Tootfinder

#OpenAI and #Anthropic Donate AGENTS.md and Model Context Protocol to New Agentic AI #Foundation

from my link log —
libfringe: an old Rust library for stackful coroutines.
https://github.com/edef1c/libfringe
saved 2025-10-28 https://dotat.at/:/S…

FreeBSD context: https://www.theregister.com/2025/09/03/freebsd_project_update_no_ai/ @…
Cc

Finally found some time to look into the QGISMCP plugin.
The original connects #QGIS :qgis: to #Claude through the Model Context Protocol #MCP. I rewired it to work with a local European alternative: the new m…

GitHub - anitagraser/qgis_mcp: Model Context Protocol (MCP) that allows LLMs to use QGIS Desktop
Model Context Protocol (MCP) that allows LLMs to use QGIS Desktop - anitagraser/qgis_mcp

I'm especially interested in a few things if anyone is willing to help...
1) missing words and simple typos - My ADHD brain skips words coming out and fulls them in when reading, so it's easy for me to make mistakes and hard for me to catch them.
2) questions - I tend to work from a lot of assumed knowledge, collected from all over, and I'm really trying to make my work more accessible. I assume I'm talking about a bunch of stuff most folks don't know, but I don't know which of them come from some rabbit hole I went down and which are more common knowledge.
3) challenges - I get bored when having things explained to me so I have a tendency to keep explanations light... Which can mean I leave out a bunch of critical context or logical steps.

facebook_friends: Maier Facebook friends (2014)
A small anonymized Facebook ego network, from April 2014. Nodes are Facebook profiles, and an edge exists if the two profiles are "friends" on Facebook. Metadata gives the social context for the relationship between ego and alter.
This network has 362 nodes and 1988 edges.
Tags: Social, Online, Unweighted, Metadata

what are these guys smoking?
https://mailarchive.ietf.org/arch/msg/cfrg/arwZRrgGid3AaMgTUNbGXJLJk_8/
context:

from my link log —
Thread stack layout and ASLR on various unixes.
https://www.netmeister.org/blog/thread-stacks.html
saved 2025-10-30 https://

Stacking Threads
An attempt to clarify my understanding of thread stacks in memory, particularly within the context of Address Space Layout Randomization (ASLR).

I have a habbit of making (too) many (small) packages for functionality that might be reused in different context. {box} might be an alternative by making scripts into modlues that can be loaded: #RStats <…

‘box’: Write Reusable, Composable and Modular R Code
A modern module system for R. Organise code into hierarchical, composable, reusable modules, and use it effortlessly across projects via a flexible, declarative dependency loading syntax.

Anthropic says Claude can now keep a chat going indefinitely, automatically summarizing earlier context when it hits its context window (Russell Brandom/TechCrunch)
https://techcrunch.com/2025/11/24/anthropic-releases-opus-4-5-with-new-ch…

Anthropic releases Opus 4.5 with new Chrome and Excel integrations | TechCrunch
Anthropic has launched Opus 4.5, the latest version of its flagship model, with new integrations into Chrome and Excel.

Da is übrigens der Einstieg in das Bildarchiv (Jovan Ritopečki’s
photographic
documentation
of Yugoslav
labor migration
in Austria), auf das Du unlängst hingewiesen hast, @… :

@… 😃
Incidentally, there's more than mirroring to be done, before the announcement. For documentation, please see (for example):
― <https://

»Importing vs fetching JSON:
This year, JSON module imports became baseline 'newly available', meaning they're implemented across browser engines.«
— by @…
Although I don't know for what and in what context to use in the browser, but it's good that I now know about this.
🧑‍💻

Importing vs fetching JSON
They behave differently, so make sure you pick the right one.

facebook_friends: Maier Facebook friends (2014)
A small anonymized Facebook ego network, from April 2014. Nodes are Facebook profiles, and an edge exists if the two profiles are "friends" on Facebook. Metadata gives the social context for the relationship between ego and alter.
This network has 362 nodes and 1988 edges.
Tags: Social, Online, Unweighted, Metadata

maybe i should have a website again
i've avoided it for years after deciding that i didn't like both the nature of my old writing and the reasons for writing
but i've worked on a lot of different things, and a lot of those are useful, and maybe it's good for there to be some unified repository of them that adds context

@… @… They say only a Sith deals in absolutes. I think there’s a lot of important context that’s going implied here.
For most American businesses, I think you’re spot on.
But what about say… the tax agency of anoth…

Over 20 ad tech companies including PubMatic, Optable, and Yahoo launch the Ad Context Protocol, a new open standard to support future agentic advertising (Trishla Ostwal/Adweek)
https://www.adweek.com/media/adcp-ad-context-protocol-agentic-advertising-sta…

Yahoo, PubMatic, and Others Launch New Standard for Agentic Advertising
Twenty ad tech firms launch the Ad Context Protocol to cut costs, boost transparency, and lay the groundwork for agentic advertising.

