Papers with two-stage contrastive learning framework

2 papers
Improving Word Translation via Two-Stage Contrastive Learning (2022.acl-long)

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Challenge: Existing approaches to bilingual lexicon induction (BLI) are limited to two stages, but we propose a robust and effective two-stage contrastive learning framework for the task.
Approach: They propose a two-stage contrastive learning framework for the task . they propose to refine cross-lingual linear maps between static word embeddings via a contrastive objective and integrate it into the self-learning procedure for even more refined cross-linguistic maps.
Outcome: The proposed framework improves cross-lingual maps and word translation capability by integrating it into the self-learning procedure.
ImpliHateVid: A Benchmark Dataset and Two-stage Contrastive Learning Framework for Implicit Hate Speech Detection in Videos (2025.acl-long)

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Challenge: Existing studies on text-based hate speech detection focus on video-based approaches . however, hateful content remains a persistent challenge due to the vast amount of data generated every day.
Approach: They propose a novel two-stage contrastive learning framework for hate speech detection in videos . they train modality-specific encoders for audio, text, and image using contrastive loss .
Outcome: The proposed framework is based on two datasets, ImpliHateVid and HateMM datasets.

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