Papers by Abisek Rajakumar Kalarani

3 papers
A Match Made in Heaven: A Multi-task Framework for Hyperbole and Metaphor Detection (2023.findings-acl)

Copied to clipboard

Challenge: Existing approaches to detect metaphor and hyperbole independently have not explored their relationship computationally.
Approach: They propose a multi-task deep learning framework to detect hyperbole and metaphor simultaneously by annotating two hyperbolic datasets with metaphor labels.
Outcome: The proposed framework improves state-of-the-art hyperbole detection by 12% over existing methods.
“Let’s not Quote out of Context”: Unified Vision-Language Pretraining for Context Assisted Image Captioning (2023.acl-industry)

Copied to clipboard

Challenge: Large enterprises have several teams to create their content for the purpose of marketing, campaigning, or even maintaining a brand presence.
Approach: They propose a new unified Vision-Language (VL) model with a focus on context-assisted image captioning where the caption is generated based on both the image and its context.
Outcome: The proposed model achieves state-of-the-art with an improvement of up to 8.34 CIDEr score on the benchmark news image captioning datasets.
Unveiling the Invisible: Captioning Videos with Metaphors (2024.findings-emnlp)

Copied to clipboard

Challenge: Recent studies have shown that Vision-Language models cannot understand visual metaphors in memes and adverts.
Approach: They propose a task to describe visual metaphors in videos using a manually created dataset and a new metric called Average Concept Distance to automatically evaluate creativity.
Outcome: The proposed system performs comparable to existing video language models on the proposed task and can be used for future research.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations