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 651–700 of 1961 papers

TitleStatusHype
Don't Fight Hallucinations, Use Them: Estimating Image Realism using NLI over Atomic FactsCode0
Do Neural Language Representations Learn Physical Commonsense?Code0
An Imitation Learning Approach to Unsupervised ParsingCode0
ETPC - A Paraphrase Identification Corpus Annotated with Extended Paraphrase Typology and NegationCode0
Generating Natural Adversarial ExamplesCode0
Generating Natural Language Adversarial ExamplesCode0
CASPR: Automated Evaluation Metric for Contrastive SummarizationCode0
Evaluating Coherence in Dialogue Systems using EntailmentCode0
Evaluating Compositionality in Sentence EmbeddingsCode0
Causal Abstractions of Neural NetworksCode0
Do Language Models Understand Morality? Towards a Robust Detection of Moral ContentCode0
Evaluating Gender Bias in Natural Language InferenceCode0
Adaptation of Deep Bidirectional Multilingual Transformers for Russian LanguageCode0
Generating Persona Consistent Dialogues by Exploiting Natural Language InferenceCode0
Guide the Learner: Controlling Product of Experts Debiasing Method Based on Token Attribution SimilaritiesCode0
From Machine Translation to Code-Switching: Generating High-Quality Code-Switched TextCode0
Bilateral Multi-Perspective Matching for Natural Language SentencesCode0
LiTEx: A Linguistic Taxonomy of Explanations for Understanding Within-Label Variation in Natural Language InferenceCode0
From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label ClassificationCode0
Does External Knowledge Help Explainable Natural Language Inference? Automatic Evaluation vs. Human RatingsCode0
Does Chinese BERT Encode Word Structure?Code0
From Text to Context: An Entailment Approach for News Stakeholder ClassificationCode0
Evaluating the Effectiveness of Natural Language Inference for Hate Speech Detection in Languages with Limited Labeled DataCode0
bgGLUE: A Bulgarian General Language Understanding Evaluation BenchmarkCode0
From Alignment to Entailment: A Unified Textual Entailment Framework for Entity AlignmentCode0
Frame- and Entity-Based Knowledge for Common-Sense Argumentative ReasoningCode0
From Key Points to Key Point Hierarchy: Structured and Expressive Opinion SummarizationCode0
FZI-WIM at SemEval-2024 Task 2: Self-Consistent CoT for Complex NLI in Biomedical DomainCode0
Doctor XAvIer: Explainable Diagnosis on Physician-Patient Dialogues and XAI EvaluationCode0
An Evaluation Framework for Mapping News Headlines to Event Classes in a Knowledge GraphCode0
D-NLP at SemEval-2024 Task 2: Evaluating Clinical Inference Capabilities of Large Language ModelsCode0
Machine Comprehension Using Match-LSTM and Answer PointerCode0
FlauBERT: Unsupervised Language Model Pre-training for FrenchCode0
Fine-grained Entailment: Resources for Greek NLI and Precise EntailmentCode0
Fine-Grained Natural Language Inference Based Faithfulness Evaluation for Diverse Summarisation TasksCode0
Marking: Visual Grading with Highlighting Errors and Annotating Missing BitsCode0
Flexible Natural Language-Based Image Data Downlink Prioritization for NanosatellitesCode0
Forget NLI, Use a Dictionary: Zero-Shot Topic Classification for Low-Resource Languages with Application to LuxembourgishCode0
Generating Data to Mitigate Spurious Correlations in Natural Language Inference DatasetsCode0
Explaining Neural Network Predictions on Sentence Pairs via Learning Word-Group MasksCode0
HellaSwag: Can a Machine Really Finish Your Sentence?Code0
A Neural-Symbolic Approach to Natural Language UnderstandingCode0
BERTSel: Answer Selection with Pre-trained ModelsCode0
Figurative Language in Recognizing Textual EntailmentCode0
Distilling Task-Specific Knowledge from BERT into Simple Neural NetworksCode0
Dissecting vocabulary biases datasets through statistical testing and automated data augmentation for artifact mitigation in Natural Language InferenceCode0
Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations in a Label-Abundant SetupCode0
Fill the GAP: Exploiting BERT for Pronoun ResolutionCode0
TinyBERT: Distilling BERT for Natural Language UnderstandingCode0
DisGeM: Distractor Generation for Multiple Choice Questions with Span MaskingCode0
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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