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arXiv:2603.21393v2 Announce Type: replace Abstract: The widespread use of AI and ML models in sensitive areas raises significant concerns about fairness. While the research community has introduced various methods for bias mitigation in binary classification tasks, the issue remains under-explored in multi-class classification settings. To address this limitation, in this paper, we first formulate the problem of fair learning in multi-class classification as a multi-objective problem between eff

arXiv:2605.14477v2 Announce Type: replace Abstract: We introduce EvoLib, a test-time learning framework that enables large language models to accumulate, reuse, and evolve knowledge across problem instances without parameter updates or external supervision. Instead of adapting model parameters, our approach maintains a shared library of knowledge abstractions, including modular skills and reflective insights, automatically extracted from the model's own inference trajectories. To support continu

arXiv:2605.18147v2 Announce Type: replace Abstract: Predictive models play a pivotal role in credit risk management, guiding critical decisions through accurate estimation of default probabilities and losses. Extensive research has introduced new modeling techniques, complemented by large-scale benchmarking studies consolidating the state-of-the-art. Today, quasi-standards such as gradient-boosting models paired with SHAP explainers have emerged, yet continuous improvement of risk models remains

arXiv:2605.24395v2 Announce Type: replace Abstract: Alignment plays a fundamental role in many machine learning problems, such as multi-network analysis, multimodal learning, and point cloud registration. Recent works increasingly leverage optimal transport (OT) for distributional alignment, whose effectiveness largely depends on sparse supervision that is hard or costly to obtain in practice. Existing works, however, largely overlook how to actively acquire high-quality supervision to improve t

arXiv:2605.26477v2 Announce Type: replace Abstract: While Deep Neural Networks (DNNs) achieve remarkable performance, their tendency to produce overconfident predictions. Evidential Deep Learning (EDL) mitigates this by formulating predictions as a Dirichlet distribution over class probabilities to explicitly quantify epistemic uncertainty. However, we found that the conventional EDL suffers from two fundamental limitations: a Kullback-Leibler (KL) penalty that only suppresses the evidence of ne

arXiv:2605.31272v2 Announce Type: replace Abstract: As predictive models are increasingly deployed in high-stakes settings such as credit approval, there is a growing need for post-hoc methods that provide recourse to affected individuals. Many such models operate on tabular data, where features correspond to real-world attributes. Recently, in-context learning (ICL) has enabled large language models to perform tabular prediction by conditioning on labeled examples at inference time, without exp

arXiv:2503.24092v2 Announce Type: replace-cross Abstract: Motivated by the rapidly growing field of mathematics for operator approximation with neural networks, we present a novel universal operator approximation theorem for broad classes of encoder-decoder architectures and a wide range of input and output spaces. In this study, we focus on the approximation of continuous operators between infinite-dimensional normed or metric spaces in the topology of uniform convergence on compact sets. Unlik

Article URL: https://www.youtube.com/watch?v=rqmJk9aIJ6I Comments URL: https://news.ycombinator.com/item?id=48930061 Points: 3 # Comments: 0

Article URL: https://github.com/sixvolts/familiar Comments URL: https://news.ycombinator.com/item?id=48930009 Points: 3 # Comments: 0

Comments

We've been working on an open-source coding agent that generates code alongside machine-checkable proofs. We'd love feedback from the HN community, especially from people interested in formal verification, Lean, Dafny, or AI coding agents. Currently, only 3 langauges can be verified. Comments URL: https://news.ycombinator.com/item?id=48929654 Points: 5 # Comments: 0

Article URL: https://old.reddit.com/r/vibecoding/comments/1uxpox5/i_reimplemented_the_core_workflows_of_40/ Comments URL: https://news.ycombinator.com/item?id=48929623 Points: 3 # Comments: 0

<p>Or will they forge a path of their own?</p><ul><li><p>See more of <a href="https://www.theguardian.com/profile/fiona-katauskas">Fiona Katauskas’s cartoons here</a></p></li></ul> <a href="https://www.theguardian.com/commentisfree/picture/2026/jul/16/will-the-new-ai-roadmap-keep-the-tech-giants-in-line">Continue reading...</a>

Article URL: https://www.channelnewsasia.com/singapore/tiktok-ai-women-disinformation-deepfake-presenters-6250271 Comments URL: https://news.ycombinator.com/item?id=48929445 Points: 4 # Comments: 0

