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 1501–1550 of 1961 papers

TitleStatusHype
TAG Parser Evaluation using Textual Entailments—0
Neural Paraphrase Generation using Transfer Learning—0
Fake news stance detection using stacked ensemble of classifiers—0
Visual Denotations for Recognizing Textual Entailment—0
Evaluating Hierarchies of Verb Argument Structure with Hierarchical Clustering—0
Inter-Weighted Alignment Network for Sentence Pair Modeling—0
Identifying Semantic Edit Intentions from Revisions in Wikipedia—0
LangPro: Natural Language Theorem ProverCode1
Shortcut-Stacked Sentence Encoders for Multi-Domain InferenceCode0
Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language InferenceCode0
Detecting Cross-Lingual Semantic Divergence for Neural Machine Translation—0
The Event StoryLine Corpus: A New Benchmark for Causal and Temporal Relation Extraction—0
Prediction of Frame-to-Frame Relations in the FrameNet Hierarchy with Frame Embeddings—0
STS-UHH at SemEval-2017 Task 1: Scoring Semantic Textual Similarity Using Supervised and Unsupervised Ensemble—0
Acquiring Predicate Paraphrases from News Tweets—0
MITRE at SemEval-2017 Task 1: Simple Semantic Similarity—0
Detecting Asymmetric Semantic Relations in Context: A Case-Study on Hypernymy Detection—0
Generating Pattern-Based Entailment Graphs for Relation Extraction—0
SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation—0
The RepEval 2017 Shared Task: Multi-Genre Natural Language Inference with Sentence Representations—0
Character-level Intra Attention Network for Natural Language InferenceCode0
Refining Raw Sentence Representations for Textual Entailment Recognition via AttentionCode0
Learning to Compose Task-Specific Tree StructuresCode0
A Monotonicity Calculus and Its Completeness—0
RelTextRank: An Open Source Framework for Building Relational Syntactic-Semantic Text Pair Representations—0
An Empirical Study on End-to-End Sentence Modelling—0
Evaluating Compound Splitters Extrinsically with Textual Entailment—0
TextFlow: A Text Similarity Measure based on Continuous Sequences—0
Dynamic Integration of Background Knowledge in Neural NLU Systems—0
Learning to Compute Word Embeddings On the Fly—0
Jointly Learning Sentence Embeddings and Syntax with Unsupervised Tree-LSTMs—0
Max-Cosine Matching Based Neural Models for Recognizing Textual Entailment—0
Second-Order Word Embeddings from Nearest Neighbor Topological FeaturesCode0
A Regularized Framework for Sparse and Structured Neural AttentionCode0
Supervised Learning of Universal Sentence Representations from Natural Language Inference DataCode1
A Broad-Coverage Challenge Corpus for Sentence Understanding through InferenceCode1
Baselines and test data for cross-lingual inferenceCode0
Integer Linear Programming formulations in Natural Language Processing—0
Arabic Textual Entailment with Word Embeddings—0
Social Bias in Elicited Natural Language InferencesCode0
Annotating omission in statement pairsCode0
Modelling metaphor with attribute-based semantics—0
How Well Can We Predict Hypernyms from Word Embeddings? A Dataset-Centric Analysis—0
Learning to Predict Denotational Probabilities For Modeling Entailment—0
On-demand Injection of Lexical Knowledge for Recognising Textual Entailment—0
A Structured Self-attentive Sentence EmbeddingCode1
Soft Label Memorization-Generalization for Natural Language Inference—0
Understanding Deep Learning Performance through an Examination of Test Set Difficulty: A Psychometric Case Study—0
Bilateral Multi-Perspective Matching for Natural Language SentencesCode0
Structured Attention Networks—0
Show:102550
← PrevPage 31 of 40Next →
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