The ability to evaluate intermediate results in a Question Answering (QA) system, which we call introspection, is necessary in architectures based on planning or on processing loops. In particular, it is needed to determine if an earlier phase must be retried, or if the response "No Answer" ...
We will be using Hugging Face’sTransformerslibrary for training our QA model. We will also be using BioBERT, which is a language model based on BERT, with the only difference being that it has been finetuned with MLM and NSP objectives on different combinations of general & biomedical domai...
Machine LearningOne of the most important aspects of the learning process is the assessment of the knowledge acquired by the learners.In typical assessment like Exam, Assignment or Quiz, a grader provides students with feedback on their ans...
Empowering Educators: Automated Short Answer Grading with Inconsistency Check and Feedback Integration using Machine Learning Automatic Short Answer Grading (ASAG) is a thriving domain of natural language understanding, focusing on learning analytics research. ASAG solutions are d... PS Lakshmi,JB Simha...
Answer-driven Deep Question Generation based on Reinforcement Learning.COLING, 2020. 多任务学习 通过一些辅助任务来提升QG的能力,如通过语言建模来提升句子表示;通过复述生成增加表达的多样性;通过语义匹配和答案位置预测来缓解生成的疑问词不合适和copy不相关词汇的问题。
🏡 Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering. nlp deep-learning pytorch question-answering transfer-learning pretrained-models language-models ner nlp-library bert nlp-framework roberta xlnet-pytorch germanbert Updated Dec 20, 202...
MS MARCO(Microsoft Machine Reading Comprehension) is a large scale dataset focused on machine reading comprehension, question answering, and passage ranking. In MS MARCO, all question have been generated from real anonymized Bing user queries which grounds the dataset in a real world problem and can...
We found that although NQG can generate fluent and relevant factoid-type questions, few studies focus on education. Specifically, there is limited literature using context in the form of multi-paragraphs, which due to the input limitation of the current deep learning techniques, require key ...
Unlike many aspects of BI and data mining we are not on a fishing expedition, and although ML can just be use to explore data with its built in tools or via your own Python / R scripts that is not what is was designed for. The typical use cases for ML - predict...
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