reconstruction of Marine Active Tracers

Reconstructing global sea surface pH from sparse observations is critical for monitoring ocean acidification and understanding marine carbon cycling. Traditional assimilation and inverse models are physically grounded but costly for large-scale reconstruction. Recent black-box…

arXiv — cs.AI
Исследования1 мин

The Independence Prior of SAEs Fragments Visual Concepts

Sparse Autoencoders (SAEs) decompose model activations into sparse combinations of interpretable dictionary atoms. Although SAEs are grounded in the Linear Representation Hypothesis (LRH), their objective smuggles in an additional prior: concepts across patches are treated as…

arXiv — cs.AI
Исследования1 мин

MLLMs Fail to Refuse when Using Tools Agentically

Agentic multimodal large language models (MLLMs) have recently pushed the frontier of visual reasoning by calling tools such as zooming and tagging. Despite the recent strong success of agentic MLLMs, this work uncovers a critical safety failure in the tool-use paradigm: agentic…

arXiv — cs.AI
Исследования1 мин

CUAWright: A Minimal Unified Interface for Digital Agents

The prevailing approach to computer-use agents couples a model with a domain-specific harness: a browser or desktop environment equipped with human engineered tools that are fixed before task execution. As models' coding capabilities improve, the GUI native and static harness…

arXiv — cs.AI
Исследования1 мин

Discrete Diffusion for Large Graph Generation via Structural Candidate Restriction

Synthesizing realistic graphs at scale is vital when the graphs of interest are large and real-world samples are limited or access-sensitive. Diffusion-based generators have recently driven much of the progress, offering high modeling capacity, but most such methods have…

arXiv — cs.AI
Исследования1 мин

Exploration-Preserving Policy Optimization

Reinforcement learning with verifiable rewards improves reasoning, while the allocation of learning signal shapes which solutions remain accessible under repeated sampling. Group-relative objectives assign equal advantages to equally rewarded responses, making aggregate credit…

arXiv — cs.AI
Исследования1 мин

SGAnalog: An End-to-End Circuit Benchmark from Open-Source Silicon Tapeouts

Existing analog integrated circuit design benchmarks make two questions hard to answer: whether a model has learned transferable circuit skills rather than recalled familiar examples, and whether its output works under defined process and test conditions. We introduce a…

arXiv — cs.AI
Исследования1 мин

Proxy Confidence: Auditing Black-Box LLM Agents with a Surrogate's Log-Probabilities

A deployed LLM agent emits tool calls, queries, and code that can be silently wrong -- by the time the error surfaces, the action has run. Frontier chat APIs hide the model's token probabilities; the agent's stated confidence barely beats chance on the mistakes that matter; and…

arXiv — cs.AI
Исследования1 мин

Training Numerical Intelligence via Auto-Diagnosis and Skill Discovery

AI agents are becoming increasingly capable of generating scientific code, but generating code is not the same as improving the algorithms behind it. For numerical solvers, execution feedback can expose poor performance, but rarely reveals its underlying cause and how to address…

arXiv — cs.AI
Исследования1 мин

Teaching Agents to Code Reliably

Autonomous coding agents solve repository issues by reading code, running commands, editing files, and submitting patches. Extra inference-time compute yields gains only when it produces a useful repair and supplies reliable evidence for choosing one. Three behaviors decide…

arXiv — cs.AI
Исследования1 мин

Ornith 1.5 35b-a3b | Достойная повседневная модель

Привет. И сегодня у меня наконец-таки спустя, наверное, почти месяц, если не больше, модель полтора 35 би. Когда я снял видос про девятимиллиардную версию этой модели, я тогда офигевал от того, что она может, учитывая её размер, учитывая, где её можно запустить и что я с ней мог…

YouTube — Amorev
Исследования1 мин

ChatGPT начнет помечать тексты невидимыми водяными знаками

OpenAI в ближайшие недели начнет добавлять невидимые водяные знаки в текстовые ответы ChatGPT и Codex в Евросоюзе. Маркировка поможет определить, использовались ли инструменты компании при создании текста, говорится в сообщении OpenAI. На первом этапе нововведение затронет…

Kursiv Media Tech
Исследования1 мин

MCP for agent-to-agent comms may be the riskiest protocol you've never heard of

The adoption of AI agents in millions of organizations is creating new opportunities for attackers to make them take malicious actions, such as exfiltrating database contents and sensitive business and personal information. In the past five months, Google and four other…

Ars Technica — AI
Исследования1 мин

Саясат Нурбек принял участие в круглом столе министров науки и технологий STS Forum 2026

Конкурентоспособность государств все в большей степени определяется способностью эффективно развивать человеческий капитал, создавать условия для научных открытий и обеспечивать практическое применение новых технологий.

Profit.kz — тег «Искусственный интеллект»
Исследования1 мин

All the drama around AI’s takeover of mathematics

This past year, OpenAI, Anthropic, and other labs have announced breakthroughs on numerous long-standing mathematical problems, in some cases pushing well beyond what researchers expected current systems to be capable of — including resolving one of the famous Millennium Prize…

The Verge — AI
Исследования1 мин

OpenAI is adding text watermarking in ChatGPT and Codex

An invisible, machine-readable watermark in text output is rolling out to ChatGPT and Codex, but only for users in the European Union at first. OpenAI says its textGrain watermarking "matched or exceeded" other approaches like Google DeepMind's SynthID for text, which is also…

The Verge — AI