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20202023
most citedA Contrastive Framework for Neural Text Generation

83 citations · 264 across the 31 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.CV2023★ 2 cited

Sparkles: Unlocking Chats Across Multiple Images for Multimodal Instruction-Following Models

Yupan Huang, Zaiqiao Meng, Fangyu Liu +3

Large language models exhibit enhanced zero-shot performance on various tasks when fine-tuned with instruction-following data. Multimodal instruction-following models extend these…

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★ 6 cited

PiVe: Prompting with Iterative Verification Improving Graph-based Generative Capability of LLMs

Jiuzhou Han, Nigel Collier, Wray Buntine +1

Large language models (LLMs) have shown great abilities of solving various natural language tasks in different domains. Due to the training objective of LLMs and their pre-training…

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…