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Article URL: https://www.southampton.ac.uk/~doug/quantum_physics/index.html Comments URL: https://news.ycombinator.com/item?id=50219666 Points: 143 # Comments: 90

A controlled study shows that switching between coding-agent harnesses like Claude Code, OpenCode, or mini-SWE-agent barely moves pass rates more than rerunning the same setup. Cost per task, however, can triple, driven mainly by the system prompt that gets resent with every step. The article Fancy harnesses make coding agents more expensive but not better, study finds appeared first on The Decoder .

Article URL: https://www.bloomberg.com/news/articles/2026-10-23/sk-data-center-arm-in-talks-to-fund-350-billion-ai-buildout Comments URL: https://news.ycombinator.com/item?id=50219467 Points: 1 # Comments: 0

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Article URL: https://www.thestreet.com/crypto/artificial-intelligence/mace-ai-founders-warn-of-ai-double-agents-amid-banks-detecting-unauthorized-ai-agents- Comments URL: https://news.ycombinator.com/item?id=50219381 Points: 2 # Comments: 1

Article URL: https://www.bbc.co.uk/news/articles/cqdjv8xllvyyo Comments URL: https://news.ycombinator.com/item?id=50219343 Points: 4 # Comments: 0

Article URL: https://sideos.ai Comments URL: https://news.ycombinator.com/item?id=50219166 Points: 1 # Comments: 0

Article URL: https://usb-ai-hazel.vercel.app/ Comments URL: https://news.ycombinator.com/item?id=50219139 Points: 1 # Comments: 0

Article URL: https://aicitewho.com/ Comments URL: https://news.ycombinator.com/item?id=50219085 Points: 1 # Comments: 0

Article URL: https://github.com/trenttrinder1111-byte/zk-irp-firewall Comments URL: https://news.ycombinator.com/item?id=50219061 Points: 1 # Comments: 0

Article URL: https://www.reddit.com/r/singularity/comments/1xduimx/hacker_reverse_engineers_his_samsung_tv_and_finds/ Comments URL: https://news.ycombinator.com/item?id=50218950 Points: 4 # Comments: 1

Article URL: https://www.pewresearch.org/short-reads/2026/10/23/few-americans-say-they-are-asking-ai-chatbots-for-2026-election-information/ Comments URL: https://news.ycombinator.com/item?id=50218935 Points: 2 # Comments: 0

Article URL: https://www.tbray.org/ongoing/When/202x/2026/10/19/The-AI-Temptation Comments URL: https://news.ycombinator.com/item?id=50218743 Points: 6 # Comments: 2

Article URL: https://calmatters.org/politics/2026/10/california-proposition-2-explained/ Comments URL: https://news.ycombinator.com/item?id=50218702 Points: 3 # Comments: 0

Article URL: https://console.usetd.com/ Comments URL: https://news.ycombinator.com/item?id=50218670 Points: 1 # Comments: 0

Article URL: https://www.reddit.com/r/antiai/comments/1xdv3e5/hacker_reverse_engineers_his_samsung_tv_and_finds/ Comments URL: https://news.ycombinator.com/item?id=50218633 Points: 307 # Comments: 87

<p>Chancellor says government to commit hundreds of millions to develop ‘distinctively British’ approach to AI</p><p>John Healey has pledged to use Wednesday’s budget to harness the power of artificial intelligence to bolster Britain’s security and prosperity against the risks in the accelerating global technology arms race.</p><p>As he prepares for his debut budget, the chancellor said that Andy Burnham’s government would commit hundreds of millions of pounds to develop a “distinctively British

arXiv:2610.30158v1 Announce Type: new Abstract: Artificial intelligence (AI), as a decision-support aid, provides new tools for studying history effectively using multimodal data, including text, images, and audio. We present, to our knowledge, the first digital assistant named Lighthouse--commonly called a chatbot--for exploring the Civil Rights period of the United States using data from South Carolina. From an AI perspective, the system's novelty lies in its guiding design principles of (a) f

arXiv:2610.30161v1 Announce Type: new Abstract: Many Indian banks serve customers through FAQ pages and scripted chatbots. Assistants based on language models could respond faster and carry out requests such as blocking a card, but only if they give correct information and follow the bank's rules. These rules prescribe a procedure, a set of required steps, such as obtaining a closure quote before closing a deposit. Adapting models to this domain requires measuring how well they follow the proced