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Keybridge lets an agent or a script run an npm publish that ends in a Touch ID tap instead of dying with EOTP. It automates npm's WebAuthn hand-off (the browser hop, the one-time-token relay, the retry) in a windowless WKWebView, and answers the ceremony from a Secure Enclave key that only signs after a live Touch ID. macOS, fully open source. Comments URL: https://news.ycombinator.com/item?id=48929255 Points: 2 # Comments: 0

<p><strong>Pre-dispatch authorization for AI sub-agents</strong> means checking a child spawn's grant envelope (its role, tools, path scope and token budget) against the parent's policy in the last plaintext moment before handoff, not by reading a trace afterwards. When the orchestrator encrypts the handoff, the after-view goes blind. The before-view does not, because it sits earlier on the timeline.</p> <p>On July 14, "Codex starts encrypting sub-agent prompts" hit <a href="https://news.ycombin

<pre style='white-space:pre-wrap;width:81ex'>improve: speed up Control UI browser tests (#108504) * test(ui): accelerate browser timing coverage * test(ui): stabilize Mantis elapsed-time proof * test(ui): keep Claude viewport proof isolated</pre>

<p>Every agent-security vendor tells you what they block. Nobody tells you what they miss.</p> <p>That gap is the whole problem. "We stop prompt injection" is a claim you cannot check. You cannot run it, and you cannot tell it apart from the next company saying the same sentence. So security engineers do the rational thing and discard all of it.</p> <p>I published the opposite. It is called the <strong>ARE Incident Database</strong>, and it is public: <a href="https://aredb.org" rel="noopener no

<p> AI account executives that demo and close B2B deals </p> <p> <a href="https://www.producthunt.com/products/river-9?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1197712?app_id=339">Link</a> </p>

Article URL: https://twitter.com/Akashi203/status/2077552491567157733 Comments URL: https://news.ycombinator.com/item?id=48929104 Points: 2 # Comments: 0

<p>If you are like me and use AI often to help with complicated tasks and own a Flipper Zero, you might want a Super Tiny Language Model (STLM). </p> <h2> Why this is useful </h2> <p>Until now, there have been no language models small enough to run on a small device, such as a Flipper Zero. Flippermind relies on lightweight Python3 installs and a local connection to Qwen2.5-0.5B. Although this is configured for Flipper Zero, you can run it on other small machines like a Raspberry Pi.</p> <h2> Ch

<p>Sleep is the cornerstone of health, yet millions suffer from undiagnosed sleep apnea. If you've ever wondered about the quality of your rest but felt uneasy about uploading hours of private bedroom audio to the cloud, you're in the right place. In this tutorial, we are building a privacy-first <strong>Sleep Snoring Monitoring System</strong> using <strong>Faster-Whisper</strong> and <strong>Voice Activity Detection (VAD)</strong>.</p> <p>By leveraging <strong>local AI deployment</strong> and

<p><strong>Tool:</strong> <a href="https://tools.simonwillison.net/grok-mermaid">Mermaid to Unicode box art (grok-mermaid)</a></p> <p>While <a href="https://simonwillison.net/2026/Jul/15/grok-build/">exploring the codebase</a> for the newly open-sourced Grok CLI coding agent I came across <a href="https://github.com/xai-org/grok-build/blob/b189869b7755d2b482969acf6c92da3ecfeffd36/crates/codegen/xai-grok-markdown/src/mermaid.rs">xai-grok-markdown/src/mermaid.rs</a>, a "self-contained terminal ren

Article URL: https://www.youtube.com/watch?v=iVkgD4phOHQ Comments URL: https://news.ycombinator.com/item?id=48929052 Points: 1 # Comments: 0

Article URL: https://github.com/JustMichael-80/MasterVault Comments URL: https://news.ycombinator.com/item?id=48928934 Points: 1 # Comments: 0

Thinking Machines' first open weights model is a 975 billion parameter alternative to Chinese LLMs

Article URL: https://www.aicss.dev Comments URL: https://news.ycombinator.com/item?id=48928924 Points: 1 # Comments: 0

