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Yinghan Long

2 accepted papers

2024

Prompt-Based Bias Calibration for Better Zero/Few-Shot Learning of Language Models

EMNLP 2024finding

Prompt-based learning is susceptible to intrinsic bias present in pre-trained language models (LMs), leading to sub-optimal performance in prompt-based zero/few-shot settings. In this work, we propose a null-input prompting method to calibrate intrinsic bias encoded in pre-trained LMs. Different fro…

Cited by 1SourcePDFScholar
2023

Segmented Recurrent Transformer: An Efficient Sequence-to-Sequence Model

EMNLP 2023long findings

Transformers have shown dominant performance across a range of domains including language and vision. However, their computational cost grows quadratically with the sequence length, making their usage prohibitive for resource-constrained applications. To counter this, our approach is to divide the w…

Cited by 0SourceScholar