
TL;DR Scholar
Skip the abstract. Get the core finding instantly.
What it does
What makes TL;DR Scholar different: 🇨🇳 Native Chinese paper support—not an afterthought 🧠 Summaries include significance, not just "what they did" 🎭 Reviewer-style critique mode ("tough reviewer" / "logic geek") 🆓 8 free summaries/day, no signup required ⚡ 10-second results from PDF, Word, or pasted text
Does the same job
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Highlight & Summarize: PDF Companion2024 · ▲129Highlight & summarize PDFs effortlessly with powerful tool
- SRSave reading time with the TL;DR PLZ bookmarklet2011 · ▲44
Hey all, this is a small bookmarklet my partner made last week to save short summaries of long-winded web posts. Hopefully you can help others save time by sharing your TL;DRs with the world. You can also up/downvote the TL;DRs other users post. It should work with your iPad, too. http://tldrplz.com

More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com


Launched alongside, May 2026
the whole month →

Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai


- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com