Papers by Hyunsouk Cho
Self-Supervised Multimodal Opinion Summarization (2021.acl-long)
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| Challenge: | Existing methods for opinion summarization use text data, but non-text data are less abundant. |
| Approach: | They propose a self-supervised opinion summarization framework that uses non-text data to generate a summary from multiple reviews. |
| Outcome: | The proposed framework is superior to existing methods on Yelp and Amazon datasets. |
Visual Choice of Plausible Alternatives: An Evaluation of Image-based Commonsense Causal Reasoning (L18-1)
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Jinyoung Yeo, Gyeongbok Lee, Gengyu Wang, Seungtaek Choi, Hyunsouk Cho, Reinald Kim Amplayo, Seung-won Hwang
| Challenge: | Existing methods for evaluating plausibility of events are focused on measuring causal dependency between events or actions. |
| Approach: | They propose a task to identify the more plausible alternative with their commonsense causal context. |
| Outcome: | The proposed task is based on a visual COPA dataset with 380 questions and over 1K images with various topics. |
SQuAD2-CR: Semi-supervised Annotation for Cause and Rationales for Unanswerability in SQuAD 2.0 (2020.lrec-1)
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| Challenge: | Existing models are brittle for adversarial perturbed questions, causing uncertainty . a dataset with annotations on unanswerable questions is not available to solve this problem . |
| Approach: | They use crowdsourced annotations to annotate unanswerable questions . they also annotated which part of the question causes unanswered questions a . |
| Outcome: | The proposed dataset can be used to improve model interpretation, authors say . they find that existing models are brittle for adversarial perturbed questions . |
FLEX: Expert-level False-Less EXecution Metric for Text-to-SQL Benchmark (2025.naacl-long)
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| Challenge: | Existing evaluation methods for text-to-SQL systems show many false positives and negatives . however, the Execution Accuracy (EX) metric is flawed and can diverge from human experts. |
| Approach: | They propose a method to evaluate text-to-SQL systems using large language models to emulate human expert-level evaluation of SQL queries. |
| Outcome: | The proposed metric improves agreement with human experts with comprehensive context and sophisticated criteria. |
GTA: Gated Toxicity Avoidance for LM Performance Preservation (2023.findings-emnlp)
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| Challenge: | Existing Controllable Text Generation methods that generate toxic text can negatively impact the performance of the language model. |
| Approach: | They propose a gated Toxicity Avoidance method that can be applied to any CTG method and evaluate its effectiveness. |
| Outcome: | The proposed method reduces toxicity and preserves performance while preserving the language model's generation performance. |