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Wenyang Tang

Hi 👋, I'm a graduate student specializing in Natural Language Processing (NLP), with a particular focus on Retrieval-Augmented Language Models and information retrieval. My research aims to push the boundaries of how machines understand and process human language, making them more efficient and effective in tasks such as question answering, document summarization, and semantic search.

My research interests include:

  1. 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.
  2. Information Retrieval: My work involves developing algorithms and techniques to improve the accuracy and speed of retrieving relevant information from large datasets.
  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 in these exciting fields!

Published Papers

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