Research Agent

The Research Agent is your AI-powered research assistant. It can search academic databases, analyze papers, and help you build comprehensive literature reviews.

Research Agent in Action

Capabilities

🔍 Academic Paper Search

The Research Agent is integrated with:

Semantic Scholar — Access millions of academic papers
arXiv — Preprints in physics, mathematics, computer science, and more

Ask a Research Question

Start by describing what you're looking for:

Find recent papers on transformer architectures for medical image segmentation

Review Results

The agent will search academic databases and present relevant papers with:

Title and authors
Publication year and venue
Citation count
Brief summary

Deep Dive

Ask for more details on specific papers to understand their methodology or results:

Tell me more about the TransUNet paper. What are its main contributions?

📚 Literature Review Organization

The Research Agent can maintain structured notes in a research-notes.md file:

## Literature Review: Vision Transformers

### Key Papers

1. **ViT: An Image is Worth 16x16 Words**
   - Authors: Dosovitskiy et al. (2020)
   - Key insight: Pure transformer architecture for images
   - Citations: 15,000+

2. **Swin Transformer**
   - Authors: Liu et al. (2021)
   - Key insight: Hierarchical vision transformer with shifted windows
   - Citations: 8,000+

Ask the agent to "organize my research notes" or "add this paper to my literature review" to keep everything structured.

📖 Citation Generation

Get properly formatted citations instantly:

Generate a BibTeX citation for the Vision Transformer paper

The agent will provide:

@article{dosovitskiy2020image,
  title={An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale},
  author={Dosovitskiy, Alexey and Beyer, Lucas and Kolesnikov, Alexander},
  journal={arXiv preprint arXiv:2010.11929},
  year={2020}
}

Give me the APA citation for this paper

Result:

Dosovitskiy, A., Beyer, L., Kolesnikov, A., et al. (2020). An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. arXiv preprint arXiv:2010.11929.

Format this in MLA style

Result:

Dosovitskiy, Alexey, et al. "An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale." arXiv preprint arXiv:2010.11929 (2020).

📄 PDF Analysis

For arXiv papers, the agent can download and analyze full-text PDFs:

Download and summarize the methodology section of arXiv:2010.11929

Full-text analysis is currently available for arXiv preprints. Support for other sources is coming soon.

Example Prompts

Here are effective prompts to get the most from the Research Agent:

Finding Papers

"Find papers about federated learning in healthcare published after 2022"
"What are the most cited papers on graph neural networks?"
"Search for work by Yoshua Bengio on attention mechanisms"

Understanding Papers

"Summarize the key contributions of this paper"
"What datasets did they use for evaluation?"
"Explain their proposed architecture in simple terms"

Building Reviews

"Create a bibliography section from our discussed papers"
"Categorize these papers by methodology"
"What gaps exist in the current literature based on our research?"

Tips for Better Results

Be Specific About Scope

Include time ranges, venues, or author names to narrow search results.

Ask Follow-up Questions

The agent remembers context. Build on previous responses for deeper understanding.

Request Comparisons

Ask the agent to compare methodologies, results, or approaches across papers.

Research Agent

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