"AI can scan, flag, and analyze at speeds humans cannot, but it still lacks context, nuance, and the human intuition necessary to differentiate between chips and guns, mischief and menace."
Teen handcuffed after AI thinks Doritos are a weapon - Salon.com
https://www.salon.com/2025/10/26/teen-handcuffed-after-ai-thinks-doritos-are-a-weapon/

Denmark recommends routinely vaccinating all children against just 10 diseases.
In the U.S., the immunization schedule calls for routine universal vaccination against 16 diseases.
-- It was 17 diseases until last week, when the Centers for Disease Control and Prevention officially dropped the recommendation to vaccinate all newborns against hepatitis B.
But Denmark has created its immunization schedule in a very different context than that of the U.S., notes Dr. Sean O'L…

DCP: Addressing Input Dynamism In Long-Context Training via Dynamic Context Parallelism
Chenyu Jiang, Zhenkun Cai, Ye Tian, Zhen Jia, Yida Wang, Chuan Wu
https://arxiv.org/abs/2510.10620

DCP: Addressing Input Dynamism In Long-Context Training via Dynamic Context Parallelism
Context parallelism has emerged as a key technique to support long-context training, a growing trend in generative AI for modern large models. However, existing context parallel methods rely on static parallelization configurations that overlook the dynamic nature of training data, specifically, the variability in sequence lengths and token relationships (i.e., attention patterns) across samples. As a result, these methods often suffer from unnecessary communication overhead and imbalanced comp…

On the Side II 🆓
在边缘 II 🆓
📷 Nikon F4E
🎞️ Ilford HP5 Plus 400, expired 1993
#filmphotography #Photography #blackandwhite

from my link log —
Context parameters and API design in Kotlin.
https://serranofp.com/blog/context-params.html
saved 2025-10-20 https://

Sumble, which offers an AI sales intelligence service, emerges from stealth and raised a $30M Series A led by Canaan Partners and $8.5M seed led by Coatue (Ram Iyer/TechCrunch)
https://techcrunch.com/2025/10/22/sumbl…

Sumble emerges from stealth with $38.5M to bring AI-powered context to sales intelligence | TechCrunch
The founders of machine learning community Kaggle are trying to upend the crowded sales prospecting market with AI. And they're making headway.

Formal Models and Convergence Analysis for Context-Aware Security Verification
Ayush Chaudhary
https://arxiv.org/abs/2510.12440 https://arxiv.org/pdf/2510.…

Formal Models and Convergence Analysis for Context-Aware Security Verification
We present a formal framework for context-aware security verification that establishes provable guarantees for ML-enhanced adaptive systems. We introduce context-completeness - a new security property - and prove: (1) sample complexity bounds showing when adaptive verification succeeds, (2) information-theoretic limits relating context richness to detection capability, (3) convergence guarantees for ML-based payload generators, and (4) compositional soundness bounds. We further provide a formal…

On the Relationship Between the Choice of Representation and In-Context Learning
Ioana Marinescu, Kyunghyun Cho, Eric Karl Oermann
https://arxiv.org/abs/2510.08372 https://

On the Relationship Between the Choice of Representation and In-Context Learning
In-context learning (ICL) is the ability of a large language model (LLM) to learn a new task from a few demonstrations presented as part of the context. Past studies have attributed a large portion of the success of ICL to the way these in-context demonstrations are represented, particularly to how labels are represented in classification tasks. On the other hand, observations of the learning capacity of ICL (i.e., the extent to which more in-context demonstrations can lead to higher performanc…

It's kinda weird how the Linux Foundation has accepted to become the dumping ground for tech/infrastructure that fall out of some tech hype. First they picked up a lot of Blockchain stuff, now they do AI infra.

💬Readers added context they thought people might want to know…
“Europe is hurtling toward digital vassalage. Under Ursula von der Leyen, the European Commission president, EU laws to tackle tech giants have been either not applied or delayed, for fear of offending Donald Trump. Now leaked documents reveal that the European Commission plans to gut a central part of Europe’s digital rulebook. This will hurt Europe’s innovators and hand the future of Europe’s tech sovereignty to US firms.…

Windows 11 Intlune devices disconnecting from Entra ID - devices no longer Entra Joined after reboot
https://www.reddit.com/r/Intune/comments/1od595p/comment/nktjcww/?context=3

VizCopilot: Fostering Appropriate Reliance on Enterprise Chatbots with Context Visualization
Sam Yu-Te Lee, Jingya Chen, Albert Calzaretto, Richard Lee, Alice Ferng, Mihaela Vorvoreanu
https://arxiv.org/abs/2510.11954

VizCopilot: Fostering Appropriate Reliance on Enterprise Chatbots with Context Visualization
Enterprise chatbots show promise in supporting knowledge workers in information synthesis tasks by retrieving context from large, heterogeneous databases before generating answers. However, when the retrieved context misaligns with user intentions, the chatbot often produces "irrelevantly right" responses that provide little value. In this work, we introduce VizCopilot, a prototype that incorporates visualization techniques to actively involve end-users in context alignment. By combining topic …

Out of context, "Why isn't Gargamel as sexy as I remember?" might be the funniest thing that I've ever heard from a podcast.

