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Open Source Science

https://github.com/amazon-science/comm-prompt

CoMM: Collaborative Multi-Agent, Multi-Reasoning-Path Prompting for Complex Problem Solving (NAACL 2024 Findings))

https://github.com/amazon-science/comm-prompt

Science Score: 13.0%

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    Low similarity (4.5%) to scientific vocabulary
Last synced: 9 months ago · JSON representation

Repository

CoMM: Collaborative Multi-Agent, Multi-Reasoning-Path Prompting for Complex Problem Solving (NAACL 2024 Findings))

Basic Info
  • Host: GitHub
  • Owner: amazon-science
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 15.6 KB
Statistics
  • Stars: 16
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 2 years ago · Last pushed about 2 years ago
Metadata Files
Readme Contributing License Code of conduct

README.md

CoMM

This repo contains the code and data for the CoMM (Collaborative Multi-Agent, Multi-Reasoning-Path Prompting) system.

Model

Experiments

College Physics - Few Shot

commandline python run_pathways.py --task college_physics --prompt_type pathways

College Physics - Zero Shot

commandline python run_pathways.py --task college_physics --prompt_type multi_agent

Moral Scenarios - Few Shot

commandline python run_pathways.py --task moral_scenarios --prompt_type pathways

Moral Scenarios - Zero Shot

commandline python run_pathways.py --task moral_scenarios --prompt_type multi_agent

Baselines

You can also reproduce the standard and chain-of-thought baselines by changing the prompt_type argument as std or cot, and the context argument as zero or few.

Evaluation

Please use the evaluate() function for evaluation, with the generated result files in the logs and the source test data files.

Owner

  • Name: Amazon Science
  • Login: amazon-science
  • Kind: organization

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