更复杂一点的做法则是增加一个组件判断输出到底有没有回答问题,可以用自然语言推理(Natural Language Inference, NLI)的方法去做。 在SQuAD 2.0发布后,就有人把当时在1.1上表现最好的BiDAF模型加上阈值在2.0上测试,F1得分一下降到了62。 2020年3月SQuAD 2.0排行榜末尾 不过SQuAD 2.0还是没有难倒各种复杂的模型。现...
如果仔细思考一下这个loss反向传播的路径,我们发现,parsing-decision的loss并不会影响直接composition function,只会通过Track LSTM。而 L_s 这一项,只会通过composition function(tree-lstm) -> Track LSTM, 并不会通过parsing的network,所以在一定程度上来说,tree-lstm和parsing network是分别训练的,这对下文出现的Co...
Natural Language Inference Natural Language Processing NLP Applications Question Answering Reading Comprehension Recommender Systems Resources and Evaluation Semantics Sentiment Analysis, Stylistic Analysis and Argument Mining Speech and Multimodality Summarization Tagging, Chunking, Syntax and Parsing Text Classificatio...
7. Zero-shot Text Classification With Generative Language Models NeurIPS 2019 2019.12.10 motivation: 针对zero-shot 任务进行任务统一(转换成 qa 问题),利用 taskdeion(prompt),快速适应新的任务 method: 8. Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference EACL 2021 ...
We introduce the Natural Language Decathlon (decaNLP), a challenge that spans ten tasks: question answering, machine translation, summarization, natural language inference, sentiment analysis, semantic role labeling, zero-shot relation extraction, goal-oriented dialogue, semantic parsing, and commonsense ...
Natural Language Inference LSTM SNLI Acc 80.7 80.6 Bowman et al. (2016) Summarization Seq2seq-LSTM CNN/Daily Mail RougeL 27.3 28.1 See et al. (2017) Pretrain-NER ELMO CoNLL 2003 F1 92.2 92.2 Peters et al. (2018) Pretrain-NER BERT CoNLL 2003 F1 94.6 94.9 Devlin et al. (2019)Speech...
Natural language inference (NLI): Considering a particular premise and hypothesis sentence, the training model classified hypotheses into entailment, contraction, and neutral. The performance was measured by the accuracy of the classification results. Named entity recognition (NER): The training model dis...
With shrinking natural resources and the climate challenges, it is foreseen that there will be an imminent stress in agricultural outputs. Deep learning provides immense possibilities in allowing computational models to learn representation of data generated for precise application of agricultural inputs an...
7.Zero-shot Text Classification With Generative Language Models NeurIPS 2019 2019.12.10 motivation: 针对zero-shot任务进行任务统一(转换成qa问题),利用taskdescription(prompt),快速适应新的任务 method: 8.Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference EACL 2021 2020.1...
基于这两个原因,作者提出了使用双向LSTM加速一个MLP作为提示编码器的结构。因为LSTM的复杂性,P-tuning在推理时也使用了重参数进行加速。 P-tuning还指出通过在提示中加入一些锚点标志(anchor token)可以提升模型的效果,这其实是一种连续提示和离散提示的混合。例如[PRE][prompt tokens][HYP]?[prompt][tokens][mask...