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Found 10 papers, 4 papers with code
Knowing Your Nonlinearities: Shapley Interactions Reveal the Underlying Structure of Data
Measuring nonlinear feature interaction is an established approach to understanding complex patterns of attribution in many models.
ConspEmoLLM: Conspiracy Theory Detection Using an Emotion-Based Large Language Model
Driven by a comprehensive analysis of conspiracy text that reveals its distinctive affective features, we propose ConspEmoLLM, the first open-source LLM that integrates affective information and is able to perform diverse tasks relating to conspiracy theories.
Meme-ingful Analysis: Enhanced Understanding of Cyberbullying in Memes Through Multimodal Explanations
A Contrastive Language-Image Pretraining (CLIP) projection-based multimodal shared-private multitask approach has been proposed for visual and textual explanation of a meme.
Explain Thyself Bully: Sentiment Aided Cyberbullying Detection with Explanation
While plenty of research is going on to develop better models for cyberbullying detection in monolingual language, there is very little research on the code-mixed languages and explainability aspect of cyberbullying.
MedSumm: A Multimodal Approach to Summarizing Code-Mixed Hindi-English Clinical Queries
This work introduces the task of multimodal medical question summarization for codemixed input in a low-resource setting.
CLIPSyntel: CLIP and LLM Synergy for Multimodal Question Summarization in Healthcare
This multimodal approach not only enhances the decision-making process in healthcare but also fosters a more nuanced understanding of patient queries, laying the groundwork for future research in personalized and responsive medical care
Large Language Models as Tax Attorneys: A Case Study in Legal Capabilities Emergence
Better understanding of Large Language Models' (LLMs) legal analysis abilities can contribute to improving the efficiency of legal services, governing artificial intelligence, and leveraging LLMs to identify inconsistencies in law.
A Survey on Medical Document Summarization
The internet has had a dramatic effect on the healthcare industry, allowing documents to be saved, shared, and managed digitally.
WIDAR -- Weighted Input Document Augmented ROUGE
The task of automatic text summarization has gained a lot of traction due to the recent advancements in machine learning techniques.
Semantic Extractor-Paraphraser based Abstractive Summarization
The anthology of spoken languages today is inundated with textual information, necessitating the development of automatic summarization models.
