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

Showing 251300 of 1961 papers

TitleStatusHype
Zero-Shot Cross-Lingual Transfer with Meta LearningCode1
PhoBERT: Pre-trained language models for VietnameseCode1
Improving BERT Fine-Tuning via Self-Ensemble and Self-DistillationCode1
From English To Foreign Languages: Transferring Pre-trained Language ModelsCode1
Utilizing BERT Intermediate Layers for Aspect Based Sentiment Analysis and Natural Language InferenceCode1
Adversarial Filters of Dataset BiasesCode1
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language InferenceCode1
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case GeneralizationCode1
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized OptimizationCode1
BERTs of a feather do not generalize together: Large variability in generalization across models with similar test set performanceCode1
ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram RepresentationsCode1
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and ComprehensionCode1
Evaluating the Factual Consistency of Abstractive Text SummarizationCode1
Q8BERT: Quantized 8Bit BERTCode1
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighterCode1
Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset BiasesCode1
Supervised Multimodal Bitransformers for Classifying Images and TextCode1
KagNet: Knowledge-Aware Graph Networks for Commonsense ReasoningCode1
Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial CrowdsCode1
Overview of the MEDIQA 2019 Shared Task on Textual Inference, Question Entailment and Question AnsweringCode1
Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and EntailmentCode1
RoBERTa: A Robustly Optimized BERT Pretraining ApproachCode1
XLNet: Generalized Autoregressive Pretraining for Language UnderstandingCode1
Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking DatasetsCode1
A Surprisingly Robust Trick for Winograd Schema ChallengeCode1
Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERTCode1
Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language InferenceCode1
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and BeyondCode1
e-SNLI: Natural Language Inference with Natural Language ExplanationsCode1
Transforming Question Answering Datasets Into Natural Language Inference DatasetsCode1
Dynamic Self-Attention : Computing Attention over Words Dynamically for Sentence EmbeddingCode1
The Natural Language Decathlon: Multitask Learning as Question AnsweringCode1
Jack the Reader - A Machine Reading FrameworkCode1
Improving Language Understanding by Generative Pre-TrainingCode1
On the Evaluation of Semantic Phenomena in Neural Machine Translation Using Natural Language InferenceCode1
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language UnderstandingCode1
SentEval: An Evaluation Toolkit for Universal Sentence RepresentationsCode1
Deep contextualized word representationsCode1
LangPro: Natural Language Theorem ProverCode1
Supervised Learning of Universal Sentence Representations from Natural Language Inference DataCode1
A Broad-Coverage Challenge Corpus for Sentence Understanding through InferenceCode1
A Structured Self-attentive Sentence EmbeddingCode1
NewsQA: A Machine Comprehension DatasetCode1
Enhanced LSTM for Natural Language InferenceCode1
A Decomposable Attention Model for Natural Language InferenceCode1
Order-Embeddings of Images and LanguageCode1
A large annotated corpus for learning natural language inferenceCode1
LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification0
DS@GT at CheckThat! 2025: Evaluating Context and Tokenization Strategies for Numerical Fact VerificationCode0
ARAG: Agentic Retrieval Augmented Generation for Personalized Recommendation0
Show:102550
← PrevPage 6 of 40Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UnitedSynT5 (3B)% Test Accuracy94.7Unverified
2UnitedSynT5 (335M)% Test Accuracy93.5Unverified
3EFL (Entailment as Few-shot Learner) + RoBERTa-large% Test Accuracy93.1Unverified
4Neural Tree Indexers for Text Understanding% Test Accuracy93.1Unverified
5RoBERTa-large+Self-Explaining% Test Accuracy92.3Unverified
6RoBERTa-large + self-explaining layer% Test Accuracy92.3Unverified
7CA-MTL% Test Accuracy92.1Unverified
8SemBERT% Test Accuracy91.9Unverified
9MT-DNN-SMARTLARGEv0% Test Accuracy91.7Unverified
10MT-DNN-SMART_100%ofTrainingDataDev Accuracy91.6Unverified
#ModelMetricClaimedVerifiedStatus
1Vega v2 6B (KD-based prompt transfer)Accuracy96Unverified
2PaLM 540B (fine-tuned)Accuracy95.7Unverified
3Turing NLR v5 XXL 5.4B (fine-tuned)Accuracy94.1Unverified
4ST-MoE-32B 269B (fine-tuned)Accuracy93.5Unverified
5DeBERTa-1.5BAccuracy93.2Unverified
6MUPPET Roberta LargeAccuracy92.8Unverified
7DeBERTaV3largeAccuracy92.7Unverified
8T5-XXL 11BAccuracy92.5Unverified
9T5-XXL 11B (fine-tuned)Accuracy92.5Unverified
10ST-MoE-L 4.1B (fine-tuned)Accuracy92.1Unverified
#ModelMetricClaimedVerifiedStatus
1UnitedSynT5 (3B)Matched92.6Unverified
2Turing NLR v5 XXL 5.4B (fine-tuned)Matched92.6Unverified
3T5-XXL 11B (fine-tuned)Matched92Unverified
4T5Matched92Unverified
5T5-11BMismatched91.7Unverified
6T5-3BMatched91.4Unverified
7ALBERTMatched91.3Unverified
8DeBERTa (large)Matched91.1Unverified
9Adv-RoBERTa ensembleMatched91.1Unverified
10SMARTRoBERTaDev Matched91.1Unverified