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researcher

Joonsuk Park

University of Richmond

9 papers hereh-index 161.1k citations29 works total

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

author position
  • middle author9

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.CL8
  • cs.LG1
affiliations
  • University of Richmond
Homepage
same name
  • Joonsuk Park — 5 papers, h 5
  • Joonsuk Park — 4 papers, h 3
  • Joonsuk Park — 3 papers, h 2
  • Joonsuk Park — 2 papers, h 39
  • Joonsuk Park — 2 papers, h 2
  • Joonsuk Park — 1 paper

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
20172023
most citedMemory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization

28 citations · 36 across the 9 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CL2022

Critic-Guided Decoding for Controlled Text Generation

Minbeom Kim, Hwanhee Lee, Kang Min Yoo +3

Steering language generation towards objectives or away from undesired content has been a long-standing goal in utilizing language models (LM). Recent work has demonstrated reinfor…

cs.CL2022

Masked Summarization to Generate Factually Inconsistent Summaries for Improved Factual Consistency Checking

Hwanhee Lee, Kang Min Yoo, Joonsuk Park +2

Despite the recent advances in abstractive summarization systems, it is still difficult to determine whether a generated summary is factual consistent with the source text. To this…

cs.CL2022

ClaimDiff: Comparing and Contrasting Claims on Contentious Issues

Miyoung Ko, Ingyu Seong, Hwaran Lee +3

With the growing importance of detecting misinformation, many studies have focused on verifying factual claims by retrieving evidence. However, canonical fact verification tasks do…

cs.CL2022

Plug-and-Play Adaptation for Continuously-updated QA

Kyungjae Lee, Wookje Han, Seung-won Hwang +3

Language models (LMs) have shown great potential as implicit knowledge bases (KBs). And for their practical use, knowledge in LMs need to be updated periodically. However, existing…

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