Show HN: Flashpapers – Interactive explainers for AI papers

Flashpapers launched as a tool that turns an arXiv or ChinaRxiv link into an interactive explainer site covering a paper's idea, method and numbers, with the site claiming 100+ papers are already interactive. Users sign in with Google and supply their own API key from Google AI Studio, Anthropic or OpenRouter, with provider charges depending on model, paper length and generated output including reasoning tokens. Featured papers include LoRA (WikiSQL 74.0%), DDPM (CIFAR10 9.46) and Spurious Rewards: Rethinking Training Signals in RLVR (MATH-500 70.8%).

Explore papers https://flashpapers.ai/explore 100+ papers already interactive → https://flashpapers.ai/explore Read the paper. Then play with it. Paste an arXiv or ChinaRxiv link. Get back a beautifully designed, fully interactive site that explains the paper — its big idea, its method, its numbers — with charts you can poke and diagrams you can scrub through. Sign in with Google and bring your own API key. Get a Google key at aistudio.google.com https://aistudio.google.com , or use your Anthropic or OpenRouter key. Provider charges depend on the model, paper length, and generated output, including reasoning tokens. Check your provider’s current pricing and limits. Featured papers Browse all → https://flashpapers.ai/explore Featuredcs.CL · 2021Code· 14k★ https://flashpapers.ai/p/axwndcargc LoRA: Low-Rank Adaptation of Large Language Models WikiSQL: 74.0% Edward J. Hu, Yelong Shen +6 An important paradigm of natural language processing consists of large-scale pre-training on general domain data and adaptation to particular tasks or domains. As we pre-train… Featuredcs.LG · 2020Code· 5.2k★ https://flashpapers.ai/p/xtmvm69j2h Denoising Diffusion Probabilistic Models DDPM CIFAR10: 9.46 Jonathan Ho, Ajay Jain, Pieter Abbeel We present high quality image synthesis results using diffusion probabilistic models, a class of latent variable models inspired by considerations from nonequilibrium… Featuredcs.AI · 2025Code https://flashpapers.ai/p/bnb9crsych Spurious Rewards: Rethinking Training Signals in RLVR MATH-500: 70.8% Rulin Shao, Shuyue Stella Li +12 We show that reinforcement learning with verifiable rewards RLVR can elicit strong mathematical reasoning in certain language models even with spurious rewards that have… - Long-context comprehension Whole-paper reasoning — methods, figures, appendix — in one shot. - Interactive by default Sliders, animated diagrams, scrollytelling, live mini-demos. - Seconds, not minutes Your chosen model streams the page as it writes it — no waiting for a finished render.