Research1 мин
У Claude Code начинает появляться собственная экосистема модов. 🏎
У Claude Code начинает появляться собственная экосистема модов.
Telegram — Вайб-кодинг
Publication Catalog
All stories
All published intelligence, sovereign stack research, ecosystem news, and AI foundation model reviews.
2709
Stories
Policy & regulation1 мин
Tokayev and the Prime Minister of South Korea were shown an air taxi for Alatau
President of Kazakhstan Kassym-Jomart Tokayev and Prime Minister of South Korea Han Sung-sook got acquainted with the Alatau Smart City projects. They were shown an air taxi control system created with the participation of Korean companies. During the presentation the main…
Kursiv Media Tech
Research1 мин
Claude Is Now Leaving Invisible Fingerprints In Its Text
Images can be watermarked for copy protection. Now, get this. Claude AI announced that they are watermarking the text you generate with it. From when? When does this start? Well, Anthropic is rolling this out right now. Yep. I am not talking about this because I agree with it,…
YouTube — Two Minute Papers
Policy & regulation1 мин
Казахстан создаст полноценную индустрию цифрового майнинга
Казахстан планирует перейти от наращивания майнинговых мощностей к созданию полноценной индустрии цифрового майнинга. В нее войдут криптобиржа, инструменты для работы с цифровыми активами, токенизация, хранение активов и платежные решения, передает Tech-news. Такое поручение на…
Tech-news.kz
Research1 мин
Archives of Kazakhstan and Korea agreed on cooperation in the field of AI and digitalization - Kazinform
Archives of Kazakhstan and Korea agreed on cooperation in the field of AI and digitalization Kazinform
Inform.kz
Research1 мин
AI safety requires more than just slowing down our pace
The article raises questions about the need for AI security measures amid recent events, including the resignation of a researcher from Anthropic and growing concerns about uncontrolled progress in AI. Anthropic CEO Dario Amodei proposes a three-step plan...
Digital Donut AI Digest
Telegram — Hackalem
Research1 мин
Инженер DeepSeek заявил, что не хочет, чтобы Anthropic получила контроль над AGI.
Инженер DeepSeek заявил, что не хочет, чтобы Anthropic получила контроль над AGI..
Telegram — Вайб-кодинг
Research1 мин
Why does Kazakhstan need scientists capable of working at the intersection of science, AI and automation - forbes.kz
Зачем Казахстану ученые, способные работать на стыке науки, ИИ и автоматизации - forbes.kz.
Forbes.kz (Google News)
Research1 мин
Vibe Patenting: Evaluating LLM Judges for Professional Patent-Drafting Agents
LLM judges are increasingly used to evaluate and improve AI-generated outputs, yet their reliability for complex professional work remains unclear. We study this problem through Vibe Patenting, an end-to-end patent-drafting testbed for AI-agent evaluation. A separately-invoked…
arXiv — cs.AI
Research1 мин
$\tau$-Elicitation: Benchmarking multi-turn entity extraction in voice agents
Voice agents often need to collect names, addresses, identifiers, dates, and times exactly, yet end-to-end benchmarks obscure where capture fails. We introduce $τ$-Elicitation, a 200-task voice benchmark spanning 10 entity types, controlled difficulty, caller realisms, and three…
arXiv — cs.AI
Research1 мин
How User-AI Mistreatment Occurs and Matters in Conversational Systems?
Safety research often focuses on model-generated harms, but users may also direct hostility, coercion, and adversarial pressure at models. Understanding how and when that occurs is essential for accurately interpreting model behaviour, alignment drift, and real-world deployment…
arXiv — cs.AI
Research1 мин
Generalized Agent Iteration: One Formal Framework for Iterative Policy Improvement and Recursive Self-Improvement
When we speak of recursive self-improvement (RSI), are we speaking of a phenomenon, a mechanism, or a prospect? Towards autonomous and evolving intelligence, RSI is being claimed at many scales, while no single framework that formally describes these emerging instances exists.…
arXiv — cs.AI
Research1 мин
ZGCM-1: A Fully Open and Extremely Efficient Foundation Model for Math and Agentic Search
In this work, we present ZGCM-1, a fully open 7B dense foundation model trained from scratch with extreme data, system, and algorithmic efficiency. ZGCM-1 is founded on a core premise: compact models cannot passively memorize the open web, but can overcome parametric capacity…
arXiv — cs.AI
Research1 мин
Asclepius: An Adaptive Harness for Long-Horizon Clinical Agents
LLM agents are predominantly benchmarked on short, single-task trajectories, yet real deployments run for hours under contention, surfacing a different class of failures. We use the Clinical Environment Simulator (CES), in which an agent manages an entire emergency-department…
arXiv — cs.AI
Research1 мин
Causal multi-modal AI for personalized chemosensitivity prediction
Chemotherapy improves survival for some patients with breast cancer, but doctors cannot reliably predict who. Current guidelines rely on recurrence scores as a proxy for treatment benefit, which may contribute to the overprescription of chemotherapy. Here we present a causal…
arXiv — cs.AI
Research1 мин
From Legal Text to AI-specific Risk Sources: A Systematic Analysis of the EU AI Act's High-Risk Requirements
The EU AI Act introduces mandatory requirements for high-risk AI systems with the explicit goal of ensuring the development and operation of trustworthy AI. At the same time, AI risk management practices rely on structured risk taxonomies to systematically identify and treat…
arXiv — cs.AI
Research1 мин
OrchSLM: Probing the Dynamics of Small Language Model Orchestration
Although large language models (LLMs) have demonstrated remarkable capabilities, their reliance on cloud-scale infrastructure poses fundamental challenges for deployment in agentic pipelines, including latency, privacy, connectivity, and substantial computational cost. Small…
arXiv — cs.AI
Research1 мин
Root-Cause Attribution Is a Search Problem: Continual Search for Long-Horizon Agent Failures
The increasing deployment of AI agents in long-horizon tasks yields massive execution logs. Diagnosing failures within these records is crucial for reliability, as it transforms outcome-level signals into actionable interventions. The sheer scale of the data renders human review…
arXiv — cs.AI
Research1 мин
Toward Self-Adaptive Physical AI: Can LLM Agents Manage Long-Horizon Physical Tasks?
