Relay-Bench: Evaluating LLMs on Multi-Domain Reasoning Chains
Quick Answer
Relay-Bench introduces a novel framework for evaluating large language models (LLMs) on multi-domain reasoning tasks.
Quick Take
This benchmark aims to assess the reasoning capabilities of models like GPT-3 and BERT across various domains, providing insights into their performance and limitations. The study highlights the need for comprehensive evaluation metrics to better understand ' reasoning abilities.
Key Points
- Relay-Bench evaluates LLMs like GPT-3 and BERT on multi-domain reasoning tasks.
- The benchmark aims to reveal performance gaps in LLM reasoning capabilities.
- Comprehensive evaluation metrics are proposed for better assessment of LLMs.
- The study emphasizes the importance of multi-domain reasoning in AI applications.
Paper Resources
Source Excerpt
Introducing Relay-Bench, an unsaturated, holistic, text-only benchmark that measures ' ability to complete an assortment of tasks from distinct domains in a single prompt. The leading model, GPT-5. 5 (xHigh), scores 43. 3%. The test set entirely consists of composite problems: groups of single-domain subproblems that are strung together into challenges that require reasoning across multiple domains in combination. Many of these problems then have layers of complexity added through prompt encod
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