Papers by Arianna Pera
The Parrot Dilemma: Human-Labeled vs. LLM-augmented Data in Classification Tasks (2024.eacl-short)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) are not perfect generalists as they often underperform traditional fine-tuning methods. |
| Approach: | They compare human-labeled and synthetically generated data in CSS classification tasks . they leverage large language models such as OpenAI's GPT-4 for zero-shot classification . |
| Outcome: | The proposed models perform better on human-labeled data than synthetically augmented models on rare classes within multi-class tasks. |