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HyunDong Cho

7 accepted papers

2026

Block-based Learned Image Compression without Blocking Artifacts

CVPR 2026

Learned image compression (LIC) outperforms traditional codecs but suffers from excessive peak memory usage when handling high-resolution images. Consequently, block-based LIC has been studied to reduce peak memory and peak computational cost, but it often introduces blocking artifacts that degrade

Cited by 0SourceScholar
2024

BotEval: Facilitating Interactive Human Evaluation

ACL 2024system demonstrations

Following the rapid progress in natural language processing (NLP) models, language models are applied to increasingly more complex interactive tasks such as negotiations and conversation moderations. Having human evaluators directly interact with these NLP models is essential for adequately evaluati…

2024

Can Language Model Moderators Improve the Health of Online Discourse?

NAACL 2024long

Conversational moderation of online communities is crucial to maintaining civility for a constructive environment, but it is challenging to scale and harmful to moderators. The inclusion of sophisticated natural language generation modules as a force multiplier to aid human moderators is a tantalizi…

2023

RECAP: Retrieval-Enhanced Context-Aware Prefix Encoder for Personalized Dialogue Response Generation

ACL 2023long

Endowing chatbots with a consistent persona is essential to an engaging conversation, yet it remains an unresolved challenge. In this work, we propose a new retrieval-enhanced approach for personalized response generation. Specifically, we design a hierarchical transformer retriever trained on dialo…

2022

Know Thy Strengths: Comprehensive Dialogue State Tracking Diagnostics

EMNLP 2022finding

Recent works that revealed the vulnerability of dialogue state tracking (DST) models to distributional shifts have made holistic comparisons on robustness and qualitative analyses increasingly important for understanding their relative performance. We present our findings from standardized and compr…

2022

Reflect, Not Reflex: Inference-Based Common Ground Improves Dialogue Response Quality

EMNLP 2022main

Human communication relies on common ground (CG), the mutual knowledge and beliefs shared by participants, to produce coherent and interesting conversations. In this paper, we demonstrate that current response generation (RG) models produce generic and dull responses in dialogues because they act re…

Cited by 30SourcePDFScholar
2021

Probing Commonsense Explanation in Dialogue Response Generation

EMNLP 2021finding

Humans use commonsense reasoning (CSR) implicitly to produce natural and coherent responses in conversations. Aiming to close the gap between current response generation (RG) models and human communication abilities, we want to understand why RG models respond as they do by probing RG model’s unders…

Cited by 19SourcePDFScholar