Optimizing Prompt Length and Specificity for Enhanced AI Chatbot Responses

Abstract : Language models have revolutionized natural language processing by greatly improving text generation and comprehension. Optimizing their functioning is related to how one designs prompts because the kind and quality of response produced affects the nature of response that is generated. This article explores the impact of prompt length and specificity on AI chatbots’ capabilities concerning accuracy, fluency, and relevance of generated responses. We present evidence that careful prompt engineering is severely lacking to improve conversational performance, and illustrate this using studies and experiments on the Cornell Movie Dialogs Corpus; thus, providing interesting guidelines to the developers and researchers interested in improving chatbot responses

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-30
DOI
https://doi.org/10.5281/zenodo.13860919
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimizing Prompt Length and Specificity for Enhanced AI Chatbot Responses

Zenodo (CERN European Organization for Nuclear Research)
AI in Service Interactions
article

Optimizing Prompt Length and Specificity for Enhanced AI Chatbot Responses

article en

Abstract

Abstract : Language models have revolutionized natural language processing by greatly improving text generation and comprehension. Optimizing their functioning is related to how one designs prompts because the kind and quality of response produced affects the nature of response that is generated. This article explores the impact of prompt length and specificity on AI chatbots’ capabilities concerning accuracy, fluency, and relevance of generated responses. We present evidence that careful prompt engineering is severely lacking to improve conversational performance, and illustrate this using studies and experiments on the Cornell Movie Dialogs Corpus; thus, providing interesting guidelines to the developers and researchers interested in improving chatbot responses

Zenodo (CERN European Organization for Nuclear Research)
Bangalore University (IN)
Quality Education
Openalex Percentile: Top 68%
AI in Service Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.