Projects
Selected Research Projects
- Large Language Models for Controllable Text Generation via Reinforcement Learning
- Advior: Prof. Mustaque Ahamad, and Prof. Srijan Kumar
- Research output: ACM WWW’23 code and data
- Design novel BERT-based reward models in offline RL framework to capture desirable textual properties in text generation
- Implemented a transformer decoder-based GPT-kind language model for counter-misinformation generation
- Curate high-quality misinformation-related conversational datasets and fine-tuned LLaMA2 using LoRA
- Multi-task Learning-based Personalized Text Generation for Attack/Defense
- Advior: Prof. Mustaque Ahamad, and Prof. Srijan Kumar
- Research output: ACM KDD’21 code and data
- Proposed a Generative Adversarial Network (GAN)-based text generation framework for personalization and adversarial attack
- Design a multi-stage multi-task optimization strategy to improve the generation performance
- Leverage adversarial machine learning for fine-tuning and enhancing the model robustness
- BERT-based Fine-grained Text and Textual Sequence Classification
- Advior: Prof. Mustaque Ahamad, and Prof. Srijan Kumar
- Research output: IEEE BigData’20 code and data and ACM ASONAM’21 code and data
- Implement the masked language model-enhanced fine-tuning- and feature-based BERT for misinformation and hate speech classification
- Propose the transformer-based sequence-aware deep sequence classifier powered by data augmentation from OpenAI ChatGPT and GPT4
- Crawl large-scale tweets and user networks, and analyze the spread of misinformation and hate speech on Twitter
