Pai 的 AI 雷达
今天：数学代理作弊与 AI 政策（Agent 原型），洛杉矶建筑变迁可视化（Article URL:）。并行还有 A Tesla ran、Replaceable but Employed、Agent 编程不确定性闸门。
Welcome to Import AI, a newsletter about AI research. Import AI runs on arXiv, cappuccinos, and feedback from readers. If you’d like to support this, please subscribe. Subscribe now Researchers discover another OpenAI agent emergent communication incident: …Less severe, but worry
LLM agents deployed for software engineering fail expensively: they act confidently wrong, and bad actions are recognized only after costly execution and retry. We present Speculative Uncertainty (SU), a method that recovers a predictive failure signal for a black-box agent from
Computer-use agents have advanced on benchmarks like OSWorld and AndroidWorld, but still act mostly through the GUI, often producing inefficient trajectories. Real-world computer work is hybrid, combining visual-state inspection with precise, high-throughput command-line operatio
据 The Information 报道，Anthropic 在十一个月内签署了价值高达 5170 亿美元的算力合同，自 2025 年 10 月以来锁定至少 14.8 GW 算力，并计划自建数据中心。 🔗 阅读原文 via AIHOT · https://aihot.virxact.com/items/cmtrkorpo07jdrotnozlrlyx2
PDF: https://www.vldb.org/pvldb/vol19/p4953-fernandez-moctezuma.p...
Evaluating the calibration of Large Language Models (LLMs) is critical for their safe deployment as zero-shot classifiers. Yet, commercial API providers increasingly hide the continuous output probabilities required by standard calibration metrics. To bypass this opacity, we demo
Computer-use agents have advanced on benchmarks like OSWorld and AndroidWorld, but still act mostly through the GUI, often producing inefficient trajectories. Real-world computer work is hybrid, combining visual-state inspection with precise, high-throughput command-line operatio
Large language models (LLMs) show potential for medical tasks, but their single-turn question-answer format does not reflect how clinical diagnosis is performed in practice. As a result, they remain limited in complex diagnostic settings. We developed Debate-Mixture-of-Agents (DM
Building on the pioneering paper of Kearns, Roth, and Ryu (SODA'26), we study information aggregation in a networked learning model. The model captures a central pattern in agentic AI: each agent sees only part of the data and passes on only its own conclusion. Their model consid
A rapidly expanding ecosystem of actors is removing built-in safety guardrails from open-weight AI models. We profile this ecosystem by identifying key producers, downstream reproductions, and emerging applications. Between January 2024 and March 2026, we identified 3,471 origina
Autonomous AI agents increasingly select actions in environments whose memory, execution-time, runtime, compute, and operational constraints determine what counts as a suitable plan. We call the absence of this execution context from an agent's planning state substrate blindness.
Explainability is increasingly seen as a crucial requirement in AI-based medical diagnosis, particularly in safety-critical clinical decision-making. Most existing explainability methods in healthcare operate in a post-hoc manner and are predominantly designed for unimodal data,
Automotive infotainment validation still relies on manual testing, slow, costly, and incompatible with agile releases and OTA updates. Scripted automation only partly helps: it couples test logic to implementation, yielding brittle, high-maintenance suites. Existing LLM-driven fr
OpenAI 发布内部数据称已达到自动化研究实习生里程碑，即可在人类监督下完成熟练研究员需数天的明确任务。截至 8 月中旬，其研究组织每投入 1 个人工工作日，就使用 3.1 个 agent 工作日的运行时长，该比值衡量的是运行时间而非等效生产力；原文作者援引 OpenAI 员工观点称递归自我改进或成为未来几年 AI 能力的关键，并呼吁其他 AI 公司同样公开数据。 🔗 阅读原文 via AIHOT · https://aihot.virxact.com/items/cmtq5pxc10275roiufscxyie4