Summary of Procbench: Benchmark For Multi-step Reasoning and Following Procedure, by Ippei Fujisawa et al.
ProcBench: Benchmark for Multi-Step Reasoning and Following Procedure
by Ippei Fujisawa, Sensho Nobe, Hiroki Seto, Rina Onda, Yoshiaki Uchida, Hiroki Ikoma, Pei-Chun Chien, Ryota Kanai
First submitted to arxiv on: 4 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Machine Learning (cs.LG)
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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 The proposed benchmark focuses on evaluating the multi-step inference abilities of large language models (LLMs), by designing a special reasoning task that eliminates path exploration and implicit knowledge utilization. The dataset consists of pairs of explicit instructions and corresponding questions, where the procedures necessary for solving the questions are entirely detailed within the instructions. This setup allows LLMs to solve problems solely by following the provided directives. The benchmark includes multiple distinct tasks, with varying numbers of steps to solve, and utilizes step-aware metrics to evaluate responses at each step. The findings have significant implications for the development of LLMs and highlight areas for future research in advancing their reasoning abilities. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper proposes a new way to test how well large language models can reason. Reasoning is an important skill that we use every day, like solving puzzles or understanding stories. The best language models are really good at understanding what we say, but they’re not as good at figuring out the answers to complex questions on their own. To fix this, the researchers created a special test that asks the models to follow instructions step by step. They want to know how well the models can do this, and which ones are best at it. |
Keywords
* Artificial intelligence * Inference
