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cs.CL2022★ 1 cited
Transparency Helps Reveal When Language Models Learn Meaning
Zhaofeng Wu, William Merrill, Hao Peng +2
Many current NLP systems are built from language models trained to optimize unsupervised objectives on large amounts of raw text. Under what conditions might such a procedure acqui…
cs.CL2022
Entailment Semantics Can Be Extracted from an Ideal Language Model
William Merrill, Alex Warstadt, Tal Linzen
Language models are often trained on text alone, without additional grounding. There is debate as to how much of natural language semantics can be inferred from such a procedure. W…