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Yuanyuan Wu

5 papers hereh-index 444 citations11 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author5

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.IR1
same name
  • Yuanyuan Wu — 2 papers, h 3
  • Yuanyuan Wu — 2 papers, h 6
  • Yuanyuan Wu — 2 papers, h 1
  • Yuanyuan Wu — 2 papers, h 2
  • Yuanyuan Wu — 2 papers, h 2
  • Yuanyuan Wu — 2 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20222024
most citedDifferentiable N-gram Objective on Abstractive Summarization

2 citations · 2 across the 5 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2024

Hierarchical Skip Decoding for Efficient Autoregressive Text Generation

Yunqi Zhu, Xuebing Yang, Yuanyuan Wu +1

Autoregressive decoding strategy is a commonly used method for text generation tasks with pre-trained language models, while early-exiting is an effective approach to speedup the i…

cs.CL2023

Parameter-Efficient Fine-Tuning with Layer Pruning on Free-Text Sequence-to-Sequence Modeling

Yunqi Zhu, Xuebing Yang, Yuanyuan Wu +1

The increasing size of language models raises great research interests in parameter-efficient fine-tuning such as LoRA that freezes the pre-trained model, and injects small-scale t…

cs.CL2023

Leveraging Summary Guidance on Medical Report Summarization

Yunqi Zhu, Xuebing Yang, Yuanyuan Wu +1

This study presents three deidentified large medical text datasets, named DISCHARGE, ECHO and RADIOLOGY, which contain 50K, 16K and 378K pairs of report and summary that are derive…

cs.CL2022★ 2 cited

Differentiable N-gram Objective on Abstractive Summarization

Yunqi Zhu, Xuebing Yang, Yuanyuan Wu +2

ROUGE is a standard automatic evaluation metric based on n-grams for sequence-to-sequence tasks, while cross-entropy loss is an essential objective of neural network language model…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.