source: rss

title: Supply Chain Vuln Compromised Core AWS GitHub Repos & Threatened the AWS Console

summary:
Article URL: https://www.wiz.io/blog/wiz-research-codebreach-vulnerability-aws-codebuild

Comments URL: https://news.ycombinator.com/item?id=46636093

Points: 90

# Comments: 18


title: Internal Deployment Gaps in AI Regulation

summary: arXiv:2601.08005v1 Announce Type: new Abstract: Frontier AI regulations primarily focus on systems deployed to external users, where deployment is more visible and subject to outside scrutiny. However, high-stakes applications can occur internally when companies deploy highly capable systems within their own organizations, such as for automating R\&D, accelerating critical business processes, and handling sensitive proprietary data. This paper examines how frontier AI regulations in the United States and European Union in 2025 handle internal deployment. We identify three gaps that could c


title: Advancing ESG Intelligence: An Expert-level Agent and Comprehensive Benchmark for Sustainable Finance

summary: arXiv:2601.08676v2 Announce Type: new Abstract: Environmental, social, and governance (ESG) criteria are essential for evaluating corporate sustainability and ethical performance. However, professional ESG analysis is hindered by data fragmentation across unstructured sources, and existing large language models (LLMs) often struggle with the complex, multi-step workflows required for rigorous auditing. To address these limitations, we introduce ESGAgent, a hierarchical multi-agent system empowered by a specialized toolset, including retrieval augmentation, web search and domain-specific functi


title: Analyzing GitHub Issues and Pull Requests in nf-core Pipelines: Insights into nf-core Pipeline Repositories

summary: arXiv:2601.09612v1 Announce Type: new Abstract: Scientific Workflow Management Systems (SWfMSs) such as Nextflow have become essential software frameworks for conducting reproducible, scalable, and portable computational analyses in data-intensive fields like genomics, transcriptomics, and proteomics. Building on Nextflow, the nf-core community curates standardized, peer-reviewed pipelines that follow strict testing, documentation, and governance guidelines. Despite its broad adoption, little is known about the challenges users face during the development and maintenance of these pipelines. Th


repo: grafana/grafana

title: 12.3.0

summary: [Download page](https://grafana.com/grafana/download/12.3.0) [What's new highlights](https://grafana.com/docs/grafana/latest/whatsnew/) ### Features and enhancements - **API Clients:** Add lazy hooks to clients [#113226](https://github.com/grafana/grafana/pull/113226), [@tomratcliffe](https://github.com/tomratcliffe) - **API clients:** Automatically set PATCH headers [#111879](https://github.com/grafana/grafana/pull/111879), [@Clarity-89](https://github.com/Clarity-89) - **API clients:** Extract into a package [#111810](https://github.com/grafana/grafana/pull/111810), [@Clarity-89](https://github.com/Clarity-89) - **API clients:** Extract into a package (Enterprise) - **API clients:** Update API clients to include all endpoints & add hooks [#113061](https://github.com/grafana/grafana/pull/


summary:
Article URL: https://www.wiz.io/blog/wiz-research-codebreach-vulnerability-aws-codebuild

Comments URL: https://news.ycombinator.com/item?id=46636093

Points: 90

# Comments: 19


summary:
Article URL: https://www.wiz.io/blog/wiz-research-codebreach-vulnerability-aws-codebuild

Comments URL: https://news.ycombinator.com/item?id=46636093

Points: 99

# Comments: 21


title: PCN-Rec: Agentic Proof-Carrying Negotiation for Reliable Governance-Constrained Recommendation

summary: arXiv:2601.09771v1 Announce Type: new Abstract: Modern LLM-based recommenders can generate compelling ranked lists, but they struggle to reliably satisfy governance constraints such as minimum long-tail exposure or diversity requirements. We present PCN-Rec, a proof-carrying negotiation pipeline that separates natural-language reasoning from deterministic enforcement. A base recommender (MF/CF) produces a candidate window of size W, which is negotiated by two agents: a User Advocate optimizing relevance and a Policy Agent enforcing constraints. A mediator LLM synthesizes a top-N slate together


title: A Governance Model for IoT Data in Global Manufacturing

summary: arXiv:2601.09744v1 Announce Type: new Abstract: Industrial IoT platforms in global manufacturing environments generate continuous operational data across production assets, utilities, and connected products. While data ingestion and storage capabilities have matured significantly, enterprises continue to face systemic challenges in governing IoT data at scale. These challenges are not rooted in tooling limitations but in the absence of a governance model that aligns with the realities of distributed operational ownership, heterogeneous source systems, and continuous change at the edge. This pa