Anyone looking for context on the Irish presidential election, here is everything you need to know:
https://bellacaledonia.org.uk/2025/10/24/messy-democracy-irelands-reshaped-presidency/

Messy Democracy: Ireland’s Reshaped Presidency
As Ireland elects its new President, Claire McNab offers a historical overview of the role and its prospects.  Ireland is on its fifteenth instance of a task which Scotland has never done: electing…

Beyond More Context: How Granularity and Order Drive Code Completion Quality
Uswat Yusuf, Genevieve Caumartin, Diego Elias Costa
https://arxiv.org/abs/2510.06606 https://…

Beyond More Context: How Granularity and Order Drive Code Completion Quality
Context plays an important role in the quality of code completion, as Large Language Models (LLMs) require sufficient and relevant information to assist developers in code generation tasks. However, composing a relevant context for code completion poses challenges in large repositories: First, the limited context length of LLMs makes it impractical to include all repository files. Second, the quality of generated code is highly sensitive to noisy or irrelevant context. In this paper, we present…

There is variation in everyone, but society / context / environment makes that variation more burdensome for some than for others. “Neurotypical” is not a thing that anyone •is•, but rather an archetype that human systems are designed for / evolved around.
When we recognize that “neurotypical” is an archetype and not an actual person, we can reach the same insight that the Air Force reached: you don’t build things to some single optimal set of “normal” dimensions; you make things more adjustable, flexible, accommodating of variation.
/end

Trump says a Canadian ad misstated Ronald Reagan's views on tariffs. Here are the facts and context (Paul Wiseman/Associated Press)
https://apnews.com/article/trump-canada-ad-tariff-reagan-trade-talks-f711559b0084b377d82d964893c67c78
http://www.memeorandum.com/251024/p125#a251024p125

Theory of Scaling Laws for In-Context Regression: Depth, Width, Context and Time
Blake Bordelon, Mary I. Letey, Cengiz Pehlevan
https://arxiv.org/abs/2510.01098 https://

Theory of Scaling Laws for In-Context Regression: Depth, Width, Context and Time
We study in-context learning (ICL) of linear regression in a deep linear self-attention model, characterizing how performance depends on various computational and statistical resources (width, depth, number of training steps, batch size and data per context). In a joint limit where data dimension, context length, and residual stream width scale proportionally, we analyze the limiting asymptotics for three ICL settings: (1) isotropic covariates and tasks (ISO), (2) fixed and structured covarianc…

Migrating a large accretion of complex blog post content between platforms is a draining & thoroughly demoralising experience. It turns out that we, as web developers, are capable of creating byzantine platforms which give diligent blog writers the ability to create hours and hours of unrewarding work that is so cryptically & diversely broken that no script can be written to make sense of the mess.
Enjoy your holidays if you're in a cultural context where that sort of thin…

Memory as Action: Autonomous Context Curation for Long-Horizon Agentic Tasks
Yuxiang Zhang, Jiangming Shu, Ye Ma, Xueyuan Lin, Shangxi Wu, Jitao Sang
https://arxiv.org/abs/2510.12635

Memory as Action: Autonomous Context Curation for Long-Horizon Agentic Tasks
Large Language Models face challenges in long-horizon agentic tasks as their constrained memory is easily overwhelmed by distracting or irrelevant context. Existing working memory methods typically rely on external, heuristic mechanisms that are decoupled from the agent's core policy. In this work, we reframe working memory management as a learnable, intrinsic capability. We propose a novel framework, Memory-as-Action, where an agent actively manages its working memory by executing explicit edi…

I can't locate the quote anymore and I don't remember the context, but a sentence I read many years ago that stuck with me was, "You must not only kill your idols, you must also burn your 'kill yr idols' t-shirt."

Towards Foundation Inference Models that Learn ODEs In-Context
Maximilian Mauel, Manuel Hinz, Patrick Seifner, David Berghaus, Ramses J. Sanchez
https://arxiv.org/abs/2510.12650

Towards Foundation Inference Models that Learn ODEs In-Context
Ordinary differential equations (ODEs) describe dynamical systems evolving deterministically in continuous time. Accurate data-driven modeling of systems as ODEs, a central problem across the natural sciences, remains challenging, especially if the data is sparse or noisy. We introduce FIM-ODE (Foundation Inference Model for ODEs), a pretrained neural model designed to estimate ODEs zero-shot (i.e., in context) from sparse and noisy observations. Trained on synthetic data, the model utilizes a …

facebook_friends: Maier Facebook friends (2014)
A small anonymized Facebook ego network, from April 2014. Nodes are Facebook profiles, and an edge exists if the two profiles are "friends" on Facebook. Metadata gives the social context for the relationship between ego and alter.
This network has 362 nodes and 1988 edges.
Tags: Social, Online, Unweighted, Metadata

In voorbereiding van een commissievergadering gebruikte ik, na eerst de stukken zelf te hebben gelezen, Gemini 3 als tool om mij te adviseren over de in te brengen punten. Heel makkelijk omdat alle stukken openbaar zijn en je deze dus kunt meegeven als context/kennis. Gemini vindt deels dingen die ik zelf had geconstateerd maar deels ook andere. Benieuwd hoe dit het werk in raden gaat veranderen. Risico, mensen gaan nog minder zelf lezen... 🙄

motion can end it all. motion can end it all. striking phrase when stripped from the youtube slop thumbnail context

