How to Integrate arXiv Papers into Your AI (2025 Guide)

TL;DR

Valyu’s Search API gives you instant access to millions of research papers from PubMed, arXiv, and top academic domains all in structured, LLM-ready JSON.
With just 3 lines of code, you can pull abstracts, metadata, and semantic matches straight into your AI app, agent, or retrieval pipeline.
Works out of the box with LangChain, Vercel AI SDK, or LlamaIndex.

Why Research Papers Matter for AI Builders

Whether you’re building a biotech RAG agent or an AI researcher’s copilot, you need access to primary sources. Integrating peer-reviewed and preprint literature is critical for:

Evidence-grounded reasoning
Research summarization tools
Literature review agents
Citation and related work discovery
Biomedical R&D copilots
Trend tracking in AI, ML, and hard science

Valyu gives your app access to structured academic data — no scraping, no PDFs, no patchwork APIs.

The Problem With Traditional Access

PubMed is keyword-only and returns XML/HTML
arXiv has limited metadata and no semantic search
Most academic sites block crawlers or require scraping
No unified interface for life sciences + ML literature
Search engines return SEO spam, not structured papers

And even when you get a paper, parsing the metadata, extracting key sections, or aligning citation data takes custom tooling.

The Fast Way: Use Valyu’s Research Paper Search API

Valyu provides structured access to:

PubMed – peer-reviewed biomedical research
arXiv – preprints across physics, ML, and hard science
Top journals – Wiley

3-Line Integration

TypeScript

import { Valyu } from 'valyu-js';
 
const valyu = new Valyu({ apiKey: 'your-valyu-api-key' });
 
const response = await valyu.search(
  "recent research on CRISPR off-target effects 2024"
);
 
console.log(response);

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Read full integration docs

Example Use Cases

🧠 AI Research Assistant
“Summarize recent arXiv papers on retrieval-augmented generation.”

💊 Biotech Literature Copilot
“Find PubMed papers discussing CAR-T therapy in pediatric leukemia.”

📎 Citation Discovery Tool
“Find related work on LoRA fine-tuning for large language models.”

📚 Evidence Synthesis Agent
“Combine PubMed + arXiv results to explain how Transformer architectures evolved.”

Advanced Usage Example

Target high-quality, recent research from multiple academic domains:

TypeScript

const response = await valyu.search(
  "checkpoint inhibitor resistance mechanisms in melanoma",
  {
    included_sources: [
      "valyu/valyu-pubmed",
      "valyu/valyu-arxiv",
      "nature.com",
      "acm.org"
    ],
    start_date: "2025-01-01",
    max_num_results: 10
  }
);

💡 Use response_length: "large" if you want full abstracts + key sections for deeper context.

Live Demo

Try the Research Papers Demo

Search across PubMed, arXiv, and curated journals in natural language.

Stream structured results - title, authors, abstract, date, source — directly into your agent or retrieval chain.

Best Practices

Be specific — include key terms, methods, or compound names
For biomedical use cases, pair valyu-pubmed with valyu-clinical-trials
Use date_range to focus on recency
Include journal domains to access non-open-access metadata (e.g., Wiley)
Limit max_num_results to 3–10 for lower token overhead

FAQ (Schema-Enabled)

Q: What sources does Valyu support for research papers?
A: PubMed, arXiv, and metadata from top journals like Nature, Science, IEEE, and ACM.

Q: Do you return full text?
A: Abstracts and metadata are always included. Full text is returned where permitted (e.g., arXiv or open-access PubMed).

Q: Can I filter by year, author, or domain?
A: Yes - include those filters in your query or use structured config parameters.

Q: Is this suitable for citation and related work agents?
A: Yes - Valyu can surface related papers, author networks, and DOIs for reference chaining.

Integrate Research Papers the Right Way

Valyu gives you one interface for all the world’s research - preprints, peer-reviewed studies, and academic metadata - fully searchable and structured for LLM use.

Get your API key
Explore the docs
Use with LangChain