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arXiv:2606.28344v1 Announce Type: cross Abstract: Augmenting large language models (LLMs) with retrieved web text has become a dominant paradigm, yet the web is not natively textual: existing systems depend on complex parsing pipelines that linearize HTML and discard layout, visual structure, and formatting. We introduce PixelRAG, a new retrieval-augmented method that represents websites in their native visual form and performs retrieval and reading entirely in pixel space, enabling an end-to-en

arXiv:2606.28345v1 Announce Type: cross Abstract: LLM-governed social robots increasingly decide who receives real-world assistance first. As prioritization norms vary across cultures by age, status, and group size, failure to calibrate pluralistically can scale into unequal access. Yet LLM moral audits remain English-centered, rarely test embodied contexts, leaving pluralistic calibration as an urgent diagnostic gap amid intensifying LLM-robot deployment. We introduce a gradient-based audit fra

arXiv:2606.28352v1 Announce Type: cross Abstract: Multi-turn retrieval-augmented generation (RAG) is challenging due to evolving user intent, conversational noise, and strict context limits. We propose a training-free hybrid retrieval pipeline for SemEval-2026 Task 8 that combines dense and sparse retrieval with controlled query rewriting and cross-encoder reranking. On the official test set of Task A, our system achieves 0.5453 nDCG@5, ranking third among 38 teams and outperforming the stronges

arXiv:2606.28358v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) aims to enhance the trustworthiness of Large Language Models (LLMs) by grounding their outputs in external documents, often using inline citations for verifiability. However, the faithfulness of these citations -- whether the model genuinely uses a source to generate an answer -- remains a critical, unverified assumption. This paper offers the first mechanistic account of how a large language model decides whe

arXiv:2606.28362v1 Announce Type: cross Abstract: Systematic reviews and meta-analyses (SR/MA) remain the gold standard for evidence synthesis, yet completing one typically requires 67 weeks and substantial expert effort. Recent large language model (LLM) systems have demonstrated strong performance on individual SR phases - screening (otto-SR: 96.7% sensitivity), extraction (Gartlehner et al.: 91.0% accuracy), and search (TrialMind: 0.83 recall) - but no study has reported what it actually cost

arXiv:2606.28379v1 Announce Type: cross Abstract: We introduce LEDGER to tackle the novel context engineering challenge of agentic document editing, where localized edits to long, structured documents must be applied efficiently without breaking cross-references or semantic consistency. LEDGER constructs a lightweight dependency graph that explicitly models document structure, including hierarchical organization, explicit references, implicit dependencies, and semantic relationships. For each ed

arXiv:2606.28445v1 Announce Type: cross Abstract: Early detection of dementia enables timely intervention, and reflecting cognitive impairment, spontaneous speech offers a non-invasive screening modality. Conventional approaches often focus on a single representational dimension -- such as acoustic descriptors, pause modeling, automatic speech recognition (ASR) transcripts, or multimodal fusion -- limiting integrative reasoning across heterogeneous cognitive symptoms. We propose a low-rank adapt

arXiv:2606.28514v1 Announce Type: cross Abstract: Multimodal models are increasingly deployed to solve tasks collaboratively with humans or other artificial agents. Existing benchmarks show that these models possess many of the required component capabilities, but the conditions that coincide in collaboration, including time pressure, information asymmetry, and imperfect communication, are usually studied in isolation. We introduce GPTNT, a benchmark built on the cooperative video game Keep Talk

Hey everyone we recently built a platform for people to share their audio ml creations and we are hoping to create it so people in the community can find demos of their models and eventually monetize their trained models. We are a team of small creators who are trying to improve the space for open source ML so the future is not dominated by closed source giants like ElevenLabs or chatgpt. if you have any feedback please feel free to share. Comments URL: https://news.ycombinator.com/item?id=48728

<p> Build with coding agents from anywhere </p> <p> <a href="https://www.producthunt.com/products/cursor?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="http://www.producthunt.com/r/p/1184233?app_id=339">Link</a> </p>

<p> Build with coding agents from anywhere </p> <p> <a href="https://www.producthunt.com/products/cursor-for-ios?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/1184233?app_id=339">Link</a> </p>

Article URL: https://github.com/ztxz16/fastllm Comments URL: https://news.ycombinator.com/item?id=48728290 Points: 3 # Comments: 0

Article URL: https://arxiv.org/abs/2512.13564 Comments URL: https://news.ycombinator.com/item?id=48728214 Points: 2 # Comments: 0

Article URL: https://snaptoai.app Comments URL: https://news.ycombinator.com/item?id=48728161 Points: 3 # Comments: 0

Article URL: https://aistorygenerator.work Comments URL: https://news.ycombinator.com/item?id=48728140 Points: 3 # Comments: 0

Article URL: https://drifty.so/ Comments URL: https://news.ycombinator.com/item?id=48728127 Points: 1 # Comments: 0

<p> Produce sharpened results faster with a team of AI experts </p> <p> <a href="https://www.producthunt.com/products/workbuddy-2?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/1184211?app_id=339">Link</a> </p>

<p> A personal AI agent that runs on your desktop and iPhone </p> <p> <a href="https://www.producthunt.com/products/flowly-6?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/1184210?app_id=339">Link</a> </p>

Wix-owned vibe coding platform Base44 has started rolling out its own AI model — with hopes that it will eventually outperform frontier models.

