Show HN: Papiers.ai – A new interface for ArXiv (twitter.com)

Show HN: Papiers.ai is a newly announced, lightweight interface built on top of arXiv that aims to streamline how researchers discover, read and organize preprints. The project — presented to the Hacker News community as a focused front end for arXiv’s corpus — emphasizes faster browsing, better filtering and paper-level tools (saved lists, alerts, and improved metadata views) compared with the default site. The launch post invites early users to try the UI and give feedback, positioning Papiers.ai as an alternative discovery layer rather than a replacement for arXiv’s content. For AI/ML practitioners the significance is practical: cleaner discovery workflows reduce time spent hunting related work and make literature triage more scalable. Technically, such interfaces typically integrate the arXiv API and PDF scraping/parsing, build searchable indices (often with full-text or abstract embeddings), and add features like similarity search, topic clustering, citation extraction and automated summarization. That enables faster related-work queries, reproducible reading lists, and easier dataset/model provenance checks. If Papiers.ai incorporates ML-powered features (e.g., semantic search or auto-summaries), it could become a useful research productivity layer and a testbed for evaluating retrieval and summarization tools on ongoing arXiv traffic.