Scott helpfully reminds us of the differences between technical purity, semantics, and what actually matters to users in the context of — yes, really — paragraphs:
https://www.scottohara.me/blog/2024/08/29/paragraphs.html

Opposition Filed Against DOJ Effort to Strike Context from Complaint About Qatar’s ‘Gifted’ Jet to Trump Administration - American Oversight
https://americanoversight.org/opposition-filed-against-doj-effort-to-strike-context-from-complaint-about-qatars-gifted-jet-to-trump-administration/

Ik weet wel een paar betere kwalificaties dan 'brutaal'.
Bizar dat Karolying Leavitt denkt door het publiceren van de 'context' het brandje te kunnen blussen ... het maakt het alleen maar erger.
"Woordvoerder Witte Huis reageert brutaal op vraag van journalist: ‘Je moeder’
"

Woordvoerder Witte Huis reageert brutaal op vraag van journalist: ‘Je moeder’
De woordvoerder van de Amerikaanse president Donald Trump, Karoline Leavitt, heeft op opvallende wijze gereageerd op een vraag van een journalist. In plaats van een echt antwoord kreeg de journalist van de site HuffPost een veeg uit de pan: ‘Je bent een extreemlinkse prutser.’

Don’t panic: This Raiders rookie receiver remains a future building block https://raiderramble.com/2025/12/25/dont-panic-this-raiders-rookie-receiver-remains-a-future-building-block/

Salesforce öffnet Slack für externe KI
Salesforce öffnet Slack für KI: Über API und Model Context Protocol erhalten Entwickler Zugriff auf Chatdaten, um kontextsensitive Agenten zu erstellen.
https://www.

shit, it finally happened. has anybody figured out what would be the answer? #deadfreaksunite https://mstdn.social/@ComicContext/115577311953122490

Comics Outta Context (@ComicContext@mstdn.social)
Attached: 1 image

I’d love to have accounts tagged with their owners’ general location. Nation. State. Time zone. Context matters. @… https://

Bill Cole (@scconsult.com)
WOW. Definitely worthy of an exemption from my usual policy towards X screengrabs. This change is surprising and I hope other platforms also adopt a general location as the norm in a profile. I'm sure it would have been hilarious back when the place wasn't Elon's toy. [contains quote post or other embedded content]

Detecting Legend Items on Historical Maps Using GPT-4o with In-Context Learning
Sofia Kirsanova, Yao-Yi Chiang, Weiwei Duan
https://arxiv.org/abs/2510.08385 https://

Detecting Legend Items on Historical Maps Using GPT-4o with In-Context Learning
Historical map legends are critical for interpreting cartographic symbols. However, their inconsistent layouts and unstructured formats make automatic extraction challenging. Prior work focuses primarily on segmentation or general optical character recognition (OCR), with few methods effectively matching legend symbols to their corresponding descriptions in a structured manner. We present a method that combines LayoutLMv3 for layout detection with GPT-4o using in-context learning to detect and …

Anthropic donates the Model Context Protocol to the Agentic AI Foundation and says there are now more than 10,000 active public MCP servers (Anthropic)
https://www.anthropic.com/news/donating-the-model-context-protocol-and-esta…

Donating the Model Context Protocol and establishing the Agentic AI Foundation
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

Anybody familiar with the details of how thread local storage on aarch64 is implemented abi wise?
Like if I'm working on a bare metal embedded platform with two cores and i want some data to be private per core using gcc thread local attributes how do i actually make that work so accesses to that data get a pointer to a per core context object and look it up as an offset into it etc?

Evaluation Framework for Highlight Explanations of Context Utilisation in Language Models
Jingyi Sun, Pepa Atanasova, Sagnik Ray Choudhury, Sekh Mainul Islam, Isabelle Augenstein
https://arxiv.org/abs/2510.02629

Evaluation Framework for Highlight Explanations of Context Utilisation in Language Models
Context utilisation, the ability of Language Models (LMs) to incorporate relevant information from the provided context when generating responses, remains largely opaque to users, who cannot determine whether models draw from parametric memory or provided context, nor identify which specific context pieces inform the response. Highlight explanations (HEs) offer a natural solution as they can point the exact context pieces and tokens that influenced model outputs. However, no existing work evalu…

Scalable In-context Ranking with Generative Models
Nilesh Gupta, Chong You, Srinadh Bhojanapalli, Sanjiv Kumar, Inderjit Dhillon, Felix Yu
https://arxiv.org/abs/2510.05396 https…

Scalable In-context Ranking with Generative Models
In-context Ranking (ICR) is an emerging paradigm for Information Retrieval (IR), which leverages contextual understanding of LLMs by directly incorporating the task description, candidate documents, and the query into the model's input prompt and tasking the LLM to identify relevant document(s). While it is effective, efficiency is a significant challenge in this paradigm, especially as the candidate list grows due to quadratic/super-linear scaling of attention operation with context length. To…

AwareCompiler: Agentic Context-Aware Compiler Optimization via a Synergistic Knowledge-Data Driven Framework
Hongyu Lin, Haolin Pan, Haoran Luo, Yuchen Li, Kaichun Yao, Libo Zhang, Mingjie Xing, Yanjun Wu
https://arxiv.org/abs/2510.11759