title: CodeAssistBench (CAB): Dataset & Benchmarking for Multi-turn Chat-Based Code Assistance

summary: arXiv:2507.10646v5 Announce Type: replace Abstract: Programming assistants powered by large language models have improved dramatically, yet existing benchmarks still evaluate them in narrow code-generation settings. Recent efforts such as InfiBench and StackEval rely on Stack Overflow questions and remain limited to single-turn interactions, manually curated data, and isolated snippets rather than full project environments. We introduce CodeAssistBench (CAB), the first benchmark for evaluating multi-turn, project-grounded programming assistance at scale. CAB automatically constructs datasets f


summary:
Article URL: https://www.wiz.io/blog/wiz-research-codebreach-vulnerability-aws-codebuild

Comments URL: https://news.ycombinator.com/item?id=46636093

Points: 105

# Comments: 23


summary:
Article URL: https://www.wiz.io/blog/wiz-research-codebreach-vulnerability-aws-codebuild

Comments URL: https://news.ycombinator.com/item?id=46636093

Points: 112

# Comments: 22


summary:
Article URL: https://www.wiz.io/blog/wiz-research-codebreach-vulnerability-aws-codebuild

Comments URL: https://news.ycombinator.com/item?id=46636093

Points: 117

# Comments: 24


title: Texas A&M university is banning Plato, citing his "gender ideology"

summary:
Article URL: https://lithub.com/texas-am-is-banning-plato-citing-his-gender-ideology/

Comments URL: https://news.ycombinator.com/item?id=46662886

Points: 23

# Comments: 10


title: Empathy Guidelines for Improving Practitioner Well-being & Software Engineering Practices

summary: arXiv:2508.03846v2 Announce Type: replace Abstract: Empathy is a powerful yet often overlooked element in software engineering (SE), supporting better teamwork, smoother communication, and effective decision-making.This paper introduces 17 actionable empathy guidelines designed to support practitioners, teams, and organisations. We also explore how these guidelines can be implemented in practice by examining real-world applications, challenges, and strategies to overcome them shared by software practitioners. To support adoption, we present a visual prioritisation framework that categorises th


title: Ultrathink is deprecated & How to enable 2x thinking tokens in Claude Code

summary:
Article URL: https://decodeclaude.com/ultrathink-deprecated/

Comments URL: https://news.ycombinator.com/item?id=46672858

Points: 22

# Comments: 1


title: Show HN: Pdfwithlove – PDF tools that run 100% locally (no uploads, no back end)

summary:
Most PDF web tools make millions by uploading documents that never needed to leave your computer.
pdfwithlove does the opposite:
1. 100% local processing 2. No uploads, no backend, no tracking
Features include merge/split/edit/compress PDFs, watermarks & signatures, and image/HTML/Office → PDF conversion.

Comments URL: https://news.ycombinator.com/item?id=46675231

Points: 5

# Comments: 1


summary:
Most PDF web tools make millions by uploading documents that never needed to leave your computer.
pdfwithlove does the opposite:
1. 100% local processing 2. No uploads, no backend, no tracking
Features include merge/split/edit/compress PDFs, watermarks & signatures, and image/HTML/Office → PDF conversion.

Comments URL: https://news.ycombinator.com/item?id=46675231

Points: 72

# Comments: 33


summary:
Most PDF web tools make millions by uploading documents that never needed to leave your computer.
pdfwithlove does the opposite:
1. 100% local processing 2. No uploads, no backend, no tracking
Features include merge/split/edit/compress PDFs, watermarks & signatures, and image/HTML/Office → PDF conversion.

Comments URL: https://news.ycombinator.com/item?id=46675231

Points: 124

# Comments: 61


title: Show HN: Subth.ink – write something and see how many others wrote the same

summary:
Hey HN, this is a small Haskell learning project that I wanted to share. It's just a website where you can see how many people write the exact same text as you (thought it was a fun idea).
It's built using Scotty, SQLite, Redis and Caddy. Currently it's running in a small DigitalOcean droplet (1 Gb RAM).
Using Haskell for web development (specifically with Scotty) was slightly easier than I thought, but still a relatively hard task compared to other languages. One of my main friction points was Haskell's multiple string-like types: String, Text (& lazy), ByteString (& lazy), and each li


title: Show HN: GitClassic.com, GitHub circa 2015 without JS & AI

summary:
Hey HN,
Got tired of how bloated GitHub became- copilot everywhere, janky JS, slow loads. So I built GitClassic, a read-only GitHub interface that's pure server-rendered HTML, kind of like old.reddit.com. No JavaScript.
Try it: https://gitclassic.com
Browse any public repo, files, READMEs. Loads instantly, works on any connection. No account needed for public repos.
Stack: Node on Lambda, server-side rendering, cached against GitHub's API. Pro adds private repo access via GitHub OAuth.
Built this in about 3 hours. Would love feed


