title: How is ChatGPT's behavior changing over time?
summary: GPT-3.5 and GPT-4 are the two most widely used large language model (LLM)
  services. However, when and how these models are updated over time is opaque.
  Here, we evaluate the March 2023 and June 2023 versions of GPT-3.5 and GPT-4 on
  four diverse tasks: 1) solving math problems, 2) answering sensitive/dangerous
  questions, 3) generating code and 4) visual reasoning. We find that the
  performance and behavior of both GPT-3.5 and GPT-4 can vary greatly over time.
  For example, GPT-4 (March 2023) was very good at identifying prime numbers
  (accuracy 97.6%) but GPT-4 (June 2023) was very poor on these same questions
  (accuracy 2.4%). Interestingly GPT-3.5 (June 2023) was much better than GPT-3.5
  (March 2023) in this task. GPT-4 was less willing to answer sensitive questions
  in June than in March, and both GPT-4 and GPT-3.5 had more formatting mistakes
  in code generation in June than in March. Overall, our findings shows that the
  behavior of the same LLM service can change substantially in a relatively short
  amount of time, highlighting the need for continuous monitoring of LLM quality.
paper_authors._id: 64b740b81d913123e6d5aef9
paper_authors.name: Lingjiao Chen
paper_authors._id: 64b740b81d913123e6d5aefa
paper_authors.name: Matei Zaharia
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-07-19T12:15:32.291Z
paper_authors._id: 642509c6d476e4ad5568dd31
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/642509c6d476e4ad5568dd31/dPiEV70hMeuY-cveLNPQg.jpeg
paper_authors.fullname: Matei Zaharia
paper_authors.type: user
paper_authors.user: mateiz
paper_authors._id: 64b740b81d913123e6d5aefb
paper_authors.name: James Zou
paper_title: How is ChatGPT's behavior changing over time?
paper_summary: GPT-3.5 and GPT-4 are the two most widely used large language model (LLM)
  services. However, when and how these models are updated over time is opaque.
  Here, we evaluate the March 2023 and June 2023 versions of GPT-3.5 and GPT-4 on
  four diverse tasks: 1) solving math problems, 2) answering sensitive/dangerous
  questions, 3) generating code and 4) visual reasoning. We find that the
  performance and behavior of both GPT-3.5 and GPT-4 can vary greatly over time.
  For example, GPT-4 (March 2023) was very good at identifying prime numbers
  (accuracy 97.6%) but GPT-4 (June 2023) was very poor on these same questions
  (accuracy 2.4%). Interestingly GPT-3.5 (June 2023) was much better than GPT-3.5
  (March 2023) in this task. GPT-4 was less willing to answer sensitive questions
  in June than in March, and both GPT-4 and GPT-3.5 had more formatting mistakes
  in code generation in June than in March. Overall, our findings shows that the
  behavior of the same LLM service can change substantially in a relatively short
  amount of time, highlighting the need for continuous monitoring of LLM quality.
paper_ai_keywords: large language model (LLM) GPT-3.5 GPT-4 synthesis solving math problems answering sensitive/dangerous questions generating code visual reasoning accuracy identifying prime numbers formatting mistakes continuous monitoring LLM quality