AwareCompiler: Agentic Context-Aware Compiler Optimization via a Synergistic Knowledge-Data Driven Framework
Compiler optimization is crucial for enhancing program performance by transforming the sequence of optimization passes while maintaining correctness. Despite the promising potential of large language models (LLMs)-based agent for software optimization, automating compiler optimization remains challenging due to: (1) semantic misalignment between abstract program representations and concrete optimization passes, (2) inefficient interaction mechanisms between agents and compiler environments, and…

Series A, Episode 03 - Cygnus Alpha
ARTIX: Come on, move it. Hurry. Move it. [Prisoners file in] Guard, make a double check that the rest of the prisoners are secure.
GUARD: Yes sir.
ARTIX: Move it.
https://blake.torpidity.net/m/103/189 B7B4

Model Context Protocol Server for #HomeAssistant
https://www.home-assistant.io/integrations/mcp_server/

For greater confidence, I must also lock the packages for which files were not installed.
Without locking: an upgrade may cause unwanted installation. <https://www.reddit.com/r/freebsd/comments/1psmi54/comment/nvt7rq7/?context=1>

just the normal goings-on at my house

@… draw for me a photo of a woman in her fifties with blond hair wearing an eye patch over one eye. The other eye is blue. The context is a library

ContextVLA: Vision-Language-Action Model with Amortized Multi-Frame Context
Huiwon Jang, Sihyun Yu, Heeseung Kwon, Hojin Jeon, Younggyo Seo, Jinwoo Shin
https://arxiv.org/abs/2510.04246

ContextVLA: Vision-Language-Action Model with Amortized Multi-Frame Context
Leveraging temporal context is crucial for success in partially observable robotic tasks. However, prior work in behavior cloning has demonstrated inconsistent performance gains when using multi-frame observations. In this paper, we introduce ContextVLA, a policy model that robustly improves robotic task performance by effectively leveraging multi-frame observations. Our approach is motivated by the key observation that Vision-Language-Action models (VLA), i.e., policy models built upon a Visio…

Jessie Price and David Pocock in conversation about the critical importance of community Independents on the crossbench in the context of a Coalition shambles and Labor majority - sharpening the role of the crossbench in holding the government to account and pushing for stronger action.
#JessiePrice #DavidPocock

It’s important to put Ukraine’s current situation in the context of history. And it’s important to know that history is still controversial: https://en.wikipedia.org/wiki/Holodomor The past isn’t even past.
https://social.vivaldi.net/@Ann1944/115590607854450930

Trump says a Canadian ad misstated Ronald Reagan's views on tariffs. Here are the facts and context | AP News
https://apnews.com/article/trump-canada-ad-tariff-reagan-trade-talks-f711559b0084b377d82d964893c67c78

facebook_friends: Maier Facebook friends (2014)
A small anonymized Facebook ego network, from April 2014. Nodes are Facebook profiles, and an edge exists if the two profiles are "friends" on Facebook. Metadata gives the social context for the relationship between ego and alter.
This network has 362 nodes and 1988 edges.
Tags: Social, Online, Unweighted, Metadata

In-Context Clustering with Large Language Models
Ying Wang, Mengye Ren, Andrew Gordon Wilson
https://arxiv.org/abs/2510.08466 https://arxiv.org/pdf/2510.08…

In-Context Clustering with Large Language Models
We propose In-Context Clustering (ICC), a flexible LLM-based procedure for clustering data from diverse distributions. Unlike traditional clustering algorithms constrained by predefined similarity measures, ICC flexibly captures complex relationships among inputs through an attention mechanism. We show that pretrained LLMs exhibit impressive zero-shot clustering capabilities on text-encoded numeric data, with attention matrices showing salient cluster patterns. Spectral clustering using attenti…

A look at Model Context Protocol and how it went from a passion project made by Anthropic employees to an industry standard shared through the Linux Foundation (Hayden Field/The Verge)
https://www.theverge.com/ai-artificial-int

AI companies want a new internet — and they think they’ve found the key
Anthropic is donating MCP to the Linux Foundation, to be governed under the Agentic AI Foundation, with other members including OpenAI, Google, and Block.

Scaling LLM Multi-turn RL with End-to-end Summarization-based Context Management
Miao Lu, Weiwei Sun, Weihua Du, Zhan Ling, Xuesong Yao, Kang Liu, Jiecao Chen
https://arxiv.org/abs/2510.06727

Scaling LLM Multi-turn RL with End-to-end Summarization-based Context Management
We study reinforcement learning (RL) fine-tuning of large language model (LLM) agents for long-horizon multi-turn tool use, where context length quickly becomes a fundamental bottleneck. Existing RL pipelines can suffer from degraded instruction following, excessive rollout costs, and most importantly, strict context limits. To address these challenges, we introduce summarization-based context management to training. In specific, it periodically compresses the tool using history by LLM-generate…

@… I see pros and cons with Linux (Kubuntu), pros and cons with FreeBSD.
Today: <https://www.reddit.com/r/freebsd/comments/1oeeed6…

Fine-Grained Emotion Recognition via In-Context Learning
Zhaochun Ren, Zhou Yang, Chenglong Ye, Haizhou Sun, Chao Chen, Xiaofei Zhu, Xiangwen Liao
https://arxiv.org/abs/2510.06600

