AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28600v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong performance on mathematical reasoning benchmarks, yet the mathematically meaningful skills underlying their reasoning remain underexplored. We introduce \texttt{SHAPE}, a framework that analyzes Chain-of-Thought (CoT) trajectories through two lenses developed in mathematics education: (1) semantic spaces: the model's evolving mathematical interpretations of a problem (e.g., algebraic, geometric), and (2) heuristics: the specific mathematical actions taken within those spaces (e.g., simplifying the problem, working backward). We first use \texttt{SHAPE} to analyze the reasoning patterns of various models. Our findings reveal that the mathematical heuristics employed by a…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28599v1 Announce Type: new Abstract: Clinical diagnosis is a step-by-step, cost-aware process: a physician orders examinations one at a time, observes the results, and updates the diagnosis before reaching a final conclusion. Most medical language models instead treat diagnosis as a one-pass classification task and ignore the trade-off between a test's value and its cost. We model diagnosis as a cost-aware sequential decision process and train the policy with reinforcement learning. The main difficulty is credit assignment: the only reliable signal comes once at the end of a long trajectory, so it scores a wasteful workup the same as an efficient one. We propose CDPR (Counterfactual Diagnostic Process Reward), which needs no expert labels and no lear…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28597v1 Announce Type: new Abstract: Online surveys are a foundational data collection instrument in a variety of fields, with attention checks serving as critical guardians of response quality. However, the rapid emergence of agentic AI (goal directed systems powered by a large language model (LLM) brain and/or a multimodal processing unit with tool-augmented capabilities) raises new questions about the robustness of these safeguards. We investigate how well agentic AI architectures can complete web-based surveys and pass standard attention checks. We evaluate a single-agent architecture capable of multimodal input processing and tool-based web interaction on a controlled survey sandbox. We analyze the problem from two perspectives. From an attack p…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28596v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly embedded in scientific workflows for literature analysis, drafting, and review. Existing systems advance autonomous discovery and manuscript generation, but do not resolve the governance problem that arises when ideas, methods, results, and claims propagate through AI-assisted workflows without mandatory human approval or artifact-level traceability. This paper proposes Paper Pilot, a human-in-the-loop expert system for evidence-traceable scientific manuscript generation in applied sciences. It adapts the Collaborative Agent Reasoning Engineering (CARE) methodology to manuscript development through manuscript-owner approval gates, explicit no-pass criteria, claim…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28595v1 Announce Type: new Abstract: Biomedical NLP pipelines routinely presuppose clean input text, yet large-scale corpora assembled through automated PDF parsing harbour pervasive OCR-like artifacts, token splits and merges, hyphenation remnants, and character-level corruption, that systematically erode lexical evidence and degrade downstream classifiers. We introduce a conservative, fully auditable spell-correction reliability layer conceived as a safety-oriented preprocessing module rather than a maximal-accuracy corrector: under conditions of uncertainty, the system abstains from editing, in accordance with a medical do-no-harm philosophy. The deterministic architecture couples bounded edit-distance candidate generation with corpus-derived n-gr…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28594v1 Announce Type: new Abstract: Conversational analytics systems assume the user already has a well-formed question, leaving a non-expert facing a blank query box on an unfamiliar enterprise schema. Commercial 'proactive' tools narrow this gap only by detecting statistical anomalies over analyst-curated metric layers, and academic next-question recommenders depend on query logs that a fresh dataset lacks. We describe a production analytics system that inverts the interaction model from question-first to analyst-first through two coupled architectural ideas. First, a pluggable domain-expert 'skill' abstraction: a folder-based, database-free subject-matter pack (a manifest, per-stage prompt facets, keyword-routed references, report templates, and…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28593v1 Announce Type: new Abstract: With the increasing development of AI regulatory frameworks, ensuring that artificial intelligence systems, particularly generative models, operate in accordance with legal and ethical standards has become a critical priority. Existing proposals for AI alignment and value-guided behavior, however, face some limitations. Approaches such as Constitutional AI depend on human supervision, while broad normative frameworks like the Good-for-Humanity (GfH) principle may be overly general and ambiguous to provide actionable governance guidance. To overcome these limitations, we propose a hybrid approach called Statutory AI that employs pre-existing human-authored principles drawn from specific themes within a legal corpus…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28592v1 Announce Type: new Abstract: Large language models (LLMs) achieve high scores on medical knowledge examinations, yet real-world oncology is not a knowledge test--it is a sequence of guideline-pathway choices, escalation judgments, and commitments under uncertainty. Existing benchmarks largely measure factual recall, leaving open whether frontier LLMs share decision-path blind spots that combining models cannot fix. We built the Oncology Decision Boundary Benchmark (ODBB)--2,005 oncology decision points across NCCN guidelines and colorectal cancer cases--and evaluated nine frontier LLMs (four closed-source, five open-weight families) released between June 2025 and April 2026. A fully deterministic scorer (zero LLM inference) classified outputs…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28591v1 Announce Type: new Abstract: Recent advancements in AI are helping scientists achieve breakthroughs in fields such as mathematics, medicine, and materials sciences. New evaluation datasets for AI models contribute to such advancement in AI. In the STEM domain, frontier models have consumed most of the available online data, creating the need for human-created datasets that codify the knowledge of leading experts in the domain. There are several STEM datasets available for the research community in this field. However, there