Papers by Jihee Kim

2 papers
TIDES: Technical Information Discovery and Extraction System (2025.emnlp-main)

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Challenge: Traditional pre-trained LLMs struggle with domain-specific terminology, while fine-tuned LLM requires substantial computational resources.
Approach: They propose a training-free approach that combines TF-IDF with prompt-based LLMs to address technical questions.
Outcome: The proposed system improves the accuracy and efficiency of QA systems in technical domains without LLM retraining.
CED: Comparing Embedding Differences for Detecting Out-of-Distribution and Hallucinated Text (2024.findings-emnlp)

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Challenge: Existing methods for detecting out-of-distribution (OOD) samples are limited due to their domain shift and computational limitations.
Approach: They propose a training-free method to detect out-of-distribution (OOD) samples . they theoretically validate that specific auxiliary and oracle samples improve this distinction .
Outcome: The proposed method improves the ability of pre-trained models to distinguish between ID and OOD samples in text classification and hallucination detection tasks.

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