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 151–200 of 1961 papers

TitleStatusHype
Cross-Thought for Sentence Encoder Pre-trainingCode1
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and LanguageCode1
Charformer: Fast Character Transformers via Gradient-based Subword TokenizationCode1
CIDER: Commonsense Inference for Dialogue Explanation and ReasoningCode1
Deep Learning Based Text Classification: A Comprehensive ReviewCode1
Defeasible Visual Entailment: Benchmark, Evaluator, and Reward-Driven OptimizationCode1
Can NLI Models Verify QA Systems’ Predictions?Code1
Differentiable Subset Pruning of Transformer HeadsCode1
Can NLI Models Verify QA Systems' Predictions?Code1
Distributionally Robust Neural NetworksCode1
DocNLI: A Large-scale Dataset for Document-level Natural Language InferenceCode1
Do Multilingual Language Models Think Better in English?Code1
Addressing Inquiries about History: An Efficient and Practical Framework for Evaluating Open-domain Chatbot ConsistencyCode1
Dynamic Self-Attention : Computing Attention over Words Dynamically for Sentence EmbeddingCode1
Can NLI Provide Proper Indirect Supervision for Low-resource Biomedical Relation Extraction?Code1
Empowering Language Understanding with Counterfactual ReasoningCode1
Can Explanations Be Useful for Calibrating Black Box Models?Code1
A Broad-Coverage Challenge Corpus for Sentence Understanding through InferenceCode1
e-SNLI: Natural Language Inference with Natural Language ExplanationsCode1
e-SNLI-VE: Corrected Visual-Textual Entailment with Natural Language ExplanationsCode1
Are self-explanations from Large Language Models faithful?Code1
Evaluating Multimodal Representations on Visual Semantic Textual SimilarityCode1
A Decomposable Attention Model for Natural Language InferenceCode1
Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4Code1
CBLUE: A Chinese Biomedical Language Understanding Evaluation BenchmarkCode1
Are Large Language Models Ready for Healthcare? A Comparative Study on Clinical Language UnderstandingCode1
Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESuppositionCode1
Faking Fake News for Real Fake News Detection: Propaganda-loaded Training Data GenerationCode1
Citation-Enhanced Generation for LLM-based ChatbotsCode1
FENICE: Factuality Evaluation of summarization based on Natural language Inference and Claim ExtractionCode1
ARMAN: Pre-training with Semantically Selecting and Reordering of Sentences for Persian Abstractive SummarizationCode1
Few-Shot Learning with Siamese Networks and Label TuningCode1
BioELECTRA:Pretrained Biomedical text Encoder using DiscriminatorsCode1
From English To Foreign Languages: Transferring Pre-trained Language ModelsCode1
Building Efficient Universal Classifiers with Natural Language InferenceCode1
From Hero to Zéroe: A Benchmark of Low-Level Adversarial AttacksCode1
Get Your Vitamin C! Robust Fact Verification with Contrastive EvidenceCode1
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language UnderstandingCode1
Guess the Instruction! Flipped Learning Makes Language Models Stronger Zero-Shot LearnersCode1
LLMs Learn Task Heuristics from Demonstrations: A Heuristic-Driven Prompting Strategy for Document-Level Event Argument ExtractionCode1
Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with 1/n ParametersCode1
Automatic Evaluation of Attribution by Large Language ModelsCode1
An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language ModelsCode1
Improving BERT Fine-Tuning via Self-Ensemble and Self-DistillationCode1
Improving Language Understanding by Generative Pre-TrainingCode1
Incorporating External Knowledge to Enhance Tabular ReasoningCode1
Inducing Causal Structure for Interpretable Neural NetworksCode1
InfoBERT: Improving Robustness of Language Models from An Information Theoretic PerspectiveCode1
Assessing the Generalization Capacity of Pre-trained Language Models through Japanese Adversarial Natural Language InferenceCode1
Big Bird: Transformers for Longer SequencesCode1
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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