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 1601–1650 of 1961 papers

TitleStatusHype
Unveiling Divergent Inductive Biases of LLMs on Temporal DataCode0
uOttawa at LegalLens-2024: Transformer-based Classification ExperimentsCode0
Entailment Graph Learning with Textual Entailment and Soft TransitivityCode0
Entailed Between the Lines: Incorporating Implication into NLICode0
UoW: NLP techniques developed at the University of Wolverhampton for Semantic Similarity and Textual EntailmentCode0
CORE: A Retrieve-then-Edit Framework for Counterfactual Data GenerationCode0
HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on TextCode0
Enhancing Transformers with Gradient Boosted Decision Trees for NLI Fine-TuningCode0
Cooperative Learning of Disjoint Syntax and SemanticsCode0
Hybrid Autoregressive Inference for Scalable Multi-hop Explanation RegenerationCode0
Am I eligible? Natural Language Inference for Clinical Trial Patient Recruitment: the Patient's Point of ViewCode0
On Adversarial Removal of Hypothesis-only Bias in Natural Language InferenceCode0
Hy-NLI: a Hybrid system for Natural Language InferenceCode0
Enhancing Sentence Embedding with Generalized PoolingCode0
Hyperbolic Neural NetworksCode0
On Adversarial Robustness and Out-of-Distribution Robustness of Large Language ModelsCode0
A Generalized Framework of Sequence Generation with Application to Undirected Sequence ModelsCode0
Hypothesis Engineering for Zero-Shot Hate Speech DetectionCode0
Hypothesis Only Baselines in Natural Language InferenceCode0
Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair ModelingCode0
Improving Sequence Modeling Ability of Recurrent Neural Networks via SememesCode0
Textual Entailment for Effective Triple Validation in Object PredictionCode0
X-PARADE: Cross-Lingual Textual Entailment and Information Divergence across ParagraphsCode0
Continuous Prompt Tuning Based Textual Entailment Model for E-commerce Entity TypingCode0
Identifying and Explaining Discriminative AttributesCode0
UKP-Athene: Multi-Sentence Textual Entailment for Claim VerificationCode0
On Measuring and Mitigating Biased Inferences of Word EmbeddingsCode0
ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence PairsCode0
Identifying inherent disagreement in natural language inferenceCode0
Continual Few-Shot Learning for Text ClassificationCode0
Textual Entailment with Structured Attentions and CompositionCode0
Textual Inference: getting logic from humansCode0
Idiom Paraphrases: Seventh Heaven vs Cloud NineCode0
On the Stability of a non-hyperbolic nonlinear map with non-bounded set of non-isolated fixed points with applications to Machine LearningCode0
Lisbon Computational Linguists at SemEval-2024 Task 2: Using A Mistral 7B Model and Data AugmentationCode0
IITK at SemEval-2024 Task 2: Exploring the Capabilities of LLMs for Safe Biomedical Natural Language Inference for Clinical TrialsCode0
Constructing a Natural Language Inference Dataset using Generative Neural NetworksCode0
On the Language-specificity of Multilingual BERT and the Impact of Fine-tuningCode0
ZARA: Improving Few-Shot Self-Rationalization for Small Language ModelsCode0
On the Role of Summary Content Units in Text Summarization EvaluationCode0
A Logic-Driven Framework for Consistency of Neural ModelsCode0
On the use of Silver Standard Data for Zero-shot Classification Tasks in Information ExtractionCode0
An Imitation Learning Approach to Unsupervised ParsingCode0
Augmenting Neural Networks with First-order LogicCode0
The Curse of Performance Instability in Analysis Datasets: Consequences, Source, and SuggestionsCode0
Enhancing Generalization in Natural Language Inference by SyntaxCode0
OpenStance: Real-world Zero-shot Stance DetectionCode0
Word-level Textual Adversarial Attacking as Combinatorial OptimizationCode0
Adaptation of Deep Bidirectional Multilingual Transformers for Russian LanguageCode0
The Effect of Model Size on LLM Post-hoc Explainability via LIMECode0
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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