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 551–600 of 1961 papers

TitleStatusHype
Effective Cross-Task Transfer Learning for Explainable Natural Language Inference with T5Code0
Annotating omission in statement pairsCode0
BreakingBERT@IITK at SemEval-2021 Task 9 : Statement Verification and Evidence Finding with TablesCode0
Boosting Zero-Shot Crosslingual Performance using LLM-Based Augmentations with Effective Data SelectionCode0
Forget NLI, Use a Dictionary: Zero-Shot Topic Classification for Low-Resource Languages with Application to LuxembourgishCode0
FlauBERT: Unsupervised Language Model Pre-training for FrenchCode0
Fine-Grained Natural Language Inference Based Faithfulness Evaluation for Diverse Summarisation TasksCode0
Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty EstimationCode0
Frame- and Entity-Based Knowledge for Common-Sense Argumentative ReasoningCode0
Fill the GAP: Exploiting BERT for Pronoun ResolutionCode0
Figurative Language in Recognizing Textual EntailmentCode0
Finding Fuzziness in Neural Network Models of Language ProcessingCode0
DS@GT at CheckThat! 2025: Evaluating Context and Tokenization Strategies for Numerical Fact VerificationCode0
Annotating and analyzing the interactions between meaning relationsCode0
Fine-grained Entailment: Resources for Greek NLI and Precise EntailmentCode0
From Alignment to Entailment: A Unified Textual Entailment Framework for Entity AlignmentCode0
GPT-HateCheck: Can LLMs Write Better Functional Tests for Hate Speech Detection?Code0
Hyperbolic Neural NetworksCode0
Drop Dropout on Single-Epoch Language Model PretrainingCode0
Fake News Detection as Natural Language InferenceCode0
Extracting and filtering paraphrases by bridging natural language inference and paraphrasingCode0
Bipol: Multi-axes Evaluation of Bias with Explainability in Benchmark DatasetsCode0
Falsesum: Generating Document-level NLI Examples for Recognizing Factual Inconsistency in SummarizationCode0
Exploring Tokenization Strategies and Vocabulary Sizes for Enhanced Arabic Language ModelsCode0
BioNLI: Generating a Biomedical NLI Dataset Using Lexico-semantic Constraints for Adversarial ExamplesCode0
Exploring Transitivity in Neural NLI Models through VeridicalityCode0
Do Prompt-Based Models Really Understand the Meaning of their Prompts?Code0
Dynamic Compositionality in Recursive Neural Networks with Structure-aware Tag RepresentationsCode0
Bonafide at LegalLens 2024 Shared Task: Using Lightweight DeBERTa Based Encoder For Legal Violation Detection and ResolutionCode0
Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations in a Label-Abundant SetupCode0
Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language InferenceCode0
Extracting and Encoding: Leveraging Large Language Models and Medical Knowledge to Enhance Radiological Text RepresentationCode0
FarFetched: Entity-centric Reasoning and Claim Validation for the Greek Language based on Textually Represented EnvironmentsCode0
Don't Fight Hallucinations, Use Them: Estimating Image Realism using NLI over Atomic FactsCode0
Do Neural Language Representations Learn Physical Commonsense?Code0
Flexible Natural Language-Based Image Data Downlink Prioritization for NanosatellitesCode0
Ecologically Valid Explanations for Label Variation in NLICode0
EconNLI: Evaluating Large Language Models on Economics ReasoningCode0
ECon: On the Detection and Resolution of Evidence ConflictsCode0
Edinburgh Clinical NLP at SemEval-2024 Task 2: Fine-tune your model unless you have access to GPT-4Code0
An Imitation Learning Approach to Unsupervised ParsingCode0
Exploring the Limits of Natural Language Inference Based Setup for Few-Shot Intent DetectionCode0
Exploring Continual Learning of Compositional Generalization in NLICode0
Exploring Robustness of Multilingual LLMs on Real-World Noisy DataCode0
Efficient Annotator Reliability Assessment and Sample Weighting for Knowledge-Based Misinformation Detection on Social MediaCode0
From Key Points to Key Point Hierarchy: Structured and Expressive Opinion SummarizationCode0
From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label ClassificationCode0
From Text to Context: An Entailment Approach for News Stakeholder ClassificationCode0
A Hypothesis-Driven Framework for the Analysis of Self-Rationalising ModelsCode0
Do Language Models Understand Morality? Towards a Robust Detection of Moral ContentCode0
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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