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 1651–1700 of 1961 papers

TitleStatusHype
Conformalized Credal Set PredictorsCode0
ConEntail: An Entailment-based Framework for Universal Zero and Few Shot Classification with Supervised Contrastive PretrainingCode0
Enhancing Ethical Explanations of Large Language Models through Iterative Symbolic RefinementCode0
Enhancing Descriptive Image Captioning with Natural Language InferenceCode0
Accurate and Nuanced Open-QA Evaluation Through Textual EntailmentCode0
ConCSE: Unified Contrastive Learning and Augmentation for Code-Switched EmbeddingsCode0
Compositional Semantics and Inference System for Temporal Order based on Japanese CCGCode0
Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data TasksCode0
Enhancing Cross-lingual Natural Language Inference by Soft Prompting with Multilingual VerbalizerCode0
Using Focal Loss to Fight Shallow Heuristics: An Empirical Analysis of Modulated Cross-Entropy in Natural Language InferenceCode0
A Logic-Based Framework for Natural Language Inference in DutchCode0
Enhancing Cross-lingual Natural Language Inference by Prompt-learning from Cross-lingual TemplatesCode0
Sentence Pair Scoring: Towards Unified Framework for Text ComprehensionCode0
Sentence Representations via Gaussian EmbeddingCode0
Improving Natural Language Inference in Arabic using Transformer Models and Linguistically Informed Pre-TrainingCode0
Overconfidence in the Face of Ambiguity with Adversarial DataCode0
Improving Natural Language Inference with a Pretrained ParserCode0
Improving Personality Consistency in Conversation by Persona ExtendingCode0
Improving Pretrained Models for Zero-shot Multi-label Text Classification through Reinforced Label Hierarchy ReasoningCode0
Improving Results on Russian Sentiment DatasetsCode0
Improving Retrieval-Based Question Answering with Deep Inference ModelsCode0
Comparing Text Representations: A Theory-Driven ApproachCode0
Improving Sentence Embeddings with Automatic Generation of Training Data Using Few-shot ExamplesCode0
OYXOY: A Modern NLP Test Suite for Modern GreekCode0
Augmenting Legal Decision Support Systems with LLM-based NLI for Analyzing Social Media EvidenceCode0
Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and ApproachesCode0
Improving Truthfulness of Headline GenerationCode0
Combining Similarity Features and Deep Representation Learning for Stance Detection in the Context of Checking Fake NewsCode0
WTMED at MEDIQA 2019: A Hybrid Approach to Biomedical Natural Language InferenceCode0
Combining Fact Extraction and Verification with Neural Semantic Matching NetworksCode0
Sequence Learning Using Equilibrium PropagationCode0
Combining Axiom Injection and Knowledge Base Completion for Efficient Natural Language InferenceCode0
End-Task Oriented Textual Entailment via Deep Explorations of Inter-Sentence InteractionsCode0
Embracing Ambiguity: Shifting the Training Target of NLI ModelsCode0
The Impact of Cross-Lingual Adjustment of Contextual Word Representations on Zero-Shot TransferCode0
Embarrassingly Simple Performance Prediction for Abductive Natural Language InferenceCode0
Code Comment Inconsistency Detection with BERT and LongformerCode0
Inference and Verbalization Functions During In-Context LearningCode0
PARADISE: Exploiting Parallel Data for Multilingual Sequence-to-Sequence PretrainingCode0
InferES : A Natural Language Inference Corpus for Spanish Featuring Negation-Based Contrastive and Adversarial ExamplesCode0
Uncertainty-Aware Cross-Lingual Transfer with Pseudo Partial LabelsCode0
Efficient Annotator Reliability Assessment and Sample Weighting for Knowledge-Based Misinformation Detection on Social MediaCode0
InfoLossQA: Characterizing and Recovering Information Loss in Text SimplificationCode0
Effective Cross-Task Transfer Learning for Explainable Natural Language Inference with T5Code0
Several Experiments on Investigating Pretraining and Knowledge-Enhanced Models for Natural Language InferenceCode0
Parameter-Efficient Transformer EmbeddingsCode0
Uncertainty-Aware Natural Language Inference with Stochastic Weight AveragingCode0
In Search of the Long-Tail: Systematic Generation of Long-Tail Inferential Knowledge via Logical Rule Guided SearchCode0
Uncovering Agendas: A Novel French & English Dataset for Agenda Detection on Social MediaCode0
Using Natural Language Explanations to Improve Robustness of In-context LearningCode0
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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