arXiv:2610.30162v1 Announce Type: new Abstract: Model fusion aims to integrate the capabilities of multi-expert models into a single model. Existing evaluations offer limited coverage of reasoning with long chains of thought and tool use, while strong average performance can mask substantial losses in individual expert capabilities. We introduce FusionEval, a benchmark that provides controlled expert pools, integrates fusion methods with and without additional training, and offers a unified eval

arXiv:2610.30296v1 Announce Type: new Abstract: Large Language Models (LLMs) have accelerated research on low-resource and multilingual NLP, but their effectiveness in creating an equitable landscape remains unmapped. We analyze 1,158 peer-reviewed open-access papers published between 2020 and 2025, examining research attention to low-resource languages (LRLs) and representation across language and speaker populations. To assess linguistic inclusion beyond publication counts, we introduce the Li

arXiv:2610.30344v1 Announce Type: new Abstract: Training Arabic large language models faces challenges from noisy web data, dialectal variation, and the high cost of continual pretraining (CPT). We introduce AQL-Lite (AQL: Arabic Quality Language), a time- and resource-efficient framework for adapting a multilingual LLM to Modern Standard Arabic (MSA). AQL-Lite couples a quality-first curation pipeline (structural cleaning, heuristic and model-based filtering, MSA selection, and deduplication) w

arXiv:2610.30374v1 Announce Type: new Abstract: The massively multilingual translation systems that now include Sicilian learned it from noisy, non-standardised web text. To obtain better translation quality, we redevelop the small neural machine translation (NMT) system that Wdowiak customized for Sicilian. We rebuild on maintained software the extraction of the parallel text from the PDFs of the bilingual journal Arba Sicula, whose sentences are aligned by a language-agnostic sentence encoder

arXiv:2610.30379v1 Announce Type: new Abstract: LLM agents are flexible in language interaction, but using them as long-horizon planners is costly and prone to hallucinated or invalid actions. This paper targets a different role for LLMs: constrained bridges between language and symbolic planning. We propose MemPlan, a memory-conditioned PDDL planning framework for partially observable interactive text environments. MemPlan keeps the PDDL domain fixed and reconstructs the PDDL problem at each st

arXiv:2610.30412v1 Announce Type: new Abstract: LLM-based chat agents are increasingly used for complex, multi-turn, multilingual medical triage in low- and middle-income countries (LMICs), yet evaluation methods focus on single-turn, English-only benchmarks that primarily test the chatbots' knowledge. In practice, users are often confused, overwhelmed, or emotionally vulnerable, giving unclear, misspelled single-word answers or long messages in regional dialects, and the context of a conversati

arXiv:2610.30435v1 Announce Type: new Abstract: Recent advances in search agents have enabled large language models to tackle complex tasks by retrieving and synthesizing external information. However, existing search agents often lack search-state awareness, i.e., the ability to recognize what information has been obtained and what remains missing, leading to hallucinated reasoning and prematurely terminated search. To address this limitation, we propose Self-Assessment Reinforcement Learning (

arXiv:2610.30504v1 Announce Type: new Abstract: Large language models (LLMs) are widely used to answer factual questions, but their answers can contain errors and must be fact-checked claim by claim. Yet the resulting score depends on three design decisions: which questions the claims answer, under what conditions each claim is judged, and which sources count as evidence. No existing benchmark specifies all three. We introduce JSFactCheckBench, a Japanese benchmark that specifies all three, with

arXiv:2610.30512v1 Announce Type: new Abstract: LLM judges are used to determine which of two answers is better. Trusting these verdicts requires knowing how repeatable they are and how much they depend on the judge's instructions. We show that similar aggregate scores can conceal substantial changes in individual verdicts, both when the same setup is repeated and when the instructions change. Using 500 Arena-Hard v2.0 prompts with two models' answers held fixed, we run GPT-4.1 as the judge unde

arXiv:2610.30518v1 Announce Type: new Abstract: We present Protegrity-PII, a new PII decision model for structured and unstructured text. Protegrity-PII achieves a typed recall of 0.915 with a precision of 0.907 on a new benchmark we propose, PII-SCOPE. Our model processes text in 0.49 seconds per million characters at \$0.0005 per million characters on a single RTX 6000 using batched inference. Due in part to the expansive nature of the entity type taxonomy used in training, Protegrity-PII achi

