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HELP: A Dataset for Identifying Shortcomings of Neural Models in Monotonicity...
A new dataset for handling entailments with lexical and logical phenomena, called HELP, is introduced to investigate the shortcomings of neural models in monotonicity reasoning. -
SNLI, SciTail, and BreakingNLI
The dataset used in the paper is SNLI, SciTail, and BreakingNLI. -
Towards Improving Selective Prediction Ability of NLP Systems
SNLI, MNLI, Stress Test, Matched Mismatched, Competence, Distraction, and Noise datasets -
SNLI, MultiNLI, SciTail, and Quora Question Pairs
The dataset used for Natural Language Inference task, which involves a premise P = {p0, p1,..., pm−1} of m words and a hypothesis H = {h0, h1,..., hn−1} of n words, and aims to... -
Stanford Corpus of Implicatives
The Stanford Corpus of Implicatives is a dataset of natural language inference tasks. -
Se2: Sequential Example Selection for In-Context Learning
The paper proposes a novel approach to the sequential example selection paradigm for in-context learning. -
e-SNLI: Natural Language Inference with Natural Language Explanations
The e-SNLI dataset is a large-scale dataset for natural language inference, with human-written explanations for each sample. -
SNLI dataset
The dataset used in the paper is the SNLI dataset. -
MNLI and FEVER datasets
The MNLI and FEVER datasets are used to evaluate the proposed MoCaD framework. -
Breaking NLI
The Breaking NLI dataset is a test set constructed by taking premises from the SNLI training set and constructing several hypotheses from them by changing at most one word...
