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Wenyang Tang

Hi 👋, I'm a graduate student specializing in Natural Language Processing (NLP), with a particular focus on improving the factuality and reliability of Large Language Models. My research aims to advance how AI systems can generate truthful and verifiable information, making them more reliable and trustworthy for real-world applications.

🎓 I am actively seeking PhD positions for the 2026 academic year! I'm particularly interested in research opportunities focusing on multi-modal Large Language Models and multi-modal Retrieval-Augmented Generation (RAG). Please feel free to reach out if you have opportunities or would like to discuss potential collaborations.

My research interests include:

  1. Hallucination Detection and LLM Factuality: My work focuses on developing methods to detect and prevent language models from generating false or unsupported information, while improving their ability to produce factual and verifiable outputs. This includes designing novel evaluation frameworks and techniques to enhance the truthfulness and reliability of large language models.
  2. Retrieval-Augmented Language Models: I'm exploring ways to enhance the performance of large language models by efficiently retrieving and incorporating relevant information from external knowledge sources.
  3. Reinforcement Learning: Drawing parallels to human learning processes, I'm also interested in applying reinforcement learning techniques to NLP tasks, particularly in scenarios where continuous adaptation and learning from feedback are crucial.

Feel free to reach out if you're interested in discussing NLP, reinforcement learning, or potential collaborations.

Published Papers