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Found 4 papers, 0 papers with code
Verifiable by Design: Aligning Language Models to Quote from Pre-Training Data
To address these limitations, we tackle the verifiability goal with a different philosophy: we trivialize the verification process by developing models that quote verbatim statements from trusted sources in pre-training data.
Error Norm Truncation: Robust Training in the Presence of Data Noise for Text Generation Models
Text generation models are notoriously vulnerable to errors in the training data.
Simple yet Effective Code-Switching Language Identification with Multitask Pre-Training and Transfer Learning
Our methods include a stacked Residual CNN+GRU model and a multitask pre-training approach to use Automatic Speech Recognition (ASR) as an auxiliary task for CSLID.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Why Does Zero-Shot Cross-Lingual Generation Fail? An Explanation and a Solution
Zero-shot cross-lingual transfer is when a multilingual model is trained to perform a task in one language and then is applied to another language.
