11 citations · 16 across the 6 of their papers we have counts for
6 papers
Can Authorship Representation Learning Capture Stylistic Features?
Andrew Wang, Cristina Aggazzotti, Rebecca Kotula +3
Automatically disentangling an author's style from the content of their writing is a longstanding and possibly insurmountable problem in computational linguistics. At the same time…
Boosted Prompt Ensembles for Large Language Models
Silviu Pitis, Michael R. Zhang, Andrew Wang +1
Methods such as chain-of-thought prompting and self-consistency have pushed the frontier of language model reasoning performance with no additional training. To further improve per…
Operator Splitting Value Iteration
Amin Rakhsha, Andrew Wang, Mohammad Ghavamzadeh +1
We introduce new planning and reinforcement learning algorithms for discounted MDPs that utilize an approximate model of the environment to accelerate the convergence of the value…
Simple Text Detoxification by Identifying a Linear Toxic Subspace in Language Model Embeddings
Andrew Wang, Mohit Sudhakar, Yangfeng Ji
Large pre-trained language models are often trained on large volumes of internet data, some of which may contain toxic or abusive language. Consequently, language models encode tox…
iReason: Multimodal Commonsense Reasoning using Videos and Natural Language with Interpretability
Aman Chadha, Vinija Jain
Causality knowledge is vital to building robust AI systems. Deep learning models often perform poorly on tasks that require causal reasoning, which is often derived using some form…
Quantum Criticism: A Tagged News Corpus Analysed for Sentiment and Named Entities
Ashwini Badgujar, Sheng Chen, Andrew Wang +3
In this research, we continuously collect data from the RSS feeds of traditional news sources. We apply several pre-trained implementations of named entity recognition (NER) tools,…