Summary of Reasoning with Natural Language Explanations, by Marco Valentino et al.
Reasoning with Natural Language Explanations
by Marco Valentino, André Freitas
First submitted to arxiv on: 5 Oct 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 This paper introduces a new direction in Natural Language Inference (NLI) research, focusing on explanation-based NLI models that encode and use natural language explanations for downstream tasks. The field is crucial for human rationality, learning, and generalization. The tutorial provides an overview of the epistemological-linguistic foundations of explanations, architectural trends, and evaluation methodologies for building systems capable of explanatory reasoning. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Explanation-based NLI models can learn from natural language explanations to improve their ability to reason about complex concepts. This paper presents a comprehensive introduction to the field, discussing its importance in human reasoning and learning. |
Keywords
» Artificial intelligence » Generalization » Inference
