Papers by Daniela Massiceti
Investigating Dictionary Expansion for Video-based Sign Language Dictionaries (2025.findings-emnlp)
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| Challenge: | Currently, most dictionary retrieval methods only work with fixed vocabularies, and it is unclear how they might support dictionary expansion without retraining. |
| Approach: | They propose to use a representation-based method to explore the feasibility of dictionary expansion for sign language dictionaries. |
| Outcome: | The proposed method improves sign language dictionaries by varying number of signs added and amount of data for newly added signs. |
Distilling Knowledge from Text-to-Image Generative Models Improves Visio-Linguistic Reasoning in CLIP (2024.emnlp-main)
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| Challenge: | Image-text contrastive models like CLIP struggle on compositional visio-linguistic tasks where their performance is no better than random chance. |
| Approach: | They propose a distillation method to enhance CLIP's compositional visio-linguistic reasoning by using a model-derived distillation objective borrowed from large text-to-image generative models like Stable-Diffusion. |
| Outcome: | The proposed method improves CLIP models' visio-linguistic performance on the Winoground benchmark by 7% while on the ARO dataset, it boosts performance by 3%. |