Papers by Fitsum Gaim
GeezSwitch: Language Identification in Typologically Related Low-resourced East African Languages (2022.lrec-1)
Copied to clipboard
| Challenge: | Low-resourced languages with similar typologies are often confused with each other in real-world applications such as machine translation, affecting the user’s experience. |
| Approach: | They propose to build a dataset for five typologically and phylogenetically related low-resourced East African languages using the Ge’ez script as a writing system. |
| Outcome: | The proposed dataset is built automatically from selected data sources, but also performed a manual evaluation to assess its quality. |
Question-Answering in a Low-resourced Language: Benchmark Dataset and Models for Tigrinya (2023.acl-long)
Copied to clipboard
| Challenge: | Question-Answering (QA) has seen significant advances in recent years, achieving near human-level performance over some benchmarks. |
| Approach: | They propose to use a native QA dataset for an East African language, Tigrinya, to build similar resources for related languages. |
| Outcome: | The proposed method is applicable to constructing similar resources for related languages. |
Semantic Hardness Is Not Visual Hardness: Sign-Aware Hard Negative Mining for Sign Language Retrieval (2026.acl-long)
Copied to clipboard
Junmyeong Lee, Chan Hur, ChangSu Choi, Sukmin Cho, Fitsum Gaim, Eui Jun Hwang, Hoyun Song, KyungTae Lim
| 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. |