activity
20172022
most citedSelf-Guided Contrastive Learning for BERT Sentence Representations

10 citations · 31 across the 9 of their papers we have counts for

collaborators

13 papers

cs.CL2022

Enhancing Out-of-Distribution Detection in Natural Language Understanding via Implicit Layer Ensemble

Hyunsoo Cho, Choonghyun Park, Jaewook Kang +3

Out-of-distribution (OOD) detection aims to discern outliers from the intended data distribution, which is crucial to maintaining high reliability and a good user experience. Most…

cs.LG20221 cited

AlphaTuning: Quantization-Aware Parameter-Efficient Adaptation of Large-Scale Pre-Trained Language Models

Se Jung Kwon, Jeonghoon Kim, Jeongin Bae +7

There are growing interests in adapting large-scale language models using parameter-efficient fine-tuning methods. However, accelerating the model itself and achieving better infer…

cs.CL20221 cited

Continuous Decomposition of Granularity for Neural Paraphrase Generation

Xiaodong Gu, Zhaowei Zhang, Sang-Woo Lee +2

While Transformers have had significant success in paragraph generation, they treat sentences as linear sequences of tokens and often neglect their hierarchical information. Prior…

cs.CV20227 cited

Mutual Information Divergence: A Unified Metric for Multimodal Generative Models

Jin-Hwa Kim, Yunji Kim, Jiyoung Lee +2

Text-to-image generation and image captioning are recently emerged as a new experimental paradigm to assess machine intelligence. They predict continuous quantity accompanied by th…

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.CL2021

Efficient Attribute Injection for Pretrained Language Models

Reinald Kim Amplayo, Kang Min Yoo, Sang-Woo Lee

Metadata attributes (e.g., user and product IDs from reviews) can be incorporated as additional inputs to neural-based NLP models, by modifying the architecture of the models, in o…