Exploring ChatGPT for Next-generation Information Retrieval:
Opportunities and Challenges
- URL: http://arxiv.org/abs/2402.11203v1
- Date: Sat, 17 Feb 2024 05:44:40 GMT
- Title: Exploring ChatGPT for Next-generation Information Retrieval:
Opportunities and Challenges
- Authors: Yizheng Huang and Jimmy Huang
- Abstract summary: The emergence of ChatGPT, alongside GPT-4, marks a new phase in Generative AI.
Unlike the traditional supervised learning approach in IR tasks, ChatGPT challenges existing paradigms.
This paper seeks to examine the impact of ChatGPT on IR tasks and offer insights into its potential future developments.
- Score: 1.7223564681760166
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The rapid advancement of artificial intelligence (AI) has highlighted ChatGPT
as a pivotal technology in the field of information retrieval (IR).
Distinguished from its predecessors, ChatGPT offers significant benefits that
have attracted the attention of both the industry and academic communities.
While some view ChatGPT as a groundbreaking innovation, others attribute its
success to the effective integration of product development and market
strategies. The emergence of ChatGPT, alongside GPT-4, marks a new phase in
Generative AI, generating content that is distinct from training examples and
exceeding the capabilities of the prior GPT-3 model by OpenAI. Unlike the
traditional supervised learning approach in IR tasks, ChatGPT challenges
existing paradigms, bringing forth new challenges and opportunities regarding
text quality assurance, model bias, and efficiency. This paper seeks to examine
the impact of ChatGPT on IR tasks and offer insights into its potential future
developments.
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