Papers by Junmyeong Lee

2 papers
An Efficient Gloss-Free Sign Language Translation Using Spatial Configurations and Motion Dynamics with LLMs (2025.naacl-long)

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Challenge: Existing methods for sign language translation rely on glosses, which are written representations of signs.
Approach: They propose a new LLM-based SLT framework that uses off-the-shelf visual encoders to extract spatial and motion features from sign videos.
Outcome: The proposed framework captures spatial configurations and motion dynamics in sign language without domain-specific tuning.
Semantic Hardness Is Not Visual Hardness: Sign-Aware Hard Negative Mining for Sign Language Retrieval (2026.acl-long)

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Challenge: Existing methods for sign language retrieval fail to capture visual ambiguity . semantically distinct yet visually confusable signs are rarely treated as hard negatives .
Approach: They propose a method that constructs hard negatives based on visual confusability rather than linguistic similarity.
Outcome: The proposed method significantly improves fine-grained retrieval performance while preserving coarse-grain accuracy.

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