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 51–100 of 1961 papers

TitleStatusHype
BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in BanglaCode1
Adversarial Filters of Dataset BiasesCode1
DocNLI: A Large-scale Dataset for Document-level Natural Language InferenceCode1
Do Multilingual Language Models Think Better in English?Code1
Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language InferenceCode1
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case GeneralizationCode1
Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERTCode1
BERTs of a feather do not generalize together: Large variability in generalization across models with similar test set performanceCode1
Empowering Language Understanding with Counterfactual ReasoningCode1
An Empirical Study of Pre-trained Transformers for Arabic Information ExtractionCode1
Big Bird: Transformers for Longer SequencesCode1
Enhancing adversarial robustness in Natural Language Inference using explanationsCode1
Dynamic Self-Attention : Computing Attention over Words Dynamically for Sentence EmbeddingCode1
Deep contextualized word representationsCode1
Decorrelate Irrelevant, Purify Relevant: Overcome Textual Spurious Correlations from a Feature PerspectiveCode1
Deep Learning Based Text Classification: A Comprehensive ReviewCode1
A Statistical Framework for Low-bitwidth Training of Deep Neural NetworksCode1
Assessing the Generalization Capacity of Pre-trained Language Models through Japanese Adversarial Natural Language InferenceCode1
A Structured Self-attentive Sentence EmbeddingCode1
Defeasible Visual Entailment: Benchmark, Evaluator, and Reward-Driven OptimizationCode1
ARMAN: Pre-training with Semantically Selecting and Reordering of Sentences for Persian Abstractive SummarizationCode1
Cross-Modal BERT for Text-Audio Sentiment AnalysisCode1
Cross-Thought for Sentence Encoder Pre-trainingCode1
Cross-Lingual Word Embedding Refinement by _1 Norm OptimisationCode1
A large annotated corpus for learning natural language inferenceCode1
Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat ViolenceCode1
Cross-Lingual Word Embedding Refinement by _1 Norm OptimisationCode1
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and LanguageCode1
DefSent: Sentence Embeddings using Definition SentencesCode1
Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical ReasoningCode1
Addressing Inquiries about History: An Efficient and Practical Framework for Evaluating Open-domain Chatbot ConsistencyCode1
Compositional Explanations of NeuronsCode1
Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESuppositionCode1
Are Large Language Models Ready for Healthcare? A Comparative Study on Clinical Language UnderstandingCode1
Compositional Exemplars for In-context LearningCode1
A Decomposable Attention Model for Natural Language InferenceCode1
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less DataCode1
Combining Event Semantics and Degree Semantics for Natural Language InferenceCode1
New Protocols and Negative Results for Textual Entailment Data CollectionCode1
DataMUX: Data Multiplexing for Neural NetworksCode1
A Study of Situational Reasoning for Traffic UnderstandingCode1
Compositional Evaluation on Japanese Textual Entailment and SimilarityCode1
A Surprisingly Robust Trick for Winograd Schema ChallengeCode1
A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark DatasetsCode1
ConjNLI: Natural Language Inference Over Conjunctive SentencesCode1
CIDER: Commonsense Inference for Dialogue Explanation and ReasoningCode1
Differentiable Subset Pruning of Transformer HeadsCode1
DISCO: Distilling Counterfactuals with Large Language ModelsCode1
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated PromptsCode1
An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language ModelsCode1
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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