Papers by Che Hyun Lee

3 papers
EdiText: Controllable Coarse-to-Fine Text Editing with Diffusion Language Models (2025.acl-long)

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Challenge: Existing methods for text editing have been proposed for various types of data with diverse attributes.
Approach: They propose a novel text editing method that modifies reference text to desired attributes at various scales.
Outcome: The proposed method is capable of making precise adjustments within the desired range while maintaining the accuracy of the reference text.
Does Your Voice Assistant Remember? Analyzing Conversational Context Recall and Utilization in Voice Interaction Models (2025.findings-acl)

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Challenge: Recent advances in multi-turn voice interaction models have improved user-model communication, but whether open-source models share this ability remains unexplored.
Approach: They propose to use ContextDialog to evaluate open-source interaction models' ability to recall past utterances to identify key limitations.
Outcome: The proposed model retains and recalls past utterances better than closed-source models, but still struggles with questions about past . findings highlight key limitations in open-source model and suggest ways to improve memory retention and retrieval robustness.
Still Between Us? Evaluating and Improving Voice Assistant Robustness to Third-Party Interruptions (2026.acl-long)

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Challenge: Recent Spoken Language Models lack the capability to discern Third-Party Interruptions (TPI) from the primary user’s ongoing flow, leaving them vulnerable to contextual failures.
Approach: They propose a dataset with speaker-aware hard negatives to enforce acoustic cue prioritization for interruption handling and a framework to measure the interruption-handling strategy and precise speaker discrimination in deceptive contexts.
Outcome: The proposed framework mitigates semantic shortcut learning while neglecting acoustic signals essential for discerning speaker changes.

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