Search Results for author:
Found 4 papers, 2 papers with code
Improving Factual Error Correction by Learning to Inject Factual Errors
Given the lack of paired data (i. e., false claims and their corresponding correct claims), existing methods typically adopt the mask-then-correct paradigm.
AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators
Many natural language processing (NLP) tasks rely on labeled data to train machine learning models with high performance.
CAPSTONE: Curriculum Sampling for Dense Retrieval with Document Expansion
The dual-encoder has become the de facto architecture for dense retrieval.
Metric-guided Distillation: Distilling Knowledge from the Metric to Ranker and Retriever for Generative Commonsense Reasoning
Commonsense generation aims to generate a realistic sentence describing a daily scene under the given concepts, which is very challenging, since it requires models to have relational reasoning and compositional generalization capabilities.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
