Papers with concept classification
Licon: A Diverse, Controllable and Challenging Linguistic Concept Learning Benchmark (2023.findings-emnlp)
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| Challenge: | Existing methods for Concept Learning focus on visual information, but visual information cannot present abstract concepts exactly, which struggles the introduction of novel concepts related to known concepts. |
| Approach: | They propose a benchmark where concepts in diverse forms are defined by linguistic descriptions and an entailment-based concept learning method to model the relationship among concepts. |
| Outcome: | The proposed benchmark is based on the existing visual concepts learning benchmarks and will be released to the public soon. |
Are Structural Concepts Universal in Transformer Language Models? Towards Interpretable Cross-Lingual Generalization (2023.findings-emnlp)
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| Challenge: | Large language models (LLMs) have implicitly transfer knowledge across languages, but not all languages have such generalization capabilities. |
| Approach: | They propose a meta-learning-based method to learn to align conceptual spaces of different languages to enhance cross-lingual generalization. |
| Outcome: | The proposed method achieves competitive results with state-of-the-art methods and narrows the performance gap between languages. |