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Article URL: https://www.youtube.com/watch?v=0GQ2RP-25gM Comments URL: https://news.ycombinator.com/item?id=48727856 Points: 3 # Comments: 0

Article URL: https://www.kimi.com/aicard Comments URL: https://news.ycombinator.com/item?id=48727792 Points: 4 # Comments: 1

Article URL: https://kunyuan.substack.com/p/ai-does-not-have-to-kill-humans-to Comments URL: https://news.ycombinator.com/item?id=48727764 Points: 5 # Comments: 0

Article URL: https://cyrusradfar.com/thoughts/the-lake-they-couldnt-see Comments URL: https://news.ycombinator.com/item?id=48727755 Points: 3 # Comments: 0

Article URL: https://www.ft.com/content/8f872761-76d9-43c7-bbcd-d313c4732e81 Comments URL: https://news.ycombinator.com/item?id=48727708 Points: 7 # Comments: 0

Hey Guys, I would like to showcase Tiny Agents, which is an entirely Rust-based RLM. RLMs are a recent and fantastic new innovation on how LLMs can be reimagined by designing the LLM agent itself to define how it will orchestrate or create its own sub-agent. I also could not find any good LLM harness workflow in Rust, so I built this one, taking massive inspiration from LangGraph and LangChain but also incorporating a Rust-based transpiler to build on-demand LLM graphs all in Rust following the

Article URL: https://mrkt30.com/why-wont-europe-build-ai-data-centers-in-iceland/ Comments URL: https://news.ycombinator.com/item?id=48727538 Points: 29 # Comments: 25

Hello Folks! Agentic Orchestrator is a terminal tool that takes complex feature requests and builds them by orchestrating coding agents through a series of phases that emulate a full-fledged engineering flow: requirements clarification, research, design, multi-phase planning, implementation, and review. It is a single pane of glass for all your features and exposes post-publish utilities such as resolving merge conflicts and responding to review comments. The key design choice is that this is de

Article URL: https://homebutler.dev/ Comments URL: https://news.ycombinator.com/item?id=48727396 Points: 1 # Comments: 0

Article URL: https://pdf-insight.com/ Comments URL: https://news.ycombinator.com/item?id=48727255 Points: 2 # Comments: 0

Article URL: https://www.getforay.ai/ Comments URL: https://news.ycombinator.com/item?id=48727207 Points: 2 # Comments: 0

<pre style='white-space:pre-wrap;width:81ex'>fix(cron): scope agent wake targets (#97949) * fix(cron): scope agent wake targets * fix(cron): refresh prompt snapshots</pre>

Article URL: https://www.404media.co/tidal-says-it-wont-pay-royalties-for-ai-generated-music/ Comments URL: https://news.ycombinator.com/item?id=48727144 Points: 3 # Comments: 4

I'm a solo founder building AMA2, a messaging runtime made for AI agents. This is my first Show HN, so I'd really appreciate your feedback. What brought me this idea: At first, I was building an AI agent for solo creators that knows everything about you and can do business chore on your behalf. When I tried to plug it into normal chat tools like Telegram, Discord, Slack... , they all felt wrong for agents: 1. They don't care about an agent's context. To follow a thread, the agent has to pull the

Article URL: https://github.com/azhakhan/dribble Comments URL: https://news.ycombinator.com/item?id=48727039 Points: 2 # Comments: 0

Article URL: https://github.com/SMJAI/open-memory-protocol Comments URL: https://news.ycombinator.com/item?id=48726966 Points: 5 # Comments: 1

OpenAI engineers used large-scale core dump analysis to debug rare infrastructure crashes, uncovering both a hardware fault and a long-standing software bug.

Vercel Agent pricing is changing. You no longer need to pre-load credits or manage a separate wallet for Vercel Agent. Instead of a $0.30 per-request fee, you now pay a Vercel Token Rate of $0.25 per million tokens, plus provider inference costs at the underlying token rate. The new Vercel Token Rate scales with the actual work each task requires. A quick question costs less than a deep investigation that reads your logs, deployments, configuration, and runtime data, spins up sandboxes, and writ

Claude Sonnet 5 from Anthropic is now available on AI Gateway . Sonnet 5 improves on Sonnet 4.6 across coding and agentic work, reaching outcomes on many tasks that previously needed an Opus model, at Sonnet pricing. The model is more agentic and follows instructions more closely. Document parsing and long-context memory use are also stronger. Sonnet 5 also uses an updated tokenizer, like the recent Opus models, which can map the same input to more tokens. Launch pricing of $2 per million input