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AI & Machine Learning Papers (arXiv)
da6b2e9a-342a-410c-9d40-399bff5898a1ai-papers-v3Curated, machine-readable feed of recent computer science and machine learning preprints from arXiv. Records are normalized to a stable JSON schema suitable for agents and analytics pipelines, including metadata, canonical links, abstracts, and a concise one-sentence insight. 1. Data is ingested on a scheduled basis via the provider push API; 2. Consumers retrieve the current snapshot through the standard read API with cursor-based pagination.
Data Health & History
Agent-Native Workbench
Add this skill to your OpenClaw skill directory to enable autonomous data fetching.
One-line install
curl -fsSL https://pipeagent.dev/install.sh | bash -s -- --alias "ai-papers-v3"
Documentation
Overview
This data product delivers recent arXiv preprints relevant to artificial intelligence and machine learning, presented as a versioned collection (snapshot semantics per sync). Each record is a single paper with stable identifiers, bibliographic fields, abstract text, and a one-sentence insight intended for quick scanning by humans and downstream agents.
Data source and provenance
one_sentence_insight is produced with a local heuristic. Optionally, the provider job may be configured to use an external language model; that mode is operational only and does not change the consumer contract.Update cadence
Consumer API
Authenticated clients retrieve data with:
GET https://api.pipeagent.dev/v1/feed/{FEED_ID}
x-api-key: YOUR_READ_KEYBearer authentication is also supported where configured for your account.
Common query parameters
| Parameter | Purpose |
|---|---|
limit | Page size (capped by platform policy; default if omitted). |
cursor | Opaque cursor for the next page when metadata.has_more is true. |
jsonpath | Optional projection of the JSON payload (subject to platform limits). |
ids | Comma-separated list of business keys (id field) for targeted retrieval when supported. |
Pagination follows cursor-first semantics: rely on has_more and next_cursor rather than inferring totals from partial pages.
Response schema (records)
Each element of the top-level array is an object with at least:
| Field | Type | Description |
|---|---|---|
id | string | Stable paper identifier in this feed (e.g. derived from arXiv id / version). |
title | string | Paper title. |
authors | string[] | Author list in display order. |
publish_date | string | Publication or announcement date (ISO-8601 date or datetime string). |
abstract | string | Full abstract text where available. |
one_sentence_insight | string | Short, non-authoritative summary for triage. |
link | string | Canonical URL to the paper on arXiv. |
captured_at | string | UTC timestamp when the record was captured for this feed. |
Required fields for validation: id, title, link.
Example record
{
"id": "arxiv:2401.00001v1",
"title": "Example: On scalable training of transformer models",
"authors": ["A. Researcher", "B. Scientist"],
"publish_date": "2024-01-15",
"abstract": "We study methods for efficient training under resource constraints…",
"one_sentence_insight": "Proposes practical techniques to reduce training cost while preserving accuracy.",
"link": "https://arxiv.org/abs/2401.00001",
"captured_at": "2026-03-23T12:00:00.000Z"
}Provider operations (reference)
Ingestion is performed by the repository job SelfMadeFeeds/arxiv-papers/crawler.ts, which posts to:
POST /api/v1/provider/feed/{FEED_ID}/pushusing a write API key. Large runs may split payloads across multiple posts sharing a batch id; refer to the provider integration guide for batch_complete semantics.
Pricing
Per-call pricing follows the price per 1,000 calls (price_per_1k) shown on the feed listing. Free promotional credits, if available on your account, are applied before metered charges according to platform billing rules.
Disclaimer
arXiv and paper metadata are third-party sources. This feed does not constitute peer review, investment, or legal advice. Verify critical facts against primary publications and official arXiv pages.