Date of sighting: Oct 2023Location of sighting: USA (no other info given)Source: Dept of WarLink: https://www.war.gov/UFO/?releaseDate=Release+06&release=06#LLE-UAP-PR002-Unresolved-UAP-Report-Colorado-October-2023I was looking at the Dept of War website at…
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Background Movements for civil rights were a worldwide series of political movements for equality before the law that peaked in the 1960s. In many situations…
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Background The following document was obtained by The Black Vault through the Freedom of Information Act (FOIA), and was part of the “Stargate Collection” release.…
Read MoreA preprocessing pipeline let my car price model peek at the test set before the exam, and the twelve points of R squared it cheated its way to The post My Model Was Cheating on Its Own Test appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #13] - Putting the patterns together, and why this is what “agentic RAG” should look like The post RAG Workflow and Loop Engineering: The Dispatcher That Decides When to Loop and When to Stop appeared first on Towards Data Science.
How AI has massively changed my day-to-day workflow The post A Day in the Life of a Data Scientist in 2026 appeared first on Towards Data Science.
If you read only five papers on AI agents, make them these.
Turn any webpage into a lightweight LLM-powered QA engine by cleaning HTML, converting content to Markdown, and returning focused answers while reducing token usage.
arXiv:2608.12371v1 Announce Type: new Abstract: Stream-processing systems increasingly operate across heterogeneous mobile edge--cloud infrastructures, where workload volatility, resource contention, and stringent quality-of-service (QoS) requirements complicate decentralized scheduling. This paper proposes emph{MAS-DecStream}, whose main contribution is emph{LLM-MR-CNP}: an extension of the classical Contract Net Protocol with semantic CFP formulation, progressive context disclosure, multi-round proposal revision, negotiation…
arXiv:2608.12368v1 Announce Type: new Abstract: Agreement with human judgments is a common proxy for evaluating the alignment of large language models (LLMs). Yet agreement in final labels does not show that human annotators and models rely on the same moral grounds. Two agents may reach the same judgment while appealing to different principles, contextual assumptions,…
arXiv:2608.12346v1 Announce Type: new Abstract: This position paper argues that modern AI alignment methods - originally designed to prevent harmful output - are dual-use technologies that may easily be misused by malicious actors for censorship and manipulation. By mapping current alignment techniques to the possibility and actual cases of misuse, we show that the quest…
arXiv:2608.12345v1 Announce Type: new Abstract: Language models are increasingly deployed as co-scientists, yet their ability to uphold research integrity under institutional pressure remains unmeasured. We introduce IntegrityBench, a benchmark evaluating misconduct classification, ethical action reasoning and artifact-grounded decision making across 36 paired tasks under a 5-level implicit-explicit pressure protocol spanning 3 domains and 4 research…
arXiv:2608.12325v1 Announce Type: new Abstract: Autonomous reasoning is among the most scientifically and economically motivating topics in AI today. Historically the purview of symbolic AI, recent advances have mainly emerged from deep probabilistic generative models. Despite immense interest and rapid progress, the generative AI community has not clearly converged on operational definitions for reasoning and…
