# Recent open access papers with PDF links

**Use case:** 

The newest open access papers on a topic since 2025, each with a free PDF link, DOI and abstract, for a quick reading list.

## Input

```json
{
  "query": "large language model agents",
  "queries": [
    "retrieval augmented generation",
    "transformer language models survey"
  ],
  "sources": [
    "openalex",
    "crossref",
    "arxiv",
    "pubmed"
  ],
  "maxResults": 10,
  "sort": "date",
  "yearFrom": 2025,
  "yearTo": 2025,
  "openAccessOnly": true,
  "contactEmail": "name@example.com"
}
```

## Output

```json
{
  "type": {
    "label": "Row type",
    "format": "string"
  },
  "query": {
    "label": "Search",
    "format": "string"
  },
  "rank": {
    "label": "Rank",
    "format": "integer"
  },
  "title": {
    "label": "Title",
    "format": "string"
  },
  "authors": {
    "label": "Authors",
    "format": "array"
  },
  "authorCount": {
    "label": "Author count",
    "format": "integer"
  },
  "year": {
    "label": "Year",
    "format": "integer"
  },
  "publicationDate": {
    "label": "Published",
    "format": "string"
  },
  "venue": {
    "label": "Venue",
    "format": "string"
  },
  "doi": {
    "label": "DOI",
    "format": "string"
  },
  "url": {
    "label": "Link",
    "format": "string"
  },
  "pdfUrl": {
    "label": "PDF",
    "format": "string"
  },
  "openAccessUrl": {
    "label": "Free full text",
    "format": "string"
  },
  "abstract": {
    "label": "Abstract",
    "format": "string"
  },
  "abstractSource": {
    "label": "Abstract from",
    "format": "string"
  },
  "citationCount": {
    "label": "Citations",
    "format": "integer"
  },
  "isOpenAccess": {
    "label": "Open access",
    "format": "boolean"
  },
  "sources": {
    "label": "Found in",
    "format": "array"
  },
  "paperType": {
    "label": "Paper type",
    "format": "string"
  },
  "isSurvey": {
    "label": "Review or survey",
    "format": "boolean"
  },
  "bibtex": {
    "label": "BibTeX",
    "format": "string"
  },
  "openalexId": {
    "label": "OpenAlex ID",
    "format": "string"
  },
  "arxivId": {
    "label": "arXiv ID",
    "format": "string"
  },
  "pmid": {
    "label": "PubMed ID",
    "format": "string"
  },
  "pmcid": {
    "label": "PMC ID",
    "format": "string"
  },
  "summaryText": {
    "label": "Summary",
    "format": "string"
  },
  "duplicateOf": {
    "label": "Repeat of",
    "format": "string"
  },
  "source": {
    "label": "Failed source",
    "format": "string"
  },
  "message": {
    "label": "Error",
    "format": "string"
  },
  "retrievedAt": {
    "label": "Retrieved at",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Research Papers Search API: arXiv, PubMed, Crossref, DOI Actor is ready to run with the inputs already set for "Recent open access papers with PDF links". [Sign up or log in](https://console.apify.com/create-task-from-example/BeY9vztF0mQDVgpj9) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Recent open access papers with PDF links" task

The Research Papers Search API: arXiv, PubMed, Crossref, DOI Actor will start running based on the input automatically. You can also change all the input fields, like search, more searches, and more, to match your specific use case.

### 3. Receive the "Recent open access papers with PDF links" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as row type, search, rank, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Recent open access papers with PDF links" task via API](https://apify.com/solidfetch/research-papers.md).

## About this Actor

This example demonstrates how to use [Research Papers Search API: arXiv, PubMed, Crossref, DOI](https://apify.com/solidfetch/research-papers.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/solidfetch/research-papers.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/solidfetch/research-papers.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).