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cs.CL2024
Atomic Inference for NLI with Generated Facts as Atoms
Joe Stacey, Pasquale Minervini, Haim Dubossarsky +2
With recent advances, neural models can achieve human-level performance on various natural language tasks. However, there are no guarantees that any explanations from these models…
cs.CL2024
Distilling Robustness into Natural Language Inference Models with Domain-Targeted Augmentation
Joe Stacey, Marek Rei
Knowledge distillation optimises a smaller student model to behave similarly to a larger teacher model, retaining some of the performance benefits. While this method can improve re…