Enter your research topic in the search box:


"attention mechanism transformer natural language processing"




Search results include:


- Paper title and author


- TLDR (AI generated one sentence summary)


- Citation count and impact score


- Year of publication and journal/conference




Filter options:


- Filter by year (only view the last 3 years)


- Sort by citation count


- Filter by open access (see only those that are free to download)

Open a paper and view:

1. "Cited By"
   - Which papers cited this article
   - Understand the impact of this paper

2. "References"
   - What work is cited in this paper?
   - Understand the research background

3. "Recommended Papers"
   -Related papers recommended by AI
   - Discover important work that may have been missed

import requests

# Search papers (no API Key required)
url = "https://api.semanticscholar.org/graph/v1/paper/search"
params = {
    "query": "large language models code generation",
    "limit": 5,
    "fields": "title,authors,year,citationCount,abstract"
}

response = requests.get(url, params=params)
papers = response.json()["data"]

for paper in papers:
    print(f"Title: {paper['title']}")
    print(f"Year: {paper['year']}")
    print(f"Citation count: {paper['citationCount']}")
    print(f"Abstract: {paper['abstract'][:200]}...")
    print()