are some gaps in these datasets, leaving room for improvement. Examples of gaps include (1) saturation in model performance on these datasets, leaving no head-room for meaningful evaluations, (2) skewed taxonomy distributi…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28590v1 Announce Type: new Abstract: Large Language Model (LLM) agents have shown promise for automating data-science workflows, yet their end-to-end performance depends critically on the agent harness that represents tasks, manages execution state, constrains output artifacts, and provides evaluation feedback. Existing data-science agents often leave this harness implicit, making results difficult to reproduce, compare, and attribute across heterogeneous tasks. We introduce DS-Lighting, a unified harness toolkit that makes harness design explicit for data-science automation. DS-Lighting decomposes the harness into four reusable layers: data, workflow, execution, and evaluation, and represents diverse agents as executable operator programs that suppo…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：The PhD student works to give young people an active role in shaping digital technologies that can support their own well-being.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Your companion from the airport to the hotel meet travelers, and a smart assistant keeps you safe Seatlr is a social network for travelers worldwide: enter your flight number and instantly join a chat room with everyone…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：v2.3.6·What's new→ The coding agent that runs on your machine. Offline, at zero token cost, with your choice of model, and it asks before it changes a single line. Download GIDE ✓30-day trial · no card Other platforms &…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Speed and accuracy usually pull against each other in text-to-speech. Gradium AI's new default model reports both: an 81.0% human-rated pass rate on 500 hard sentences across five languages, at 216 ms P50 time-to-first-audio on Coval. The evaluation set is open on Hugging Face under CC BY 4.0. The post Gradium AI Releases New Default TTS Model: 81.0% Hard-Case Pass Rate at 216 ms Time-to-First-Audio appeared first on MarkTechPost.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Notifications You must be signed in to change notification settings Fork 2 Star 17 BranchesTags Open more actions menu Latest commit History 18 Commits 18 Commits Folders and files NameName Last commit message Last comm…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Weird little guys of FOSS This is a list of weird little guys in the free software movement and adjacent spaces. Request additions, removals, or changes via email; patches welcome. Don’t harass these people! Don’t engag…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：See how Gilbert + Tobin combines CEO-led commitment, rigorous governance, and human accountability to scale ChatGPT Enterprise and Codex across the firm.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Inworld TTS Open Evaluation Toolkit: Reproducible TTS Evals Get started 08.28.2026 Introducing the Inworld TTS Open Evaluation Toolkit An open customizable framework for reproducible, inspectable TTS evaluation. Summari…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：MU/TH/UR 6000 — Free Anonymous AI Chat Terminal (No Login) SYSTEM ONLINE __ __ ___ _ _ ___ ___ ___ ___ ___ ___ _ _ ___ ___ | \/ | __| | | | _ \ | _ \ __| _ \_ _/ __| || |/ __| __| | |\/| | _|| |_| | / | / _|| /| | (__|…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：PDFs full of charts and tables are notoriously hard to put through a traditional RAG pipeline. In this post, we show how late-interaction multi-vector retrieval lets you search PDFs by what the page looks like: no OCR, no chunking, no text extraction.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯： Introducing wrapture New from Graham Dumpleton (of wrapt, mod_wsgi, and New Relic's Python agent fame), who describes Wrapture as taking the monkeypatching ideas from wrapt and extending them to apply to testing and tracing at the same time. Wrapture (full documentation here) makes it easy to wrap any function or method such that all access can be traced, or can be overridden to return a different value. It acts as both an alternative to unittest.mock and a way to implement tracing against an existing project: Attaching observation to code you do not control, recording what flows through it, and doing so without disturbing the program being watched, is a problem I have never really stopped thinking about. Wrapture includes OpenTelemetry support and even has an…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Google Search If you're having trouble accessing Google Search, please click here, or send feedback.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：In September 2023, the Census Bureau added questions about AI to its Business Trends and Outlook Survey. Census asked hundreds of thousands of businesses whether they had used AI in the previous two weeks to produce goo…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：How do you benchmark a web search API when the thing being tested can read the answer key? A search agent has a fetch tool. If the gold labels sit in a public dataset, the agent can download them mid-evaluation and skip retrieval entirely. A similar problem arises when the answers are already encoded in […] The post Keenable AI Open-Sources NEEDLE: A Live Search Benchmark That Rebuilds Its Query Set Every Hour appeared first on MarkTechPost.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Notifications You must be signed in to change notification settings Fork 13 Star 113 BranchesTags Open more actions menu Latest commit History 270 Commits 270 Commits Folders and files NameName Last commit message Last…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Uh oh! There was an error while loading. Please reload this page. Notifications You must be signed in to change notification settings Fork 0 Star 0 BranchesTags Open more actions menu Latest commit History 70 Commits 70…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Peter Wildeford Aug 31, 2026 Photo by Dan Meyers on Unsplash When an aircraft goes down, the wreckage is preserved by law, the investigators have subpoena power, the hearings are public, and the report ends with a proba…

OpenMarket 是一個多智能體市場，核心規則是“用證明説話”——參與者憑藉可驗證的證據而非單純聲明來贏得競爭。

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：In this post, you will learn how to deploy and host your MCP server in AgentCore Runtime and integrate it with Amazon Quick, along with the prerequisites. With this pattern, you promote reusability and avoid duplication of AI tools, so clients can reuse commonly used tools and agents exposed through an MCP server instead of authoring them from scratch again. Your customers get a way to use your product inside Amazon Quick (chat agents and workflows) without building custom connectors for every use case.