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 251–300 of 1961 papers

TitleStatusHype
Cross-Thought for Sentence Encoder Pre-trainingCode1
Z-BERT-A: a zero-shot Pipeline for Unknown Intent detectionCode1
BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in BanglaCode1
ZeroGen: Efficient Zero-shot Learning via Dataset GenerationCode1
Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat ViolenceCode1
Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical ReasoningCode1
Cross-Lingual Word Embedding Refinement by _1 Norm OptimisationCode1
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and LanguageCode1
ConjNLI: Natural Language Inference Over Conjunctive SentencesCode1
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less DataCode1
Cross-Lingual Word Embedding Refinement by _1 Norm OptimisationCode1
Cross-Modal BERT for Text-Audio Sentiment AnalysisCode1
ContractNLI: A Dataset for Document-level Natural Language Inference for ContractsCode1
An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language ModelsCode1
Can NLI Models Verify QA Systems’ Predictions?Code1
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and ComprehensionCode1
Deep Learning Based Text Classification: A Comprehensive ReviewCode1
Citation-Enhanced Generation for LLM-based ChatbotsCode1
Contrastive Learning of Sentence Embeddings from ScratchCode1
BERTs of a feather do not generalize together: Large variability in generalization across models with similar test set performanceCode1
Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERTCode1
A Broad-Coverage Challenge Corpus for Sentence Understanding through InferenceCode1
Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with 1/n ParametersCode1
Can NLI Models Verify QA Systems' Predictions?Code1
Calibration of Pre-trained TransformersCode1
Distributed NLI: Learning to Predict Human Opinion Distributions for Language ReasoningCode1
Big Bird: Transformers for Longer SequencesCode1
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case GeneralizationCode1
Are self-explanations from Large Language Models faithful?Code1
Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset BiasesCode1
EENLP: Cross-lingual Eastern European NLP IndexCode1
BioELECTRA:Pretrained Biomedical text Encoder using DiscriminatorsCode1
DataMUX: Data Multiplexing for Neural NetworksCode1
Discrete and Soft Prompting for Multilingual ModelsCode1
Evaluating Factuality in Generation with Dependency-level EntailmentCode1
Entailment as Few-Shot LearnerCode1
Evaluating Attribution in Dialogue Systems: The BEGIN BenchmarkCode1
Evaluating Multimodal Representations on Visual Semantic Textual SimilarityCode1
Can NLI Provide Proper Indirect Supervision for Low-resource Biomedical Relation Extraction?Code1
Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4Code1
Exploring the Benefits of Training Expert Language Models over Instruction TuningCode1
IndoNLI: A Natural Language Inference Dataset for IndonesianCode1
Faking Fake News for Real Fake News Detection: Propaganda-loaded Training Data GenerationCode1
FarsTail: A Persian Natural Language Inference DatasetCode1
Natural Language Rationales with Full-Stack Visual Reasoning: From Pixels to Semantic Frames to Commonsense GraphsCode1
Few-shot Learning with Multilingual Language ModelsCode1
Finding a Balanced Degree of Automation for Summary EvaluationCode1
BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla—0
An Analysis under a Unified Fomulation of Learning Algorithms with Output Constraints—0
An analysis of textual inference in German customer emails—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