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Found 4 papers, 2 papers with code
Understanding Retrieval Augmentation for Long-Form Question Answering
Our study provides new insights on how retrieval augmentation impacts long, knowledge-rich text generation of LMs.
Continually Improving Extractive QA via Human Feedback
We study continually improving an extractive question answering (QA) system via human user feedback.
Rich Knowledge Sources Bring Complex Knowledge Conflicts: Recalibrating Models to Reflect Conflicting Evidence
Question answering models can use rich knowledge sources -- up to one hundred retrieved passages and parametric knowledge in the large-scale language model (LM).
Predict and Use Latent Patterns for Short-Text Conversation
Many neural network models nowadays have achieved promising performances in Chit-chat settings.
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