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20202026
most citedDecoder-Only or Encoder-Decoder? Interpreting Language Model as a Regularized Encoder-Decoder

16 citations · 31 across the 11 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.CL2023★ 3 cited

Repetition In Repetition Out: Towards Understanding Neural Text Degeneration from the Data Perspective

Huayang Li, Tian Lan, Zihao Fu +5

There are a number of diverging hypotheses about the neural text degeneration problem, i.e., generating repetitive and dull loops, which makes this problem both interesting and con…

cs.CL2023★ 2 cited

BAND: Biomedical Alert News Dataset

Zihao Fu, Meiru Zhang, Zaiqiao Meng +3

Infectious disease outbreaks continue to pose a significant threat to human health and well-being. To improve disease surveillance and understanding of disease spread, several surv…

cs.CL2023

Biomedical Named Entity Recognition via Dictionary-based Synonym Generalization

Zihao Fu, Yixuan Su, Zaiqiao Meng +1

Biomedical named entity recognition is one of the core tasks in biomedical natural language processing (BioNLP). To tackle this task, numerous supervised/distantly supervised appro…

cs.CL2023★ 16 cited

Decoder-Only or Encoder-Decoder? Interpreting Language Model as a Regularized Encoder-Decoder

Zihao Fu, Wai Lam, Qian Yu +4

The sequence-to-sequence (seq2seq) task aims at generating the target sequence based on the given input source sequence. Traditionally, most of the seq2seq task is resolved by the…

cs.CL2023

COFFEE: A Contrastive Oracle-Free Framework for Event Extraction

Meiru Zhang, Yixuan Su, Zaiqiao Meng +2

Event extraction is a complex information extraction task that involves extracting events from unstructured text. Prior classification-based methods require comprehensive entity an…

cs.LG2023★ 2 cited

A Stability Analysis of Fine-Tuning a Pre-Trained Model

Zihao Fu, Anthony Man-Cho So, Nigel Collier

Fine-tuning a pre-trained model (such as BERT, ALBERT, RoBERTa, T5, GPT, etc.) has proven to be one of the most promising paradigms in recent NLP research. However, numerous recent…