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Found 5 papers, 1 papers with code
GPS: Genetic Prompt Search for Efficient Few-shot Learning
Prompt-based techniques have demostrated great potential for improving the few-shot generalization of pretrained language models.
ZeroPrompt: Scaling Prompt-Based Pretraining to 1,000 Tasks Improves Zero-Shot Generalization
We propose a multitask pretraining approach ZeroPrompt for zero-shot generalization, focusing on task scaling and zero-shot prompting.
Memory Augmented Sequential Paragraph Retrieval for Multi-hop Question Answering
To deal with this challenge, most of the existing works consider paragraphs as nodes in a graph and propose graph-based methods to retrieve them.
Is Graph Structure Necessary for Multi-hop Question Answering?
We construct a strong baseline model to establish that, with the proper use of pre-trained models, graph structure may not be necessary for multi-hop question answering.
TripleNet: Triple Attention Network for Multi-Turn Response Selection in Retrieval-based Chatbots
The heart of TripleNet is a novel attention mechanism named triple attention to model the relationships within the triple at four levels.
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