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 1201–1250 of 1961 papers

TitleStatusHype
Learning the Difference that Makes a Difference with Counterfactually-Augmented DataCode0
Robust Natural Language Representation Learning for Natural Language Inference by Projecting Superficial Words out—0
Learning Entailment-Based Sentence Embeddings from Natural Language Inference—0
XD: Cross-lingual Knowledge Distillation for Polyglot Sentence Embeddings—0
TinyBERT: Distilling BERT for Natural Language UnderstandingCode0
On the Importance of Delexicalization for Fact Verification—0
Visuallly Grounded Generation of Entailments from Premises—0
Improving Generalization by Incorporating Coverage in Natural Language Inference—0
Improving Natural Language Inference with a Pretrained ParserCode0
Subword ELMo—0
Semantic Relatedness Based Re-ranker for Text SpottingCode0
Probing Natural Language Inference Models through Semantic FragmentsCode0
End-to-End Bias Mitigation by Modelling Biases in CorporaCode0
Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT—0
Mitigating Annotation Artifacts in Natural Language Inference Datasets to Improve Cross-dataset Generalization Ability—0
Symmetric Regularization based BERT for Pair-wise Semantic ReasoningCode0
Uncertain Natural Language Inference—0
Semantics-aware BERT for Language UnderstandingCode0
Identifying and Explaining Discriminative AttributesCode0
Certified Robustness to Adversarial Word SubstitutionsCode0
Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks—0
EoANN: Lexical Semantic Relation Classification Using an Ensemble of Artificial Neural Networks—0
A Wide-Coverage Symbolic Natural Language Inference System—0
Validation of Facts Against Textual Sources—0
Exploiting Open IE for Deriving Multiple Premises Entailment Corpus—0
NEZHA: Neural Contextualized Representation for Chinese Language UnderstandingCode0
A Logic-Driven Framework for Consistency of Neural ModelsCode0
Knowledge Enhanced Attention for Robust Natural Language Inference—0
Unlearn Dataset Bias in Natural Language Inference by Fitting the ResidualCode0
Measuring Patent Claim Generation by Span Relevancy—0
On Measuring and Mitigating Biased Inferences of Word EmbeddingsCode0
GeoSQA: A Benchmark for Scenario-based Question Answering in the Geography Domain at High School Level—0
Align, Mask and Select: A Simple Method for Incorporating Commonsense Knowledge into Language Representation Models—0
SenseBERT: Driving Some Sense into BERT—0
Abductive Commonsense ReasoningCode0
Reasoning-Driven Question-Answering for Natural Language Understanding—0
StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding—0
Do Neural Language Representations Learn Physical Commonsense?Code0
DELTA: A DEep learning based Language Technology plAtformCode0
NCUEE at MEDIQA 2019: Medical Text Inference Using Ensemble BERT-BiLSTM-Attention Model—0
KU\_ai at MEDIQA 2019: Domain-specific Pre-training and Transfer Learning for Medical NLI—0
UU\_TAILS at MEDIQA 2019: Learning Textual Entailment in the Medical Domain—0
MSIT\_SRIB at MEDIQA 2019: Knowledge Directed Multi-task Framework for Natural Language Inference in Clinical Domain.—0
Explaining Simple Natural Language InferenceCode0
ARS\_NITK at MEDIQA 2019:Analysing Various Methods for Natural Language Inference, Recognising Question Entailment and Medical Question Answering System—0
ANU-CSIRO at MEDIQA 2019: Question Answering Using Deep Contextual Knowledge—0
LasigeBioTM at MEDIQA 2019: Biomedical Question Answering using Bidirectional Transformers and Named Entity Recognition—0
Fill the GAP: Exploiting BERT for Pronoun ResolutionCode0
Saama Research at MEDIQA 2019: Pre-trained BioBERT with Attention Visualisation for Medical Natural Language Inference—0
Sieg at MEDIQA 2019: Multi-task Neural Ensemble for Biomedical Inference and Entailment—0
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All datasetsSNLIRTEMultiNLIQNLIANLI testWNLILiDiRusRCBTERRaCommitmentBankSciTailFarsTail

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UnitedSynT5 (3B)% Test Accuracy94.7—Unverified
2UnitedSynT5 (335M)% Test Accuracy93.5—Unverified
3EFL (Entailment as Few-shot Learner) + RoBERTa-large% Test Accuracy93.1—Unverified
4Neural Tree Indexers for Text Understanding% 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 11BAccuracy92.5—Unverified
9T5-XXL 11B (fine-tuned)Accuracy92.5—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
8DeBERTa (large)Matched91.1—Unverified
9Adv-RoBERTa ensembleMatched91.1—Unverified
10SMARTRoBERTaDev Matched91.1—Unverified