Pengxiang Cheng

Pengxiang Cheng

I am a senior research scientist at Bloomberg AI, working on entity-centric analysis on news, social media, and financial documents, including named entity recognition, entity linking, and entity salience prediction.

I recently completed my Ph.D. in the Department of Computer Science at The University of Texas at Austin, advised by Professor Katrin Erk. During my time at UT Austin, my research interests lie in Natural Language Processing (NLP) and Computational Semantics. My dissertation focused on different approaches of integrating structural semantic knowledge into end-to-end neural models for better natural language understanding and reasoning.

Before coming to UT Austin, I completed my undergraduate studies at Tsinghua University, majoring in Automation and Economics.

Publications

Unsupervised Contrast-Consistent Ranking with Language Models.

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Overcoming Catastrophic Forgetting in Massively Multilingual Continual Learning.

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Dataless Knowledge Fusion by Merging Weights of Language Models.

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