source: samhsa

title: SAMHSA Statutes and Regulations (Residential & Halfway Houses)

buckets: governance housing civil_structure


title: Premises Liability & Independent Contractor Doctrine

buckets: governance civil_structure risk


title: HUD Shared Housing & House Rules Guidance

buckets: housing governance shared_living


Netherlands Supervised Housing & Shared Living Standards


title: Japan Shared Housing & Group Living Guidelines

buckets: housing shared_living sanitation


title: Show HN: On-device browser agent (Qwen) running locally in Chrome

summary:
Demo of LOCAL Browser agent (powered by Web GPU Liquid LFM & Alibaba Qwen models) opening the All in Podcast on Youtube running as a chrome extension.
Source: https://github.com/RunanywhereAI/on-device-browser-agent
Post: https://www.reddit.com/r/LocalLLaMA/comments/1qh10q9/comment...
Geting in the support for web sdk soon, meanwhile have full support for mobile sdks : <a href="https://github.com/Runany


title: The Stability Trap: Evaluating the Reliability of LLM-Based Instruction Adherence Auditing

summary: arXiv:2601.11783v1 Announce Type: new Abstract: The enterprise governance of Generative AI (GenAI) in regulated sectors, such as Human Resources (HR), demands scalable yet reproducible auditing mechanisms. While Large Language Model (LLM)-as-a-Judge approaches offer scalability, their reliability in evaluating adherence of different types of system instructions remains unverified. This study asks: To what extent does the instruction type of an Application Under Test (AUT) influence the stability of judge evaluations? To address this, we introduce the Scoped Instruction Decomposition Framework


title: Improved Bug Localization with AI Agents Leveraging Hypothesis and Dynamic Cognition

summary: arXiv:2601.12522v1 Announce Type: new Abstract: Software bugs cost technology providers (e.g., AT&T) billions annually and cause developers to spend roughly 50% of their time on bug resolution. Traditional methods for bug localization often analyze the suspiciousness of code components (e.g., methods, documents) in isolation, overlooking their connections with other components in the codebase. Recent advances in Large Language Models (LLMs) and agentic AI techniques have shown strong potential for code understanding, but still lack causal reasoning during code exploration and struggle to m


title: Governance Matters: Lessons from Restructuring the data.table OSS Project

summary: arXiv:2601.13466v1 Announce Type: new Abstract: Open source software (OSS) forms the backbone of industrial data workflows and enterprise systems. However, many OSS projects face operational risks due to informal or centralized governance. This paper presents a practical case study of data.table, a high-performance R package widely adopted in production analytics pipelines, which underwent a community-led governance reform to address scalability and sustainability concerns. Before the reform, data.table faced a growing backlog of unresolved issues and open pull requests, unclear contributor pa


title: Implementing Knowledge Representation and Reasoning with Object Oriented Design

summary: arXiv:2601.14840v1 Announce Type: new Abstract: This paper introduces KRROOD, a framework designed to bridge the integration gap between modern software engineering and Knowledge Representation & Reasoning (KR&R) systems. While Object-Oriented Programming (OOP) is the standard for developing complex applications, existing KR&R frameworks often rely on external ontologies and specialized languages that are difficult to integrate with imperative code. KRROOD addresses this by treating knowledge as a first-class programming abstraction using native class structures, bridging the gap betwe


title: The Why Behind the Action: Unveiling Internal Drivers via Agentic Attribution

summary: arXiv:2601.15075v1 Announce Type: new Abstract: Large Language Model (LLM)-based agents are widely used in real-world applications such as customer service, web navigation, and software engineering. As these systems become more autonomous and are deployed at scale, understanding why an agent takes a particular action becomes increasingly important for accountability and governance. However, existing research predominantly focuses on \textit{failure attribution} to localize explicit errors in unsuccessful trajectories, which is insufficient for explaining the reasoning behind agent behaviors. T


title: Call2Instruct: Automated Pipeline for Generating Q&A Datasets from Call Center Recordings for LLM Fine-Tuning

summary: arXiv:2601.14263v1 Announce Type: cross Abstract: The adaptation of Large-Scale Language Models (LLMs) to specific domains depends on high-quality fine-tuning datasets, particularly in instructional format (e.g., Question-Answer - Q&A). However, generating these datasets, particularly from unstructured sources such as call center audio recordings, poses a significant challenge due to the noisy and disorganized nature of the data. This paper presents a solution to this challenge by offering an end-to-end automated pipeline for generating Q&A instructional datasets from such recordings.


