Summary of “sorry, Come Again?” Prompting — Enhancing Comprehension and Diminishing Hallucination with [pause]-injected Optimal Paraphrasing, by Vipula Rawte et al.
“Sorry, Come Again?” Prompting – Enhancing Comprehension and Diminishing Hallucination with [PAUSE]-injected Optimal Paraphrasing
by Vipula Rawte, S.M Towhidul Islam Tonmoy, S M Mehedi Zaman, Prachi Priya, Aman Chadha, Amit P. Sheth, Amitava Das
First submitted to arxiv on: 27 Mar 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 The proposed Sorry, Come Again (SCA) prompting technique aims to reduce Large Language Model (LLM) hallucinations by enhancing comprehension through optimal paraphrasing and injecting [PAUSE] tokens. The paper analyzes linguistic nuances, including formality, readability, and concreteness of prompts for 21 LLMs, revealing how these factors contribute to comprehension challenges. To address this, the authors propose an optimal paraphrasing technique using Integrated Gradient and its variations to ensure accurate processing of all words. Additionally, they introduce [PAUSE] token injection, fine-tuning the LLM to pause while reading lengthier prompts. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large Language Models (LLMs) have a problem with “hallucinations” – making things up that aren’t true. To fix this, researchers came up with a new way of asking questions called Sorry, Come Again (SCA). This technique makes the LLM think harder and gets it to be more accurate by using special tokens like [PAUSE]. The idea is that the LLM will pause and take its time when reading longer sentences or prompts. This can help it avoid making mistakes and provide better answers. |
Keywords
» Artificial intelligence » Fine tuning » Large language model » Prompting » Token
