Исследования1 мин
From 30 to 3 days: AI accelerated cancer screening in Kazakhstan - 24.kz
С 30 до 3 дней: ИИ ускорил онкоскрининг в Казахстане - 24.kz.
24.kz
Publication Catalog
所有文章
All published intelligence, sovereign stack research, ecosystem news, and AI foundation model reviews.
2730
Stories
Политика и регулирование1 мин
От 30 дней до 3 суток: ИИ ускорил проверку на рак в Казахстане - Kursiv Media Казахстан: последние новости Казахстана и мира
От 30 дней до 3 суток: ИИ ускорил проверку на рак в Казахстане - Kursiv Media Казахстан: последние новости Казахстана и мира.
Kursiv Media Tech
Стартапы1 мин
ИИ и защита от мошенников: что обсудят на CAFS 2026 в Алматы - DKNews.kz
ИИ и защита от мошенников: что обсудят на CAFS 2026 в Алматы - DKNews.kz.
DKNews.kz
Исследования1 мин
The Equation That Might Destroy Itself
I did not think I would live to see the day when this mathematical problem gets solved and I just did likely. So, I am kind of sitting here in disbelief. Something that nobody has ever been able to prove the Navier-Stokes existence and smoothness problem has been very likely…
YouTube — Two Minute Papers
Исследования1 мин
we JUST got played...
Итак, нам нужно это обсудить. Буду с вами честен, я очень зол из -за всей этой ситуации. Сейчас расскажу почему. Это Джейкоб Коксон. Он уволился из Anthropic, заявив, что ни OpenAI, ни Anthropic не понимают, что делают. Они играют с нашими жизнями, и ИИ может погубить нас всех к…
YouTube — Wes Roth
Исследования1 мин
Can destroy all of us” - the scientist left Anthropic and made a disturbing statement about AI
“Can destroy all of us” - the scientist left Anthropic and made a disturbing statement about TengriNews AI
Tengrinews — AI (Google News)
Исследования1 мин
可能会毁灭我们所有人”——科学家离开人类并对人工智能做出令人震惊的声明
“可能会毁灭我们所有人”——科学家离开 Anthropic，并对 AI TengriNews 发表令人震惊的言论
Tengrinews — AI (Google News)
Исследования1 мин
Introducing ChatGPT for Financial Services
Introducing ChatGPT for Financial Services, combining built-in financial data and GPT-6 Astra for research, modeling, and client-ready materials.
OpenAI Blog
Политика и регулирование1 мин
Expanding AI access and cyber defense for federal, state, local, and tribal governments
OpenAI and GSA will offer eligible federal, state, local, and tribal governments $0 license fees, 50% off usage, and expanded cyber defense support.
OpenAI Blog
Исследования1 мин
Black-Box Red Teaming of Agentic AI: A Taxonomy-Driven Framework for Automated Risk Discovery
arXiv:2609.09647v1 Announce Type: new Abstract: Agentic systems are rapidly moving to production, where they read untrusted inputs, call tools with real permissions, and act autonomously, expanding the security surface beyond chat-only models. Yet standard evaluations remain…
arXiv — cs.AI
Исследования1 мин
LexAgentHallu: A Hierarchical Benchmark for Profiling Hallucinations in Legal Agents
arXiv:2609.09754v1 Announce Type: new Abstract: As large language models are increasingly deployed as tool-augmented legal agents, they introduce agentic hallucinations where tool-call and reasoning errors cascade into fabricated holdings and miscited authority. However,…
arXiv — cs.AI
Исследования1 мин
Decision-Focused Active Learning for Scale-Aware Critical-Materials Recovery
arXiv:2609.09413v1 Announce Type: new Abstract: Choosing a recovery process for scale-up requires connecting laboratory results with product requirements, process costs, and scale effects. We analyze records from Pacific Northwest National Laboratory's Computer Intelligence for…
arXiv — cs.AI
Исследования1 мин
ContractEval: Query-Conditioned Execution Matching for Procedural Instruction Conformance
arXiv:2609.09458v1 Announce Type: new Abstract: As LLM agents move from answering questions to carrying out procedures, failures can be unwarranted rather than visibly wrong: the final response looks acceptable even though the system skipped the check, branch, dependency, or…
arXiv — cs.AI
Исследования1 мин
OpenDiscoveryTrace: Process Traces for Evaluating AI Scientist Workflows
arXiv:2609.09203v1 Announce Type: new Abstract: Existing benchmarks for autonomous AI scientists evaluate only final outputs---generated code, hypotheses, or papers---yet discard the reasoning process by which those outputs were obtained. This makes it impossible to audit…
arXiv — cs.AI
Исследования1 мин
RobustSGPO: Search-Space Control for Agent Harness Evolution
arXiv:2609.09646v1 Announce Type: new Abstract: Semantic-gradient-based prompt optimization (SGPO) improves agent harnesses using execution feedback, but its local update rule leaves the choice of edit scope and operation unresolved. We introduce RobustSGPO, which specifies the…
arXiv — cs.AI
Исследования1 мин
PRAGMA: Evaluating Personalized Guidance with Memory Alignment in Lifelong Conversations
arXiv:2609.09664v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as personalized assistants that interact with users over extended periods of time. As conversations grow longer, relying on full interaction histories becomes increasingly…
arXiv — cs.AI
Исследования1 мин
Seven Sources of Physical AI Capability Formation
