Skip to content

Commit

Permalink
Update README.md
Browse files Browse the repository at this point in the history
  • Loading branch information
mtian8 authored Jul 24, 2024
1 parent 5a0d521 commit b37c5ad
Showing 1 changed file with 2 additions and 2 deletions.
4 changes: 2 additions & 2 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -5,8 +5,8 @@

This repo contains the evaluation code for the paper "[SciCode: A Research Coding Benchmark Curated by Scientists](https://arxiv.org/abs/2407.13168)"

## News
[2024-07-24]: We add the scientist-annotated background and support setup for w/ background evaluation.
## 🔔News
**🔥[2024-07-24]: We add the scientist-annotated background and support setup for w/ background evaluation.**

## Introduction
SciCode is a challenging benchmark designed to evaluate the capabilities of language models (LMs) in generating code for solving realistic scientific research problems. It has a diverse coverage of **16** subdomains from **6** domains: Physics, Math, Material Science, Biology, and Chemistry. Unlike previous benchmarks that consist of exam-like question-answer pairs, SciCode is converted from real research problems. SciCode problems naturally factorize into multiple subproblems, each involving knowledge recall, reasoning, and code synthesis. In total, SciCode contains **338** subproblems decomposed from **80** challenging main problems, and it offers optional descriptions specifying useful scientific background information and scientist-annotated gold-standard solutions and test cases for evaluation. Claude3.5-Sonnet, the best-performing model among those tested, can solve only **4.6%** of the problems in the most realistic setting. Broadly, SciCode demonstrates a realistic and scientists' everyday workflow of identifying critical science concepts and facts and then transforming them into computation and simulation code. We believe SciCode not only helps demonstrate contemporary LLMs' progress towards helpful assistant for scientists but also helps shed light on future building and evaluation of scientific AI.
Expand Down

0 comments on commit b37c5ad

Please sign in to comment.