Papers by D McKnight
Characterizing Human and Zero-Shot GPT-3.5 Object-Similarity Judgments (2024.findings-naacl)
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| Challenge: | Recent advances in large language models have yielded few-shot, human-comparable performance on a range of tasks, but studies of LLM annotation accuracy and behavior are sparse. |
| Approach: | They characterize OpenAI’s GPT-3.5’s judgment on a behavioral task for implicit object categorization and give similarities and differences between them. |
| Outcome: | The proposed model augments human responses with LLMs for domains where data is sparse or compute resources are low. |