TRANSFORMER-STYLE LANGUAGE MODELS

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Challenge:	Existing sentences cannot account for different aspects of semantic similarity between two sentences.
Approach:	They propose a transformer-style framework that generates conditioned sentences . they propose 'conditional' STS, which measures similarity between two sentences based on condition sentences - a task that requires a sentence embedding model capable of generating distinct representations for the same sentence under different conditions.
Outcome:	The proposed framework is superior to existing models on two condition sentences . it can generate conditioned sentences while maintaining model parameters and computational efficiency .

Papers with transformer-style language models