TLDR - Large Language Models (LLMs) offer new capabilities but evaluating their alignment with human preferences is difficult. Chatbot Arena is a new open platform introduced to specifically address this evaluation challenge. For evaluation, this platform uses a pairwise comparison method, gathering human preferences through crowdsourcing. The platform gathered over 240K votes and has been successful.

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Recent Developments in Large Language Models

• Large language models (LLMs) have rapidly advanced, demonstrating capabilities in a wide range of tasks.

• These powerful models raise concerns about how to accurately evaluate their performance, especially when they're used in real-world situations where human preferences are crucial.

Current Limitations in Evaluating LLMs

Most existing LLM benchmarks have several significant limitations:

• They often use closed-ended questions that don't reflect the flexibility needed for real-world interactions.

• Datasets are static, leading to potential contamination and less reliable results.

• Establishing an absolute "ground truth" for complex tasks is impractical or impossible.

The Need for Human-Preference Based Evaluation

To better address the capabilities of modern LLMs, an open evaluation platform is needed that:

• Reflects real-world use with fresh, open-ended questions.

• Prioritizes human preferences to assess how well models align with user needs.

Introducing Chatbot Arena

• Chatbot Arena is a new benchmarking platform for LLMs that addresses these shortcomings.

• Key features:

  • Crowdsourced model evaluation: Users ask questions and anonymously vote for their preferred response from two LLMs.

  • Live and diverse questions: Ensures the platform aligns with real use cases.

  • Statistical ranking models: Used to reliably determine LLM rankings based on the collected votes.

Chatbot Arena's Success and Contributions

• Chatbot Arena has received significant adoption, collecting over 240K votes from around 90K users.

• The diverse data provides insight into LLM use and has validated the platform's value to the industry.

• Key contributions of this work:

  • The creation of the first large-scale, crowdsourced LLM evaluation platform.

  • Release of a dataset with over 100K pairwise LLM comparisons based on human preferences.

  • Development of efficient sampling algorithms to improve the accuracy of LLM rankings.

--> For complete details, refer to the Chatbot Arena paper.