Papers by Sania Waheed
Capturing the Relationship Between Sentence Triplets for LLM and Human-Generated Texts to Enhance Sentence Embeddings (2024.findings-eacl)
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| Challenge: | Recent advances in building sentence embedding models have centered on replacing traditional human-generated text datasets with those generated by LLMs. |
| Approach: | They propose a loss function that incorporates Positive-Negative sample Augmentation within the contrastive learning objective to enhance sentence embeddings using both human and LLM-generated datasets. |
| Outcome: | The proposed model mitigates the sentence anisotropy problem in Wikipedia corpus and improves Spearman’s correlation in standard Semantic Textual Similarity (STS) tasks (+1.47% compared to CLHAIF). |
Image Embedding Sampling Method for Diverse Captioning (2025.emnlp-main)
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| Challenge: | Currently, large-scale captioning models are less accessible for resource-constrained applications such as mobile devices and assistive technologies. |
| Approach: | They propose a training-free framework that enhances caption diversity and informativeness by explicitly attending to distinct image regions using a comparably small VLM as the backbone. |
| Outcome: | The proposed framework achieves comparable performance to larger models on MSCOCO, Flickr30k, and Nocaps test datasets while maintaining strong image-caption relevancy and semantic integrity with the human-annotated captions. |