Summary of Open-llm-leaderboard: From Multi-choice to Open-style Questions For Llms Evaluation, Benchmark, and Arena, by Aidar Myrzakhan and Sondos Mahmoud Bsharat and Zhiqiang Shen
Open-LLM-Leaderboard: From Multi-choice to Open-style Questions for LLMs Evaluation, Benchmark, and Arena
by Aidar Myrzakhan, Sondos Mahmoud Bsharat, Zhiqiang Shen
First submitted to arxiv on: 11 Jun 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 A novel approach to evaluating large language models (LLMs) is proposed, tackling the limitations of traditional multiple-choice questions (MCQs). MCQs are prone to selection bias, where LLMs favor certain answer choices due to inherent biases. Additionally, random guessing can lead to incorrect conclusions about an LLM’s capabilities. To address these issues, the authors suggest shifting from MCQs to open-style questions, which eliminate selection bias and random guessing. However, this transition poses challenges in identifying suitable open-style questions and validating LLM responses against human-annotated ground-truths. The paper introduces the Open-LLM-Leaderboard benchmark, tracking various LLMs’ performance, including GPT-4o/4/3.5, Claude 3, Gemini, etc. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models (LLMs) are used to test knowledge and understanding. But there’s a problem! The way we ask questions can be unfair. Sometimes, the answer choices might be biased, making it harder for the LLM to make good predictions. This is called “selection bias”. Another issue is that the LLM might just guess randomly and get it right sometimes. This doesn’t really show what the LLM knows or can do. To fix this, we need to change how we ask questions. Instead of multiple-choice, we should use open-style questions that let the LLM share its thoughts freely. But then, we have new challenges like finding good questions and checking if the LLM’s answers are correct. |
Keywords
» Artificial intelligence » Claude » Gemini » Gpt » Tracking