Fine-Grained Emotion Recognition via In-Context Learning
Fine-grained emotion recognition aims to identify the emotional type in queries through reasoning and decision-making processes, playing a crucial role in various systems. Recent methods use In-Context Learning (ICL), enhancing the representation of queries in the reasoning process through semantically similar examples, while further improving emotion recognition by explaining the reasoning mechanisms. However, these methods enhance the reasoning process but overlook the decision-making process…

the context, the context, the context

Strategic Fusion of Vision Language Models: Shapley-Credited Context-Aware Dawid-Skene for Multi-Label Tasks in Autonomous Driving
Yuxiang Feng, Keyang Zhang, Hassane Ouchouid, Ashwil Kaniamparambil, Ioannis Souflas, Panagiotis Angeloudis
https://arxiv.org/abs/2510.01126

Strategic Fusion of Vision Language Models: Shapley-Credited Context-Aware Dawid-Skene for Multi-Label Tasks in Autonomous Driving
Large vision-language models (VLMs) are increasingly used in autonomous-vehicle (AV) stacks, but hallucination limits their reliability in safety-critical pipelines. We present Shapley-credited Context-Aware Dawid-Skene with Agreement, a game-theoretic fusion method for multi-label understanding of ego-view dashcam video. It learns per-model, per-label, context-conditioned reliabilities from labelled history and, at inference, converts each model's report into an agreement-guardrailed log-likel…

“Make the seats adjustable” is a thought I bring to teaching, for example: Does the context I’m creating for learning accommodate people with all different kinds of minds? What variations am I not accommodating? Can I make some things more individually adjustable to better embrace those variations? Can multiple instructors / learning environments / schools offer the flexibility that I can’t offer myself?
Total adjustability is impossible; infinite flexibility is impossible. But as an ongoing effort, as a •direction•, this work is both feasible and useful.
9/

Clarifying Semantics of In-Context Examples for Unit Test Generation
Chen Yang, Lin Yang, Ziqi Wang, Dong Wang, Jianyi Zhou, Junjie Chen
https://arxiv.org/abs/2510.01994 https:/…

Clarifying Semantics of In-Context Examples for Unit Test Generation
Recent advances in large language models (LLMs) have enabled promising performance in unit test generation through in-context learning (ICL). However, the quality of in-context examples significantly influences the effectiveness of generated tests-poorly structured or semantically unclear test examples often lead to suboptimal outputs. In this paper, we propose CLAST, a novel technique that systematically refines unit tests to improve their semantic clarity, thereby enhancing their utility as i…

RE: https://ec.social-network.europa.eu/@EC_DIGIT/115564144071125950
Yeah you can save a lot of time by accepting that "it cannot" is the answer. You mustn't draft legislation with an LLM because in that context words do massivel…

@… So, depending on context, I think I have three different answers:
#1 for better and worse, the Protestant Christian church has, over centuries, managed to interweave itself with Danish culture.
So even though I don’t have any faith, I would gladly and with no reservations participate in something like Christmas mass. I’ve even been to one at the Nordic hous…

Donald Trump's family business and its Saudi partner are to build
a luxury Maldives resort that uses
blockchain technology to attract investment
https://www.memeorandum.com/251117/p41

Trump family and Saudi partner unveil tokenised Maldives resort
By Chloe Cornish / Financial Times. View the full context on memeorandum.

@… draw for me a horrid photo of a ragged young girl in a night gown with angel like wings standing infront of a monstrous creature resembling a dragon looking out from the ruins of a burnt down house. The context is a dystopic landscape with ruins and skulls on the ground

RUTH BEN-GHIAT: The Geopolitical Context of Trump's War on America: Video and Essay
https://lucid.substack.com/p/video-on-the-geopolitical-context

Learning-To-Measure: In-context Active Feature Acquisition
Yuta Kobayashi, Zilin Jing, Jiayu Yao, Hongseok Namkoong, Shalmali Joshi
https://arxiv.org/abs/2510.12624 https://

Learning-To-Measure: In-context Active Feature Acquisition
Active feature acquisition (AFA) is a sequential decision-making problem where the goal is to improve model performance for test instances by adaptively selecting which features to acquire. In practice, AFA methods often learn from retrospective data with systematic missingness in the features and limited task-specific labels. Most prior work addresses acquisition for a single predetermined task, limiting scalability. To address this limitation, we formalize the meta-AFA problem, where the goal…

Training-Free Time Series Classification via In-Context Reasoning with LLM Agents
Songyuan Sui, Zihang Xu, Yu-Neng Chuang, Kwei-Herng Lai, Xia Hu
https://arxiv.org/abs/2510.05950

Training-Free Time Series Classification via In-Context Reasoning with LLM Agents
Time series classification (TSC) spans diverse application scenarios, yet labeled data are often scarce, making task-specific training costly and inflexible. Recent reasoning-oriented large language models (LLMs) show promise in understanding temporal patterns, but purely zero-shot usage remains suboptimal. We propose FETA, a multi-agent framework for training-free TSC via exemplar-based in-context reasoning. FETA decomposes a multivariate series into channel-wise subproblems, retrieves a few s…