arXiv:2610.30533v1 Announce Type: new Abstract: Industry Foundation Classes (IFC), the standard for building information exchange in architecture, engineering, and construction (AEC), is increasingly queried through large language models (LLMs) using natural language. Evaluating these systems at scale is difficult because free-text answers require costly human or LLM-based review. We propose IFC-MCQ, a method that automatically generates multiple-choice benchmarks from IFC files for exact option

arXiv:2610.30635v1 Announce Type: new Abstract: Coding-agent benchmarks often describe a task in natural language but grade it with tests taken from the upstream project. Passing those tests can require information the description never states: a constant's name, a module path, an exact message. We call this a specification-oracle gap: where it exists, a benchmark also measures whether an agent reproduces upstream implementation details. We formalise the gap, including the inconsistencies that c

arXiv:2610.30664v1 Announce Type: new Abstract: Large language models increasingly act as controllers in structured decision pipelines, yet their decisions are still executed by autoregressive text decoding. Hierarchical RAG is one such setting: at each frontier of a document tree, an LLM commits to $b$ of $k$ sections under an input-dependent action grammar, executed as either failure-prone free-form JSON or reliable but strictly serial grammar-constrained generation. We show that this serializ

arXiv:2610.30676v1 Announce Type: new Abstract: Singular-value spectra encode important structure in transformer feed-forward projections, yet their causal role in downstream behavior remains underexplored. We study post-hoc spectral smoothing and spiking interventions on the up_proj and down_proj matrices. Positive perturbation stretches deviations from the geometric mean, making large singular values larger and small ones smaller (spiking), and vice versa. The intervention preserves singular v

arXiv:2610.30690v1 Announce Type: new Abstract: Large language models (LLMs) deployed in mental-health contexts can be evaluated for safety failures, but the resulting judgments are often difficult to inspect or explain. Common approaches to improving safety rely on prompt engineering, LLM-as-a-Judge, and Constitutional AI. In this work, we describe a clinician-led alternative in which two clinicians define, finalize, and adjudicate the four safety checks of a rule base, which is formally verifi

arXiv:2610.30705v1 Announce Type: new Abstract: Text embedding and text generation are two of the most useful capabilities of modern large language models, yet they are typically provided by separate specialized models (an embedder and a generator) trained with incompatible objectives and deployed side by side in retrieval-augmented generation and agent systems. Recent unified embedding-generation models such as GritLM share parameters between the two capabilities, but they either switch attenti

arXiv:2610.30715v1 Announce Type: new Abstract: This paper studies the local geometry of semantic meaning in large language models. Current representation analyses ask whether meanings are close in embedding space, or whether linear probes separate semantic classes, but they do not characterize the within-concept local geometry: what is invariant across realizations of a single semantic factor, what varies, and what changes when meaning is refined. This paper characterizes that geometry through

arXiv:2610.30742v1 Announce Type: new Abstract: Guardrail models are increasingly used as safety layers for LLMs and agentic systems, but most are trained on fixed prompt or response interfaces and become unreliable when the same safety case appears as a conversation, agent trajectory, multi-agent trace, or policy-conditioned input. We propose UniGuard, a training framework that learns interface-invariant safety representations from multiple semantically aligned views of the same safety case. We

<p><strong>Release:</strong> <a href="https://github.com/simonw/battledrones/releases/tag/v14">battledrones v14: Compass Rose, a four player map</a></p> <p>I added four player online mode to <a href="https://simonwillison.net/2026/Oct/20/battledrones/">Battledrones</a> - previous maps were limited to two.</p> <p>Here's the initial prompt I used: </p> <blockquote> <p><code>Add a new map for a four player battle - four way rotational symmetry, up to four AI players, works with the WebSocket non-au

NVIDIA released Nemotron 3.5 Bolt E4B 4GB, an open small language model post-trained from Gemma 4 E4B for local voice assistants, game characters and robots, targeting about 4GB of VRAM on RTX and Jetson. The post NVIDIA Releases Nemotron 3.5 Bolt E4B 4GB: An Open Small Language Model for Local Voice Agents, Game Characters and Robots appeared first on MarkTechPost .

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