[Nov 23, 2023]
1 paper at OPODIS 2023 selected as the *best student paper*
Authors: Junghyun Lee, Laura Schmid, Se-Young Yun
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Optimization and Statistical Inference Lab
Welcome to the Optimization and Statistical Inference Lab at KAIST AI. We tackle a wide range of problems, from theoretical analysis of traditional machine learning, to the latest research topics in deep learning. Please refer to publications for details.
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[Oct 09, 2023]
4 papers accepted to EMNLP 2023
- Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding
- HARE: Explainable Hate Speech Detection with Step-by-Step Reasoning (Findings)
- NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models (Findings)
- Bayesian Transfer Learning for Soft Prompt Tuning (Findings)