4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.CL2021
Embracing Ambiguity: Shifting the Training Target of NLI Models
Johannes Mario Meissner, Napat Thumwanit, Saku Sugawara +1
Natural Language Inference (NLI) datasets contain examples with highly ambiguous labels. While many research works do not pay much attention to this fact, several recent efforts ha…
quant-ph2021★ 4 cited
Trainable Discrete Feature Embeddings for Variational Quantum Classifier
Napat Thumwanit, Chayaphol Lortaraprasert, Hiroshi Yano +1
Quantum classifiers provide sophisticated embeddings of input data in Hilbert space promising quantum advantage. The advantage stems from quantum feature maps encoding the inputs i…