Kevin here, indie dev (lorisLabs.) Thorttle started as a menu bar meter for Claude code usage, and grow into a cockpit ! you have the full claude meter as expected with no telemetry, no network. and that in the free version. Pro is where it got interesting : Cockpit have every claude code project on your Mac in one window. Each embedded terminal using SwiftTerm, auto hibernate to keep a 16gb Mac from getting out of memory. Remote Control that hand a session off to any linux server (I use proxmox

<pre style='white-space:pre-wrap;width:81ex'>fix(line): use precise control-command check for group mention bypass (#107230) * fix(line): use precise control-command check for group mention bypass Group requireMention bypass is gated on `command.hasControlCommand`, but LINE fed it the broad `shouldComputeCommandAuthorized` detector, which is true for any inline "/x"/"!x" token. An allowlisted member's plain message like "cd /home" would satisfy the bypass and reach the agent even though the bot

<p>When the PM talks about new laws applying to the ‘next generation of large-scale datacentres’ what does he mean?</p><ul><li><p><a href="https://www.theguardian.com/australia-news/2026/jul/16/albaneses-ai-blueprint-sparks-calls-for-datacentre-moratorium-until-new-regulations-in-place">Albanese’s AI blueprint sparks calls for datacentre moratorium until new regulations in place</a></p></li></ul><p>Expectations were high as the prime minister took the stage at the University of Sydney on Wednesd

<pre style='white-space:pre-wrap;width:81ex'>fix(agents): prevent subagent registry resurrection (#105793) * fix(agents): retire legacy subagent registry JSON Co-authored-by: morluto <76467478+morluto@users.noreply.github.com> * fix(agents): keep migration decision internal Co-authored-by: morluto <76467478+morluto@users.noreply.github.com> * style(agents): format migration decision type Co-authored-by: morluto <76467478+morluto@users.noreply.github.com> --------- Co-authored-by: Peter Steinberg

The ISR Observability page now shows Observability Plus subscribers a write utilization metric, helping identify routes that regenerate often but receive few requests. Write utilization is the ratio of cached requests to ISR writes. For routes with low write utilization, consider increasing the revalidation interval or switching to on-demand revalidation to reduce costs. You can also compute write utilization using the Vercel CLI, or use agents with the cdn-caching skill to investigate. Learn mo

Kimi K3 from Moonshot AI is now available on AI Gateway. K3 is an open-source model with a 1M-token context window and native visual understanding, accepting text, image, and video inputs. Built for long-horizon software engineering, knowledge work, and deep reasoning, K3 is especially strong where code meets visual and spatial reasoning, which suits frontend, game development, and CAD workflows. Thinking mode is always on. To use Kimi K3, set model to moonshotai/kimi-k3 in the AI SDK : AI Gatew

Cars24 uses OpenAI-powered voice and chat agents to handle 1M+ monthly conversation minutes, recover 12% of lost leads, and bring agentic workflows to teams across the company.

Incremental video search requires high-quality ranking after each keystroke, where intent is often underspecified (e.g., 1–3 character prefixes). We present a personalization system for Apple TV search that combines complementary semantic and collaborative signals at ranking time. Our approach learns two item embedding spaces: (i) a text-based multilingual encoder (TextEmb) fine-tuned on co-engagement triplets via contrastive learning, and (ii) an ID-based collaborative embedding model (IdEmb) t

Can a large language model (LLM) improve at code generation using only its own raw outputs, without a verifier, a teacher model, or reinforcement learning? We answer in the affirmative with simple self-distillation (SSD): sample solutions from the model with certain temperature and truncation configurations, then fine-tune on those samples with standard supervised fine-tuning. SSD improves Qwen3-30B-Instruct from 42.4% to 55.3% pass@1 on LiveCodeBench v6, with gains concentrating on harder probl

Microsoft is looking to sell its in-house AI models as more efficient and cost-effective than its competitors' models.

Article URL: https://lore.kernel.org/linux-media/CAHk-=wi4zC+Ze8e+p3tMv8TtG_80KzsZ1syL9anBtmEh5Z40vg@mail.gmail.com/ Comments URL: https://news.ycombinator.com/item?id=48928697 Points: 11 # Comments: 2

Article URL: https://lhv.ai/ Comments URL: https://news.ycombinator.com/item?id=48928679 Points: 1 # Comments: 0