title: Hallucination-Free Automatic Question & Answer Generation for Intuitive Learning

summary: arXiv:2601.14280v1 Announce Type: cross Abstract: Hallucinations in large language models (LLMs), defined as fluent yet incorrect or incoherent outputs, pose a significant challenge to the automatic generation of educational multiple-choice questions (MCQs). We identified four key hallucination types in MCQ generation: reasoning inconsistencies, insolvability, factual errors, and mathematical errors. To address this, we propose a hallucination-free multi-agent generation framework that breaks down MCQ generation into discrete, verifiable stages. Our framework utilizes both rule-based and LLM-b


title: Tracing the Data Trail: A Survey of Data Provenance, Transparency and Traceability in LLMs

summary: arXiv:2601.14311v1 Announce Type: cross Abstract: Large language models (LLMs) are deployed at scale, yet their training data life cycle remains opaque. This survey synthesizes research from the past ten years on three tightly coupled axes: (1) data provenance, (2) transparency, and (3) traceability, and three supporting pillars: (4) bias \& uncertainty, (5) data privacy, and (6) tools and techniques that operationalize them. A central contribution is a proposed taxonomy defining the field's domains and listing corresponding artifacts. Through analysis of 95 publications, this work identifies


summary: arXiv:2601.14311v1 Announce Type: new Abstract: Large language models (LLMs) are deployed at scale, yet their training data life cycle remains opaque. This survey synthesizes research from the past ten years on three tightly coupled axes: (1) data provenance, (2) transparency, and (3) traceability, and three supporting pillars: (4) bias \& uncertainty, (5) data privacy, and (6) tools and techniques that operationalize them. A central contribution is a proposed taxonomy defining the field's domains and listing corresponding artifacts. Through analysis of 95 publications, this work identifies ke


title: Constructing Multi-label Hierarchical Classification Models for MITRE ATT&CK Text Tagging

summary: arXiv:2601.14556v1 Announce Type: cross Abstract: MITRE ATT&CK is a cybersecurity knowledge base that organizes threat actor and cyber-attack information into a set of tactics describing the reasons and goals threat actors have for carrying out attacks, with each tactic having a set of techniques that describe the potential methods used in these attacks. One major application of ATT&CK is the use of its tactic and technique hierarchy by security specialists as a framework for annotating cyber-threat intelligence reports, vulnerability descriptions, threat scenarios, inter alia, to faci


title: Neural Honeytrace: Plug&Play Watermarking Framework against Model Extraction Attacks

summary: arXiv:2501.09328v4 Announce Type: replace Abstract: Triggerable watermarking enables model owners to assert ownership against model extraction attacks. However, most existing approaches require additional training, which limits post-deployment flexibility, and the lack of clear theoretical foundations makes them vulnerable to adaptive attacks. In this paper, we propose Neural Honeytrace, a plug-and-play watermarking framework that operates without retraining. We redefine the watermark transmission mechanism from an information perspective, designing a training-free multi-step transmission stra


title: Understanding Usefulness in Developer Explanations on Stack Overflow

summary: arXiv:2601.14865v1 Announce Type: new Abstract: Explanations are essential in software engineering (SE) and requirements communication, helping stakeholders clarify ambiguities, justify design choices, and build shared understanding. Online Q&A forums such as Stack Overflow provide large-scale settings where such explanations are produced and evaluated, offering valuable insights into what makes them effective. While prior work has explored answer acceptance and voting behavior, little is known about which specific features make explanations genuinely useful. The relative influence of stru


summary: arXiv:2601.14840v1 Announce Type: cross Abstract: This paper introduces KRROOD, a framework designed to bridge the integration gap between modern software engineering and Knowledge Representation & Reasoning (KR&R) systems. While Object-Oriented Programming (OOP) is the standard for developing complex applications, existing KR&R frameworks often rely on external ontologies and specialized languages that are difficult to integrate with imperative code. KRROOD addresses this by treating knowledge as a first-class programming abstraction using native class structures, bridging the gap bet


title: Goldman Sachs Global Macro Research: Gen AI: too much spend, too little benefit [pdf]

summary:
Article URL: https://www.goldmansachs.com/static-libs/pdf-redirect/prod/index.html?path=/images/migrated/insights/pages/gs-research/gen-ai--too-much-spend,-too-little-benefit-/TOM_AI%202.0_ForRedaction.pdf&originalQuery=&referrer=

Comments URL: https://news.ycombinator.com/item?id=4672