Talk Sriparna Saha

Abstract: 

Large language models (LLMs) have become very popular nowadays and are widely used for solving various natural language processing problems. Researchers are working towards benchmarking these LLMs on various tasks like temporal reasoning and educational domains to understand their biases towards different genders, religions, and castes. In this talk, I will discuss some recent biasness studies of the LLMs and our efforts of utilizing LLM and vision language models (VLMs) in solving the tasks of medical question summarization, developing some plant-care dialogue assistant, generating interventions to help stop spreading hate speech.

Bio:

Dr. Sriparna Saha is an associate professor at the Department of Computer Science and Engineering, Indian Institute of Technology Patna, India. She has authored or co-authored more than 400 papers. Her research interests include machine learning, deep learning, natural language processing, multiobjective optimization, and biomedical information extraction. Her h5-index is 40, and the total citation count of her papers is 8897 (according to Google Scholar). She is also a senior member of IEEE, ACM, and a fellow of IET, UK.  Her research publications have been published in reputed forums like IEEE/ACM Transactions, ACL, AAAI, ACM Multimedia, NAACL, EACL, ECML, COLING, SIGIR, ECIR, ECAI, and others. She won the best paper awards in ICONIP 2023, CLINICAL-NLP workshop of COLING 2016,  and Area-chair-award (Information Extraction) at IJCNLP-AACL 2023. She is currently also serving as the Associate Editor of IEEE Transactions on Artificial Intelligence, IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Transactions on Computational Social Systems, ACM Transactions on Asian and Low-Resource Language Information Processing, Expert Systems with Applications, Pattern Recognition Letters, Pattern Recognition, PLOS ONE, Machine Learning with Applications.  

 

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