Summary of Llm Reasoners: New Evaluation, Library, and Analysis Of Step-by-step Reasoning with Large Language Models, by Shibo Hao et al.
LLM Reasoners: New Evaluation, Library, and Analysis of Step-by-Step Reasoning with Large Language Models
by Shibo Hao, Yi Gu, Haotian Luo, Tianyang Liu, Xiyan Shao, Xinyuan Wang, Shuhua Xie, Haodi Ma, Adithya Samavedhi, Qiyue Gao, Zhen Wang, Zhiting Hu
First submitted to arxiv on: 8 Apr 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper addresses a significant challenge in developing Large Language Models (LLMs) by introducing two key innovations: AutoRace, an automatic method for evaluating generated reasoning chains on different tasks, and LLM Reasoners, a library for standardized implementation of existing and new reasoning algorithms. The authors aim to close the gap in evaluating diverse LLMs and reasoning strategies, which has been hindered by the lack of unified formalism and implementation. AutoRace creates detailed evaluation criteria tailored for each task, using GPT-4 for accurate evaluation, whereas LLM Reasoners provides a library for modular implementation of existing and new reasoning algorithms under a unified formulation of search, reward, and world model components. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps computers become better at thinking step-by-step. It wants to find out what makes different ways of thinking work well or not. The authors created two tools: one that automatically checks how well the computer is doing on different tasks, and another library that lets them try out different ways of thinking in a standardized way. They then used these tools to study different types of reasoning and found some interesting patterns. |
Keywords
» Artificial intelligence » Gpt
