Academic research guide
Token compression for research paper analysis
Research papers are long (3,000-10,000 tokens each) and dense. When analyzing papers with LLMs, most of the text is irrelevant to a specific research question. Compression keeps the findings and methodology sections that matter.
Paper analysis with compression
from supercompress import Compressor
comp = Compressor()
def analyze_paper(paper_text, research_question):
result = comp.compress(paper_text, research_question)
return llm.generate(
f"Research question: {research_question}\nPaper:\n{result.compressed_text}"
)Frequently asked questions
Does compression preserve citations?
Yes. Lines containing citations relevant to the research question are preserved.
Can I analyze multiple papers simultaneously?
Yes. Compress each paper independently and combine the compressed results for cross-paper analysis.
Try it yourself
Paste your long prompt into the playground, ask a question, and see what SuperCompress keeps and removes. Free, no signup needed.