Papers by Douglas Brown

2 papers
Evaluating Language Model Character Traits (2024.findings-emnlp)

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Challenge: Language models (LMs) exhibit human-like behaviour, but it is unclear how to describe this behaviour without undue anthropomorphism.
Approach: They formalise a behaviourist view of LM character traits and infer belief and intent from LM behaviour, finding consistency varies with model size, fine-tuning, and prompting.
Outcome: The proposed model enables us to describe LM behaviour precisely and without undue anthropomorphism.
Quantum Recurrent Architectures for Text Classification (2024.emnlp-main)

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Challenge: Recurrent neural networks (RNNs) were transformative in the early stages of neural NLP, but are now becoming a potentially transformative technology.
Approach: They develop quantum RNNs with cells based on Parametrised Quantum Circuits (PQCs) they use an angle encoder to define a (non-linear) mapping from a classical word embedding into the quantum Hilbert space.
Outcome: The proposed models are competitive with RNN baselines on the Rotten Tomatoes dataset and emulator results show they perform better than classical models.

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