LongRM: Revealing and Unlocking the Context Boundary of Reward Modeling
Zecheng Tang, Baibei Ji, Quantong Qiu, Haitian Wang, Xiaobo Liang, Juntao Li, Min Zhang
https://arxiv.org/abs/2510.06915

LongRM: Revealing and Unlocking the Context Boundary of Reward Modeling
Reward model (RM) plays a pivotal role in aligning large language model (LLM) with human preferences. As real-world applications increasingly involve long history trajectories, e.g., LLM agent, it becomes indispensable to evaluate whether a model's responses are not only high-quality but also grounded in and consistent with the provided context. Yet, current RMs remain confined to short-context settings and primarily focus on response-level attributes (e.g., safety or helpfulness), while largel…

Enhancing Neural Code Representation with Additional Context
Huy Nguyen, Christoph Treude, Patanamon Thongtanunam
https://arxiv.org/abs/2510.12082 https://…

Enhancing Neural Code Representation with Additional Context
Automated program comprehension underpins many software engineering tasks, from code summarisation to clone detection. Recent deep learning models achieve strong results but typically rely on source code alone, overlooking contextual information such as version history or structural relationships. This limits their ability to capture how code evolves and operates. We conduct an empirical study on how enriching code representations with such contextual signals affects neural model performance on…

More context:
https://www.essence.com/news/money-career/howard-intern-spotify-wrapped/
Basically:
- Spotify Wrapped used to be a dull email
- Design intern proposed turning it into an ~~experience~~, demoed her idea
- They didn’t hire her, but the redesign looks a lot like what she proposed
- Spotify says “nuh-uh, and besides lots of people contributed to it.” OK.
https://hachyderm.io/@thomasfuchs/115741043600230762

Critical attention scaling in long-context transformers
Shi Chen, Zhengjiang Lin, Yury Polyanskiy, Philippe Rigollet
https://arxiv.org/abs/2510.05554 https://

Critical attention scaling in long-context transformers
As large language models scale to longer contexts, attention layers suffer from a fundamental pathology: attention scores collapse toward uniformity as context length $n$ increases, causing tokens to cluster excessively, a phenomenon known as rank-collapse. While $\textit{attention scaling}$ effectively addresses this deficiency by rescaling attention scores with a polylogarithmic factor $β_n$, theoretical justification for this approach remains lacking. We analyze a simplified yet tractable…

OpenAI releases GPT‑5.2-Codex, with improvements on long-horizon work through context compaction, stronger performance on large code changes, and more (OpenAI)
https://openai.com/index/introducing-gpt-5-2-codex/

Safe and Efficient In-Context Learning via Risk Control
Andrea Wynn, Metod Jazbec, Charith Peris, Rinat Khaziev, Anqi Liu, Daniel Khashabi, Eric Nalisnick
https://arxiv.org/abs/2510.02480

Safe and Efficient In-Context Learning via Risk Control
Large language models (LLMs) demonstrate a remarkable ability to learn new tasks from a few in-context examples. However, this flexibility introduces safety concerns: LLMs can be influenced by incorrect or malicious demonstrations -- for example, if an adversary tampers with or injects harmful examples without a human supervisor noticing. This motivates principled designs in which the system itself includes built-in mechanisms to guard against such attacks. We propose a novel approach to limit …

Display brightness: "… some backlight hardware simply is not controllable with FreeBSD …" – true or false?
Would "not easily controllable" be truer?
<https://www.reddit.com/r/freebsd/comments/1pn9flt/comment/nufe3nf/?context=1…

facebook_friends: Maier Facebook friends (2014)
A small anonymized Facebook ego network, from April 2014. Nodes are Facebook profiles, and an edge exists if the two profiles are "friends" on Facebook. Metadata gives the social context for the relationship between ego and alter.
This network has 362 nodes and 1988 edges.
Tags: Social, Online, Unweighted, Metadata

FocusAgent: Simple Yet Effective Ways of Trimming the Large Context of Web Agents
Imene Kerboua, Sahar Omidi Shayegan, Megh Thakkar, Xing Han L\`u, L\'eo Boisvert, Massimo Caccia, J\'er\'emy Espinas, Alexandre Aussem, V\'eronique Eglin, Alexandre Lacoste
https://arxiv.org/abs/2510.03204…

FocusAgent: Simple Yet Effective Ways of Trimming the Large Context of Web Agents
Web agents powered by large language models (LLMs) must process lengthy web page observations to complete user goals; these pages often exceed tens of thousands of tokens. This saturates context limits and increases computational cost processing; moreover, processing full pages exposes agents to security risks such as prompt injection. Existing pruning strategies either discard relevant content or retain irrelevant context, leading to suboptimal action prediction. We introduce FocusAgent, a sim…

from my link log —
Why are video games graphics (still) a challenge? Productionizing rendering algorithms.
https://bartwronski.com/2020/12/27/why-are-video-games-graphics-still-a-challenge-productionizing-rendering…

Why are video games graphics (still) a challenge? Productionizing rendering algorithms
Intro This post will cover challenges and aspects of production to consider when creating new rendering / graphics techniques and algorithms – especially in the context of applied research fo…

