Papers by Hancheol Park
Question-Answering in a Low-resourced Language: Benchmark Dataset and Models for Tigrinya (2023.acl-long)
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| Challenge: | Question-Answering (QA) has seen significant advances in recent years, achieving near human-level performance over some benchmarks. |
| Approach: | They propose to use a native QA dataset for an East African language, Tigrinya, to build similar resources for related languages. |
| Outcome: | The proposed method is applicable to constructing similar resources for related languages. |
Deep Model Compression Also Helps Models Capture Ambiguity (2023.acl-long)
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| Challenge: | Experimental results show that our method reduces the model size significantly and improves latency. |
| Approach: | They propose a method to capture the degree of relationship between a sample and its candidate classes by deep model compression. |
| Outcome: | The proposed method reduces model size significantly and improves latency. |
Where do LLMs Encode the Knowledge to Assess the Ambiguity? (2025.coling-industry)
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| Challenge: | False sizing of large language models can generate unreliable responses . |
| Approach: | They propose a method to train large language models without ambiguity labels . |
| Outcome: | The proposed method detects ambiguous input prompts better than representations from the final layer. |