Search Results for author: Hyungjong Noh

Found 5 papers, 2 papers with code

Align-to-Distill: Trainable Attention Alignment for Knowledge Distillation in Neural Machine Translation

1 code implementation3 Mar 2024 Heegon Jin, Seonil Son, Jemin Park, Youngseok Kim, Hyungjong Noh, Yeonsoo Lee

The Attention Alignment Module in A2D performs a dense head-by-head comparison between student and teacher attention heads across layers, turning the combinatorial mapping heuristics into a learning problem.

Knowledge Distillation Machine Translation

HaRiM$^+$: Evaluating Summary Quality with Hallucination Risk

2 code implementations22 Nov 2022 Seonil Son, Junsoo Park, Jeong-in Hwang, Junghwa Lee, Hyungjong Noh, Yeonsoo Lee

One of the challenges of developing a summarization model arises from the difficulty in measuring the factual inconsistency of the generated text.

Automated Writing Evaluation Hallucination +1

SANVis: Visual Analytics for Understanding Self-Attention Networks

no code implementations13 Sep 2019 Cheonbok Park, Inyoup Na, Yongjang Jo, Sungbok Shin, Jaehyo Yoo, Bum Chul Kwon, Jian Zhao, Hyungjong Noh, Yeonsoo Lee, Jaegul Choo

Attention networks, a deep neural network architecture inspired by humans' attention mechanism, have seen significant success in image captioning, machine translation, and many other applications.

Image Captioning Machine Translation +2

Question-Aware Sentence Gating Networks for Question and Answering

no code implementations20 Jul 2018 Minjeong Kim, David Keetae Park, Hyungjong Noh, Yeonsoo Lee, Jaegul Choo

Machine comprehension question answering, which finds an answer to the question given a passage, involves high-level reasoning processes of understanding and tracking the relevant contents across various semantic units such as words, phrases, and sentences in a document.

Question Answering Reading Comprehension +1

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