Context-Aware Model-Based Reinforcement Learning for Autonomous Racing
Emran Yasser Moustafa, Ivana Dusparic
https://arxiv.org/abs/2510.11501 https://arxiv…

Context-Aware Model-Based Reinforcement Learning for Autonomous Racing
Autonomous vehicles have shown promising potential to be a groundbreaking technology for improving the safety of road users. For these vehicles, as well as many other safety-critical robotic technologies, to be deployed in real-world applications, we require algorithms that can generalize well to unseen scenarios and data. Model-based reinforcement learning algorithms (MBRL) have demonstrated state-of-the-art performance and data efficiency across a diverse set of domains. However, these algori…

Semantic-Condition Tuning: Fusing Graph Context with Large Language Models for Knowledge Graph Completion
Ruitong Liu, Yan Wen, Te Sun, Yunjia Wu, Pingyang Huang, Zihang Yu, Siyuan Li
https://arxiv.org/abs/2510.08966

Semantic-Condition Tuning: Fusing Graph Context with Large Language Models for Knowledge Graph Completion
Fusing Knowledge Graphs with Large Language Models is crucial for knowledge-intensive tasks like knowledge graph completion. The prevailing paradigm, prefix-tuning, simply concatenates knowledge embeddings with text inputs. However, this shallow fusion overlooks the rich relational semantics within KGs and imposes a significant implicit reasoning burden on the LLM to correlate the prefix with the text. To address these, we propose Semantic-condition Tuning (SCT), a new knowledge injection parad…

Beyond Turn Limits: Training Deep Search Agents with Dynamic Context Window
Qiaoyu Tang, Hao Xiang, Le Yu, Bowen Yu, Yaojie Lu, Xianpei Han, Le Sun, WenJuan Zhang, Pengbo Wang, Shixuan Liu, Zhenru Zhang, Jianhong Tu, Hongyu Lin, Junyang Lin
https://arxiv.org/abs/2510.08276

Beyond Turn Limits: Training Deep Search Agents with Dynamic Context Window
While recent advances in reasoning models have demonstrated cognitive behaviors through reinforcement learning, existing approaches struggle to invoke deep reasoning capabilities in multi-turn agents with long-horizon interactions. We propose DeepMiner, a novel framework that elicits such abilities by introducing high-difficulty training tasks and dynamic context window. DeepMiner presents a reverse construction method to generate complex but verifiable question-answer pairs from authentic web …

This is a striking statement from somebody in his position. We all know it’s true; the news here is that this person in this context is willing to say it so bluntly.
https://mastodon.social/@eunews/115718839488535199

A First Context-Free Grammar Applied to Nawatl Corpora Augmentation
Juan-Jos\'e Guzm\'an-Landa, Juan-Manuel Torres-Moreno, Miguel Figueroa-Saavedra, Ligia Quintana-Torres, Martha-Lorena Avenda\~no-Garrido, Graham Ranger
https://arxiv.org/abs/2510.04945

A First Context-Free Grammar Applied to Nawatl Corpora Augmentation
In this article we introduce a context-free grammar (CFG) for the Nawatl language. Nawatl (or Nahuatl) is an Amerindian language of the $π$-language type, i.e. a language with few digital resources, in which the corpora available for machine learning are virtually non-existent. The objective here is to generate a significant number of grammatically correct artificial sentences, in order to increase the corpora available for language model training. We want to show that a grammar enables us sig…

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[4/7]:
- DCP: Addressing Input Dynamism In Long-Context Training via Dynamic Context Parallelism
Chenyu Jiang, Zhenkun Cai, Ye Tian, Zhen Jia, Yida Wang, Chuan Wu

@…
my confession, your reward:
https://www.reddit.com/r/freebsd/comments/1o2lara/comment/nix1qpk/?context=1
― thank you | …

How Does the Pretraining Distribution Shape In-Context Learning? Task Selection, Generalization, and Robustness
Wa\"iss Azizian, Ali Hasan
https://arxiv.org/abs/2510.01163 …

How Does the Pretraining Distribution Shape In-Context Learning? Task Selection, Generalization, and Robustness
The emergence of in-context learning (ICL) in large language models (LLMs) remains poorly understood despite its consistent effectiveness, enabling models to adapt to new tasks from only a handful of examples. To clarify and improve these capabilities, we characterize how the statistical properties of the pretraining distribution (e.g., tail behavior, coverage) shape ICL on numerical tasks. We develop a theoretical framework that unifies task selection and generalization, extending and sharpeni…

EntropyLong: Effective Long-Context Training via Predictive Uncertainty
Junlong Jia, Ziyang Chen, Xing Wu, Chaochen Gao, Zijia Lin, Debing Zhang, Songlin Hu, Binghui Guo
https://arxiv.org/abs/2510.02330

EntropyLong: Effective Long-Context Training via Predictive Uncertainty
Training long-context language models to capture long-range dependencies requires specialized data construction. Current approaches, such as generic text concatenation or heuristic-based variants, frequently fail to guarantee genuine long-range dependencies. We propose EntropyLong, a novel data construction method that leverages predictive uncertainty to verify dependency quality. Our approach identifies high-entropy positions in documents, retrieves semantically relevant contexts from large co…