Vishakha Kadam
About Vishakha Kadam
Vishakha Kadam: Research Scientist
Vishakha Kadam is recognized as a Research Scientist. Her work has contributed significantly to the fields of natural language processing and contextual advertising. Her expertise is showcased through several high-profile research papers she has authored or co-authored, presented at major international conferences and workshops.
Presentations at the International Natural Language Generation Conference
Vishakha Kadam presented two notable research papers at the 15th International Natural Language Generation (NLG) Conference. Her papers include 'Plot Writing From Pre-Trained Language Models' and 'Automated Ad Creative Generation'. These presentations highlight her innovative work in leveraging pre-trained language models for creative and advertising purposes.
Paper on Hate Speech Classification at WOAH Workshop
Vishakha Kadam co-authored a significant research paper titled 'Towards Weakly-Supervised Hate Speech Classification Across Datasets'. This paper was accepted at the 7th Workshop on Online Abuse and Harms (WOAH), emphasizing her contributions towards addressing challenges in moderating online content and improving the accuracy of hate speech classification across various datasets.
Publication on Contextual Advertising in TextGraphs-15
In the proceedings of the Fifteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-15), Vishakha Kadam co-authored a research paper titled 'Bootstrapping Large-Scale Fine-Grained Contextual Advertising Classifier from Wikipedia'. This publication demonstrates her work in developing classifiers for fine-grained contextual advertising, harnessing the extensive information available in Wikipedia.
Research on Slogan Generation in Natural Language Engineering
Vishakha Kadam contributed to the research paper 'Towards Improving Coherence and Diversity of Slogan Generation', published in Natural Language Engineering (NLE). This paper explores methods to enhance the coherence and diversity of generated slogans, reflecting her ongoing efforts to advance natural language generation technologies.