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 801–850 of 1961 papers

TitleStatusHype
To be or not to be an Integer? Encoding Variables for Mathematical Text—0
ASCM: An Answer Space Clustered Prompting Method without Answer EngineeringCode0
Clustering Examples in Multi-Dataset Benchmarks with Item Response Theory—0
ClusterFormer: Neural Clustering Attention for Efficient and Effective Transformer—0
XInfoTabS: Evaluating Multilingual Tabular Natural Language Inference—0
Capture Human Disagreement Distributions by Calibrated Networks for Natural Language Inference—0
Enhancing Cross-lingual Natural Language Inference by Prompt-learning from Cross-lingual TemplatesCode0
Empathy and Distress Prediction using Transformer Multi-output Regression and Emotion Analysis with an Ensemble of Supervised and Zero-Shot Learning Models—0
PARADISE”:" Exploiting Parallel Data for Multilingual Sequence-to-Sequence Pretraining—0
Document Retrieval and Claim Verification to Mitigate COVID-19 Misinformation—0
Uncovering Values: Detecting Latent Moral Content from Natural Language with Explainable and Non-Trained MethodsCode0
Solution of DeBERTaV3 on CommonsenseQACode0
Developmental Negation Processing in Transformer Language ModelsCode0
Adaptable Text Matching via Meta-Weight Regulator—0
Making the Most of Text Semantics to Improve Biomedical Vision--Language ProcessingCode0
Compositional Semantics and Inference System for Temporal Order based on Japanese CCGCode0
Logical Inference for Counting on Semi-structured TablesCode0
Bridging Cross-Lingual Gaps During Leveraging the Multilingual Sequence-to-Sequence Pretraining for Text Generation and UnderstandingCode0
Stretching Sentence-pair NLI Models to Reason over Long Documents and ClustersCode0
Anti-Asian Hate Speech Detection via Data Augmented Semantic Relation Inference—0
The Impact of Cross-Lingual Adjustment of Contextual Word Representations on Zero-Shot TransferCode0
A Multilingual Perspective Towards the Evaluation of Attribution Methods in Natural Language InferenceCode0
Doctor XAvIer: Explainable Diagnosis on Physician-Patient Dialogues and XAI EvaluationCode0
Entailment Graph Learning with Textual Entailment and Soft TransitivityCode0
Example-based Hypernetworks for Out-of-Distribution GeneralizationCode0
Generating Data to Mitigate Spurious Correlations in Natural Language Inference DatasetsCode0
VLSP 2021 - ViMRC Challenge: Vietnamese Machine Reading Comprehension—0
DEIM: An effective deep encoding and interaction model for sentence matching—0
Entailment Relation Aware Paraphrase Generation—0
A Neural-Symbolic Approach to Natural Language UnderstandingCode0
Cross-Lingual Ability of Multilingual Masked Language Models: A Study of Language Structure—0
Generalized but not Robust? Comparing the Effects of Data Modification Methods on Out-of-Domain Generalization and Adversarial Robustness—0
On the Calibration of Pre-trained Language Models using Mixup Guided by Area Under the Margin and Saliency—0
A Survey of Adversarial Defences and Robustness in NLP—0
Neuro-symbolic Natural Logic with Introspective Revision for Natural Language InferenceCode0
Compliance Checking with NLI: Privacy Policies vs. Regulations—0
Novelty Detection: A Perspective from Natural Language Processing—0
Embarrassingly Simple Performance Prediction for Abductive Natural Language InferenceCode0
GraphNLI: A Graph-based Natural Language Inference Model for Polarity Prediction in Online DebatesCode0
AdaPrompt: Adaptive Model Training for Prompt-based NLP—0
Comparison and Combination of Sentence Embeddings Derived from Different Supervision Signals—0
Zero-Shot Aspect-Based Sentiment Analysis—0
GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records—0
CsFEVER and CTKFacts: Acquiring Czech data for fact verificationCode0
Pair-Level Supervised Contrastive Learning for Natural Language Inference—0
TextHacker: Learning based Hybrid Local Search Algorithm for Text Hard-label Adversarial AttackCode0
Uncovering More Shallow Heuristics: Probing the Natural Language Inference Capacities of Transformer-Based Pre-Trained Language Models Using Syllogistic Patterns—0
DISTRIBUTIONALLY ROBUST NEURAL NETWORKS FOR GROUP SHIFTS ON THE IMPORTANCE OF REGULARIZATION FOR WORST-CASE GENERALIZATION—0
DialogueScore: Evaluating Responses in Task-Oriented Dialogue—0
Balanced Adversarial Training: Balancing Tradeoffs Between Oversensitivity and Undersensitivity in NLP Models—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