Summary of Small Language Model Can Self-correct, by Haixia Han et al.
Small Language Model Can Self-correct
by Haixia Han, Jiaqing Liang, Jie Shi, Qianyu He, Yanghua Xiao
First submitted to arxiv on: 14 Jan 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 Generative Language Models (LMs) like ChatGPT have achieved impressive performance across various tasks, but they often generate inaccurate or false information with confidence. Previous studies developed complex pipelines and prompts to induce large LMs to correct their answers. However, these approaches are challenging for small LMs to follow. This paper introduces the Intrinsic Self-Correction (ISC) method in generative language models, aiming to enable self-triggered correction of initial outputs even for small LMs. The authors propose a pipeline for constructing self-correction data and Partial Answer Masking (PAM) to fine-tune the model for intrinsic self-correction. Experiments with LMs ranging from 6 billion to 13 billion parameters demonstrate that ISC outperforms non-self-corrected outputs in commonsense reasoning and factual knowledge tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine a super smart computer program that can generate text, like a chatbot. These programs are great at answering questions, but sometimes they make mistakes or give false information. To fix this, researchers have developed ways to help the programs correct their own mistakes. The problem is that these methods are hard for smaller programs to follow. In this paper, scientists created a new way called Intrinsic Self-Correction (ISC) that lets small and large programs correct their mistakes on their own. They tested it with different-sized programs and found that ISC helps them give better answers. |
