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
ContractNLI: A Dataset for Document-level Natural Language Inference for ContractsCode1
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
ConjNLI: Natural Language Inference Over Conjunctive SentencesCode1
Contrastive Learning of Sentence Embeddings from ScratchCode1
Cross-Lingual Word Embedding Refinement by _1 Norm OptimisationCode1
Compositional Exemplars for In-context LearningCode1
Compositional Evaluation on Japanese Textual Entailment and SimilarityCode1
Compositional Explanations of NeuronsCode1
Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical ReasoningCode1
Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat ViolenceCode1
Are self-explanations from Large Language Models faithful?Code1
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and ComprehensionCode1
ChatGPT: Jack of all trades, master of noneCode1
DataMUX: Data Multiplexing for Neural NetworksCode1
Building Efficient Universal Classifiers with Natural Language InferenceCode1
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less DataCode1
Deep contextualized word representationsCode1
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
Differentiable Subset Pruning of Transformer HeadsCode1
Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language InferenceCode1
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighterCode1
Big Bird: Transformers for Longer SequencesCode1
Distributionally Robust Neural NetworksCode1
Cross-Modal BERT for Text-Audio Sentiment AnalysisCode1
Don't Say No: Jailbreaking LLM by Suppressing RefusalCode1
Dynamic Self-Attention : Computing Attention over Words Dynamically for Sentence EmbeddingCode1
BioELECTRA:Pretrained Biomedical text Encoder using DiscriminatorsCode1
e-SNLI-VE: Corrected Visual-Textual Entailment with Natural Language ExplanationsCode1
Improving Factual Completeness and Consistency of Image-to-Text Radiology Report GenerationCode1
CALM : A Multi-task Benchmark for Comprehensive Assessment of Language Model BiasCode1
Enhancing Clinical BERT Embedding using a Biomedical Knowledge BaseCode1
CBLUE: A Chinese Biomedical Language Understanding Evaluation BenchmarkCode1
Evaluating Factuality in Generation with Dependency-level EntailmentCode1
Evaluating Multimodal Representations on Visual Semantic Textual SimilarityCode1
Evaluating the Factual Consistency of Abstractive Text SummarizationCode1
Can NLI Provide Proper Indirect Supervision for Low-resource Biomedical Relation Extraction?Code1
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language InferenceCode1
Natural Language Rationales with Full-Stack Visual Reasoning: From Pixels to Semantic Frames to Commonsense GraphsCode1
Can NLI Models Verify QA Systems' Predictions?Code1
FarsTail: A Persian Natural Language Inference DatasetCode1
Fast and Accurate Factual Inconsistency Detection Over Long DocumentsCode1
FENICE: Factuality Evaluation of summarization based on Natural language Inference and Claim ExtractionCode1
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
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 layer% Test Accuracy92.3—Unverified
6RoBERTa-large+Self-Explaining% 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
10UL2 20B (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