Papers by Sungjae Hwang
Efficient Latent Semantic Clustering for Scaling Test-Time Computation of LLMs (2025.findings-emnlp)
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| Challenge: | Existing methods for scaling test-time computation rely on external models that introduce substantial computational overhead and fail to capture context-aware semantics. |
| Approach: | They propose a method that leverages the generator LLM’s internal hidden states for clustering, eliminating the need for external models. |
| Outcome: | The proposed method improves the computational efficiency of test-time scaling while maintaining or exceeding the performance of existing methods. |
All You Need is Attention: Lightweight Attention-based Data Augmentation for Text Classification (2024.findings-emnlp)
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| Challenge: | Existing methods to augment text classification tasks require extensive dataset training. |
| Approach: | They propose a method that uses attention mechanisms to exchange semantically similar words between sentences to generate a greater diversity of synthetic sentences compared to simpler operations like random insertions. |
| Outcome: | The proposed method consistently outperforms baseline methods across diverse text classification conditions. |