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 501–550 of 1961 papers

TitleStatusHype
A Question-Answer Driven Approach to Reveal Affirmative Interpretations from Verbal NegationsCode0
New Datasets for Automatic Detection of Textual Entailment and of Contradictions between Sentences in FrenchCode0
Character-based Neural Networks for Sentence Pair ModelingCode0
A Generalized Framework of Sequence Generation with Application to Undirected Sequence ModelsCode0
A Puzzle-Based Dataset for Natural Language InferenceCode0
Generating Natural Adversarial ExamplesCode0
Certified Robustness to Adversarial Word SubstitutionsCode0
Developmental Negation Processing in Transformer Language ModelsCode0
Generating Natural Language Adversarial ExamplesCode0
Generating Data to Mitigate Spurious Correlations in Natural Language Inference DatasetsCode0
Accurate and Nuanced Open-QA Evaluation Through Textual EntailmentCode0
Generating Persona Consistent Dialogues by Exploiting Natural Language InferenceCode0
From Key Points to Key Point Hierarchy: Structured and Expressive Opinion SummarizationCode0
Application Specific Compression of Deep Learning ModelsCode0
From Machine Translation to Code-Switching: Generating High-Quality Code-Switched TextCode0
From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label ClassificationCode0
An Understanding-Oriented Robust Machine Reading Comprehension ModelCode0
Causal Abstractions of Neural NetworksCode0
CASPR: Automated Evaluation Metric for Contrastive SummarizationCode0
From Alignment to Entailment: A Unified Textual Entailment Framework for Entity AlignmentCode0
From Text to Context: An Entailment Approach for News Stakeholder ClassificationCode0
Flexible Natural Language-Based Image Data Downlink Prioritization for NanosatellitesCode0
A CCG-based Compositional Semantics and Inference System for ComparativesCode0
FlauBERT: Unsupervised Language Model Pre-training for FrenchCode0
Forget NLI, Use a Dictionary: Zero-Shot Topic Classification for Low-Resource Languages with Application to LuxembourgishCode0
Lisbon Computational Linguists at SemEval-2024 Task 2: Using A Mistral 7B Model and Data AugmentationCode0
Can neural networks understand monotonicity reasoning?Code0
Fine-Grained Natural Language Inference Based Faithfulness Evaluation for Diverse Summarisation TasksCode0
Frame- and Entity-Based Knowledge for Common-Sense Argumentative ReasoningCode0
FZI-WIM at SemEval-2024 Task 2: Self-Consistent CoT for Complex NLI in Biomedical DomainCode0
Guide the Learner: Controlling Product of Experts Debiasing Method Based on Token Attribution SimilaritiesCode0
Introducing a Lexicon of Verbal Polarity Shifters for EnglishCode0
Can Large Language Models Capture Dissenting Human Voices?Code0
Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations in a Label-Abundant SetupCode0
Figurative Language in Recognizing Textual EntailmentCode0
Can current NLI systems handle German word order? Investigating language model performance on a new German challenge set of minimal pairsCode0
FastTrees: Parallel Latent Tree-Induction for Faster Sequence EncodingCode0
CamemBERT: a Tasty French Language ModelCode0
AILS-NTUA at SemEval-2024 Task 6: Efficient model tuning for hallucination detection and analysisCode0
Fill the GAP: Exploiting BERT for Pronoun ResolutionCode0
A Novel Cartography-Based Curriculum Learning Method Applied on RoNLI: The First Romanian Natural Language Inference CorpusCode0
FarFetched: Entity-centric Reasoning and Claim Validation for the Greek Language based on Textually Represented EnvironmentsCode0
Fake News Detection as Natural Language InferenceCode0
Falsesum: Generating Document-level NLI Examples for Recognizing Factual Inconsistency in SummarizationCode0
Extracting and Encoding: Leveraging Large Language Models and Medical Knowledge to Enhance Radiological Text RepresentationCode0
Extracting and filtering paraphrases by bridging natural language inference and paraphrasingCode0
Exploring Tokenization Strategies and Vocabulary Sizes for Enhanced Arabic Language ModelsCode0
Building a Dictionary of Affixal NegationsCode0
Exploring Transitivity in Neural NLI Models through VeridicalityCode0
Exploring Continual Learning of Compositional Generalization in NLICode0
Show:102550
← PrevPage 11 of 40Next →
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