Papers by Giovanni Semeraro
Mind Your Special Tokens! On the Importance of Dedicated Sequence-End Tokens in Vision-Language Embedding Models (2026.eacl-short)
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| Challenge: | Large Vision-Language Models (LVLMs) are highly sensitive to end-of-input artifacts in fine-tuning and inference data, e.g., whether input sequences end with punctuation or newline characters. |
| Approach: | They propose to convert generative LVLMs into vision-language encoders via contrastive learning objectives and use supervised contrastive objectives to train them. |
| Outcome: | The proposed approach improves visual and text representations and improves retrieval and (semantic) similarity tasks. |
XL-LEXEME: WiC Pretrained Model for Cross-Lingual LEXical sEMantic changE (2023.acl-short)
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| Challenge: | Existing approaches to the Word in Context task use cross-encoders, which prevent the possibility of deriving comparable word embeddings. |
| Approach: | They propose a Lexical Semantic Change Detection model that extends SBERT, highlighting the target word in the sentence. |
| Outcome: | The proposed model outperforms the state-of-the-art on the multilingual benchmarks for SemEval-2020 Task 1 - Lexical Semantic Change (LSC) Detection and the RuShiftEval shared task. |