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Research1 мин

Mimo 2.6 Flash | Лайт-модель от Xiaomi

Привет. И сегодня будем с вами говорить про очередную модель. Их за последние пару недель вышло как-то очень много. Там просто Google Open Клод антропики выпускают. Там потом китайцы ещё какие-то начали подтягиваться. И среди китайцев пришёл к Xiaomi, тот самый, который топ за…

YouTube — Amorev
Research1 мин

ИИ выдал 284 ответа, которые противоречили подтверждённым фактам

🤖 ИИ выдал 284 ответа, которые противоречили подтверждённым фактам Digital-агентство Verndale проверило, как шесть популярных ИИ-систем рассказывают о программах одного американского университета: более 7200 ответов на 100 вопросов в ChatGPT, Gemini, Google AI Overviews, Google…

Telegram — GPT Time | Нейросети | ИИ
Research1 мин

Meta*, DeepMind и Isomorphic Labs присоединились к проекту симуляции живых клеток

✔️ Meta*, DeepMind и Isomorphic Labs присоединились к проекту симуляции живых клеток Некоммерческая научно-исследовательская организация Biohub семейного фонда Цукербергов расширила программу Virtual Biology Initiative для симуляции клеточных процессов in silico. К проекту…

Telegram — AI Machine Learning Big Data
Research1 мин

Anthropic начала раздавать API-кредиты подписчикам Claude Max

💸 Anthropic начала раздавать API-кредиты подписчикам Claude Max Теперь в зависимости от уровня подписки пользователям дают отдельный ежемесячный бюджет на API-вызовы Claude — можно тратить его из собственных приложений, скриптов, CI-сборок и других проектов. При этом лимиты…

Telegram — GPT Time | Нейросети | ИИ
Research1 мин

OpenAI’s “Alien Math” Is Freaking People Out

The math apocalypse has begun. Scott Aaronson calls this the biggest day in mathematical history. A global coalition of mathematicians formed together to oppose AI math. Only humans allowed. No clankers. Now, Anthropic worried that some of these strongly worded letters might…

YouTube — Wes Roth
Research1 мин

AliO: Output Alignment Matters in Long-Term Time Series Forecasing

Long-term Time Series Forecasting (LTSF) tasks, which leverage the current data sequence as input to predict the future sequence, have become increasingly crucial in real-world applications such as weather forecasting and planning of electricity consumption. However,…

arXiv — cs.AI
Research1 мин

AgentHorizon: Evaluating Agentic Judges for Long-Horizon Computer-Use Tasks

Computer-use agents are capable of completing complex tasks, increasing the use of automatic judges to determine success, either for training or for evaluation without human involvement. Despite their flexibility, their reliability on long tasks spanning multiple applications…

arXiv — cs.AI
Research1 мин

Plan-and-Patch: Diffusion Language Models for Agentic Planning

Planning is increasingly important for long-horizon agents, where successful execution requires coordinating subgoals, tool use, and intermediate outcomes over many steps. Yet assumptions made during planning may be invalidated by the environment, tools may return unexpected…

arXiv — cs.AI
Research1 мин

Verification and Self-Improvement in Agentic AI: Foundations and Limits

Agentic AI systems can improve by searching longer, receiving additional support, or modifying how they propose and verify outputs. A performance score does not distinguish these mechanisms. We compare these changes through bounded verification with hidden terminal randomness. A…

arXiv — cs.AI
Research1 мин

Self-Supervised Keyframe Discovery for Horizon-Invariant Behavior Cloning

Behavior cloning (BC) in non-Markovian environments is a challenging problem because policies have to reason over contextual information over long horizons. Existing policy architectures rely on recurrent or attention-based mechanisms to capture long-term dependencies. However,…

arXiv — cs.AI
Research1 мин

Whose Ground Truth? Embracing Ambiguity in Human-Centered AI

As AI systems increasingly interact with people and make decisions about them, understanding human interpretations becomes an important part of developing human-centered AI. Conventional machine learning and AI systems are largely developed under the assumption that a single…

arXiv — cs.AI
Research1 мин

What to Admit and How to Present: Governing Persistent Memory in LLM Agents

Persistent memory can improve personalization in LLM agents but can also induce sycophancy and cross-domain leakage. We distinguish two governance decisions: admission, which determines what recalled information enters the working context, and presentation, which determines how…

arXiv — cs.AI
Research1 мин

Learning How to Search for Plans with Exponentially Less Space

Heuristic search for a plan can store exponentially many states, even when its heuristic is almost perfect. We instead learn search control, one specification per domain, written as an indexical policy: a generalized policy with registers that hold objects and modes that…

arXiv — cs.AI
Research1 мин

When Interfaces Speak: Data-Aware Generative UI Harness for Active Interaction

Most human-agent interaction today remains text-based. Natural language can impose cognitive overload, ambiguity, information chaos, and slow input for complex tasks; ephemeral generative UIs can present structured information and guide users toward task completion. We propose…

arXiv — cs.AI
Research1 мин

On the Clock: Towards Punctual and Productive Time-Budgeted AI Agents

We study whether small LLM agents can operate effectively under explicit wall-clock time budgets by both respecting the allocated runtime and using available time productively. We evaluate Qwen3.6-27B on five competitions from MLE-Bench Lite and Qwen3-4B on Zork I (Jericho), two…

arXiv — cs.AI
Research1 мин

Beyond Imitation: A Framework and Benchmark for LLM-Assisted Peer Review

The rapid growth of scientific publishing has strained peer review, particularly in machine learning, raising concerns about declining review quality and increasing reviewer workload. Large language models (LLMs) have been proposed as automated review assistants, yet their…

arXiv — cs.AI