Papers with encoder-only based networks

1 papers
LLM-Guided Co-Training for Text Classification (2025.emnlp-main)

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Challenge: Empirical results show that it achieves state-of-the-art performance on 4 out of 5 benchmark datasets and ranks first among 14 compared methods according to the Friedman test.
Approach: They propose a weighted co-training approach that is guided by Large Language Models (LLMs) they use LLM labels on unlabeled data as target labels and co-train two encoder-only based networks that train each other over multiple iterations.
Outcome: The proposed approach outperforms conventional methods on 4 out of 5 benchmark datasets and ranks first among 14 compared methods according to the Friedman test.

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