SOTAVerified

Natural Language Inference

Natural language inference (NLI) is the task of determining whether a "hypothesis" is true (entailment), false (contradiction), or undetermined (neutral) given a "premise".

Example:

| Premise | Label | Hypothesis | | --- | ---| --- | | A man inspects the uniform of a figure in some East Asian country. | contradiction | The man is sleeping. | | An older and younger man smiling. | neutral | Two men are smiling and laughing at the cats playing on the floor. | | A soccer game with multiple males playing. | entailment | Some men are playing a sport. |

Approaches used for NLI include earlier symbolic and statistical approaches to more recent deep learning approaches. Benchmark datasets used for NLI include SNLI, MultiNLI, SciTail, among others. You can get hands-on practice on the SNLI task by following this d2l.ai chapter.

Further readings:

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1851–1900 of 1961 papers

TitleStatusHype
MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text—0
Meaning Representation of Numeric Fused-Heads in UCCA—0
Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals—0
Measuring Patent Claim Generation by Span Relevancy—0
Measuring Semantic Relatedness using Multilingual Representations—0
Measuring Semantic Similarity for Bengali Tweets Using WordNet—0
Measuring the Groundedness of Legal Question-Answering Systems—0
Measuring Word Relatedness Using Heterogeneous Vector Space Models—0
MedHal: An Evaluation Dataset for Medical Hallucination Detection—0
Medical Knowledge-enriched Textual Entailment Framework—0
Meemi: A Simple Method for Post-processing and Integrating Cross-lingual Word Embeddings—0
Memory-Based Acquisition of Argument Structures and its Application to Implicit Role Detection—0
Meta-Embeddings for Natural Language Inference and Semantic Similarity tasks—0
MetaICL: Learning to Learn In Context—0
Meta-Learning with MAML on Trees—0
Metaphor Identification as Interpretation—0
Misleading Failures of Partial-input Baselines—0
Mitigating Annotation Artifacts in Natural Language Inference Datasets to Improve Cross-dataset Generalization Ability—0
Mitigating Dataset Artifacts in Natural Language Inference Through Automatic Contextual Data Augmentation and Learning Optimization—0
Mitigating the Diminishing Effect of Elastic Weight Consolidation—0
MITRE at SemEval-2017 Task 1: Simple Semantic Similarity—0
Modeling Extractive Sentence Intersection via Subtree Entailment—0
Modeling Human Inference Process for Textual Entailment Recognition—0
Modeling Semantic Relations Expressed by Prepositions—0
Modelling Domain Relationships for Transfer Learning on Retrieval-based Question Answering Systems in E-commerce—0
Modelling metaphor with attribute-based semantics—0
Improving Stance Detection by Leveraging Measurement Knowledge from Social Sciences: A Case Study of Dutch Political Tweets and Traditional Gender Role Division—0
Monolingual Social Media Datasets for Detecting Contradiction and Entailment—0
Montague Meets Markov: Deep Semantics with Probabilistic Logical Form—0
MorphNLI: A Stepwise Approach to Natural Language Inference Using Text Morphing—0
Most ``babies'' are ``little'' and most ``problems'' are ``huge'': Compositional Entailment in Adjective-Nouns—0
MSIT\_SRIB at MEDIQA 2019: Knowledge Directed Multi-task Framework for Natural Language Inference in Clinical Domain.—0
Multi-head attention debiasing and contrastive learning for mitigating Dataset Artifacts in Natural Language Inference—0
Multi-Level Alignments As An Extensible Representation Basis for Textual Entailment Algorithms—0
Multilingual Sentence-T5: Scalable Sentence Encoders for Multilingual Applications—0
Multilingual WSD with Just a Few Lines of Code: the BabelNet API—0
Multi-Metric Optimization Using Ensemble Tuning—0
UXLA: A Robust Unsupervised Data Augmentation Framework for Zero-Resource Cross-Lingual NLP—0
Multimodal Logical Inference System for Visual-Textual Entailment—0
Multi-Perspective Inferrer: Reasoning Sentences Relationship from Holistic Perspective—0
Multi-Scales Data Augmentation Approach In Natural Language Inference For Artifacts Mitigation And Pre-Trained Model Optimization—0
Multi-task Learning for Universal Sentence Embeddings: A Thorough Evaluation using Transfer and Auxiliary Tasks—0
NatLogAttack: A Framework for Attacking Natural Language Inference Models with Natural Logic—0
Natural Language Inference by Tree-Based Convolution and Heuristic Matching—0
Natural Language Inference for Arabic Using Extended Tree Edit Distance with Subtrees—0
Natural Language Inference from Multiple Premises—0
Natural Language Inference Improves Compositionality in Vision-Language Models—0
Natural Language Inference using Neural Network and Tableau Method—0
Natural Language Inference with Definition Embedding Considering Context On the Fly—0
Natural Language Inference with External Knowledge—0
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All datasetsSNLIRTEMultiNLIQNLIANLI testWNLILiDiRusRCBTERRaCommitmentBankSciTailFarsTail

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UnitedSynT5 (3B)% Test Accuracy94.7—Unverified
2UnitedSynT5 (335M)% Test Accuracy93.5—Unverified
3Neural Tree Indexers for Text Understanding% Test Accuracy93.1—Unverified
4EFL (Entailment as Few-shot Learner) + RoBERTa-large% Test Accuracy93.1—Unverified
5RoBERTa-large+Self-Explaining% Test Accuracy92.3—Unverified
6RoBERTa-large + self-explaining layer% Test Accuracy92.3—Unverified
7CA-MTL% Test Accuracy92.1—Unverified
8SemBERT% Test Accuracy91.9—Unverified
9MT-DNN-SMARTLARGEv0% Test Accuracy91.7—Unverified
10MT-DNN-SMART_100%ofTrainingDataDev Accuracy91.6—Unverified
#ModelMetricClaimedVerifiedStatus
1Vega v2 6B (KD-based prompt transfer)Accuracy96—Unverified
2PaLM 540B (fine-tuned)Accuracy95.7—Unverified
3Turing NLR v5 XXL 5.4B (fine-tuned)Accuracy94.1—Unverified
4ST-MoE-32B 269B (fine-tuned)Accuracy93.5—Unverified
5DeBERTa-1.5BAccuracy93.2—Unverified
6MUPPET Roberta LargeAccuracy92.8—Unverified
7DeBERTaV3largeAccuracy92.7—Unverified
8T5-XXL 11B (fine-tuned)Accuracy92.5—Unverified
9T5-XXL 11BAccuracy92.5—Unverified
10ST-MoE-L 4.1B (fine-tuned)Accuracy92.1—Unverified
#ModelMetricClaimedVerifiedStatus
1UnitedSynT5 (3B)Matched92.6—Unverified
2Turing NLR v5 XXL 5.4B (fine-tuned)Matched92.6—Unverified
3T5-XXL 11B (fine-tuned)Matched92—Unverified
4T5Matched92—Unverified
5T5-11BMismatched91.7—Unverified
6T5-3BMatched91.4—Unverified
7ALBERTMatched91.3—Unverified
8Adv-RoBERTa ensembleMatched91.1—Unverified
9DeBERTa (large)Matched91.1—Unverified
10SMARTRoBERTaDev Matched91.1—Unverified