Large Language Model (LLM) agents offer a promising path toward autonomously managing long-term physical tasks without human intervention. However, physical tasks require agents to continuously observe the environment, make consequential actions, and remain effective as the…
arXiv — cs.AI
Research1 мин
Governing at Machine Speed: An Adaptive Intelligence Architecture for Real-Time AI Policy Enforcement
Enterprise AI adoption has reached 78% of organizations globally, yet the infrastructure to govern that adoption has not kept pace. This paper identifies and characterizes the attestation deficit, a structural condition in which organizations maintain governance policies but…
arXiv — cs.AI
Research1 мин
TimeThink: Eliciting Compositional Reasoning in Timeseries Large Language Models
Timeseries multimodal large language models (TS-MLLMs) have recently begun leveraging the reasoning capabilities of large language models (LLMs) for question-answering tasks. However, these models often fail to capture dynamic temporal patterns, providing only implicit reasoning…
arXiv — cs.AI
Research1 мин
FLoKD: Adaptive Knowledge Distillation for Federated Low-Rank LLM over Wireless Networks
Large language models (LLMs) have demonstrated strong capabilities across a wide range of natural language processing tasks. However, conventional fine-tuning typically relies on centralized data collection, bringing in privacy concerns. Federated learning (FL) enables…
arXiv — cs.AI
Research1 мин
Planning or Learning: Reliability and Cost in Multi-Asset Maintenance
Industrial maintenance systems involve multiple interacting assets and shared resources, making it challenging to balance reliability and operational cost using a single decision framework. While recent work has focused on reinforcement learning (RL) for maintenance scheduling,…
arXiv — cs.AI
Policy & regulation1 мин
Identity Is More Than Recall: A Benchmark for Persistent Identity in Deployed AI Agents
Persistent agents need evaluations that distinguish identity facts they can recall from those they express and enact. We introduce PAI-Bench, a provider-neutral benchmark for fidelity to a versioned, update-governed identity contract. It separates recall, composition, behavioral…
arXiv — cs.AI
Research1 мин
Grounded Adjudication of Variations across Extracted TimeLines (GAVEL): Comparing Clinical Timelines Against Their Case Reports
Existing pipelines for clinical timeline extraction from case reports are evaluated using an expert reference and are limited by imperfect reference annotations and imprecise event alignment. We developed GAVEL, an LLM judge protocol that compares two timelines with the case…
arXiv — cs.AI
Research1 мин
Converge Then Diversify: Decoupling Convergence and Diversity in Multi-Objective Bayesian Optimisation
Multi-objective Bayesian optimisation (MOBO) is a sample-efficient approach for optimising expensive black-box functions with multiple objectives. In MOBO, the goal is to adequately approximate the Pareto front; that is, to obtain a high-quality solution set with 1) good…
arXiv — cs.AI
Research1 мин
LabAgent: Customize Any Research Hubs for Scientific Discoveries Using AI Agents
Scientific research is a continuous process that emphasizes inheritance. Methods developed by predecessors are often expanded upon by new researchers to explore more novel and in-depth scientific questions. However, the change of lab staff, such as student graduation, leads to a…
arXiv — cs.AI
Research1 мин
AutoTailor: Automatic, User-Aligned Capability Selection and Adaptation for Web Agents
Web agents can utilize reusable tools to reduce the cost and latency of low-level browser interaction, but automatically discovered tool collections can be large, redundant, and poorly aligned with user demand. We present AutoTailor, a meta-agentic framework for constructing and…
arXiv — cs.AI
Research1 мин
Fraglingo: Molecular Design via Attachment-Aware Autoregressive Fragment Generation
Molecular design is most effective when generation mirrors the edits chemists actually make: extending a scaffold, replacing a substituent, or decorating a scaffold at a specified attachment site while optimizing molecular properties. Fragment-based molecular design naturally…
arXiv — cs.AI