arXiv:2609.09627v1 Announce Type: new Abstract: Capabilities relevant to Physical AI can arise from materially different formation histories, yet existing taxonomies organized by morphology, architecture, learning algorithm, task, or domain do not directly answer what gives rise…
arXiv — cs.AI
Исследования1 мин
Adaptive Entangled Game Modules in Artificial General Intelligence
arXiv:2609.09226v1 Announce Type: new Abstract: We introduce a probability-wave framework for modeling the collective behavior of interacting adaptive agents, deriving testable eigenmodes through a generalized behavioral intelligence (GBI) nonlocal probability-wave equation.…
arXiv — cs.AI
Исследования1 мин
Safe to Stop? Risk-Constrained Stopping for Sequential Clinical Diagnosis Agents
arXiv:2609.09678v1 Announce Type: new Abstract: Clinical diagnosis agents must decide not only what test to request next, but also when to diagnose or defer. Existing agent benchmarks largely evaluate accuracy after fixed or unconstrained interaction, leaving autonomous stopping…
arXiv — cs.AI
Исследования1 мин
Which Tokens Should SFT Actually Learn? A Token-Trimming Perspective on Mathematical Reasoning
arXiv:2609.09707v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) applies a uniform cross-entropy loss to all target tokens, even though different tokens provide unequal learning signals for mathematical reasoning. This uniform treatment can over-sharpen already…
arXiv — cs.AI
Исследования1 мин
Subagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks
arXiv:2609.09233v1 Announce Type: new Abstract: How can language model agents effectively leverage libraries of reusable knowledge to solve long-horizon tasks? Recent work has increasingly focused on agent skills: reusable capabilities represented as skill packages, i.e.,…
arXiv — cs.AI
Исследования1 мин
Multi-Agent Agentic Graph Learning via Structural Signatures
arXiv:2609.09565v1 Announce Type: new Abstract: Agentic graph learning (AGL) has recently achieved promising results on graph reasoning tasks, where an agent powered by a large language model (LLM) sequentially samples the graph as evidence to support its final prediction.…
arXiv — cs.AI
Исследования1 мин
RESCUE-BENCH: Towards Relation-Aware Multi-Party Emotional Support Conversation Systems
arXiv:2609.09657v1 Announce Type: new Abstract: Existing emotional support conversation systems mainly focus on one-on-one seeker-supporter interactions and individual emotional states, leaving interpersonal relations in multi-party scenarios underexplored. In this work, we…
arXiv — cs.AI
Исследования1 мин
Can Artificial Intelligence Support Healthcare and Mental Health Through Early Cyberbullying Detection ? The Impact of Emotion-Aware AI on Proactive Online Safety
arXiv:2609.09735v1 Announce Type: new Abstract: Healthcare systems, mental health, and public well-being are increasingly affected by cyberbullying and harmful online interactions. This paper presents CareGuard, an early-warning framework designed to support healthcare-driven…
arXiv — cs.AI
Исследования1 мин
CityPlanner: A Sandbox Agent for Executable Urban Planning
arXiv:2609.09578v1 Announce Type: new Abstract: Urban planning is a real-world spatial optimization problem that requires selecting feasible actions from large candidate spaces under practical objectives such as cost and service quality. Existing optimization and reinforcement…
arXiv — cs.AI
Исследования1 мин
Gradland: On Phenomenal Experience, Differentiated Across Many Dimensions
arXiv:2609.09306v1 Announce Type: new Abstract: This paper investigates the hypothesis that the first-order structure of physical interactions, i.e. gradients or Jacobians, characterizes the structure of phenomenal experience. It does so in an idealized world inhabited by neural…
arXiv — cs.AI
Исследования1 мин
The Menu Is an Execution Prior: State-Path Tool Menus for Online Agents
arXiv:2609.09395v1 Announce Type: new Abstract: Language models act through tools, yet practical agents face libraries containing thousands of interfaces. We introduce the tool menu as the short, ordered subset of available tools shown to an agent before execution. The agent can…
arXiv — cs.AI
Исследования1 мин
XAI-Arena: Can LLMs Assess the Quality of XAI Explanations?
arXiv:2609.09428v1 Announce Type: new Abstract: Evaluating the quality of explanations produced by explainable AI (XAI) methods remains challenging because existing approaches often rely on subjective human judgment, limiting reproducibility, scalability, and comparability…
arXiv — cs.AI
Исследования1 мин
An Autonomous GeoAI Agent for Arctic Eco-Navigation
arXiv:2609.09374v1 Announce Type: new Abstract: Arctic maritime navigation is becoming increasingly important as changing sea-ice conditions expand seasonal accessibility while simultaneously introducing substantial operational, environmental, and community risks. Arctic route…
arXiv — cs.AI
Исследования1 мин
Valerant: An Automatic Navigable Game Map Generator via Action-Conditioned World Model Exploration
arXiv:2609.09418v1 Announce Type: new Abstract: World Action Models (WAMs) couple predictive world modeling with action generation, allowing anticipated future states to guide agent behavior. Although WAMs are rapidly advancing embodied AI, general-purpose counterparts remain…
arXiv — cs.AI