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 951–1000 of 1961 papers

TitleStatusHype
SIRIUS-LTG: An Entity Linking Approach to Fact Extraction and Verification—0
SMoA: Sparse Mixture of Adapters to Mitigate Multiple Dataset Biases—0
So-Called Non-Subsective Adjectives—0
SOFTCARDINALITY-CORE: Improving Text Overlap with Distributional Measures for Semantic Textual Similarity—0
SOFTCARDINALITY: Hierarchical Text Overlap for Student Response Analysis—0
SOFTCARDINALITY: Learning to Identify Directional Cross-Lingual Entailment from Cardinalities and SMT—0
Soft Cardinality + ML: Learning Adaptive Similarity Functions for Cross-lingual Textual Entailment—0
Soft Label Memorization-Generalization for Natural Language Inference—0
Soft Layer Selection with Meta-Learning for Zero-Shot Cross-Lingual Transfer—0
Spot the Odd Man Out: Exploring the Associative Power of Lexical Resources—0
SPred: Large-scale Harvesting of Semantic Predicates—0
Squibs: What Is a Paraphrase?—0
sranjans : Semantic Textual Similarity using Maximal Weighted Bipartite Graph Matching—0
SRIUBC: Simple Similarity Features for Semantic Textual Similarity—0
SSAS: Semantic Similarity for Abstractive Summarization—0
Stanford: Probabilistic Edit Distance Metrics for STS—0
Stress Test Evaluation of Transformer-based Models in Natural Language Understanding Tasks—0
Stress-Testing Neural Models of Natural Language Inference with Multiply-Quantified Sentences—0
String Re-writing Kernel—0
Strong hallucinations from negation and how to fix them—0
StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding—0
Structural Representations for Learning Relations between Pairs of Texts—0
STRUCTURED ALIGNMENT NETWORKS—0
Structured Alignment Networks for Matching Sentences—0
Structured Attention Networks—0
Structured Learning for Taxonomy Induction with Belief Propagation—0
STS-UHH at SemEval-2017 Task 1: Scoring Semantic Textual Similarity Using Supervised and Unsupervised Ensemble—0
Stubborn Lexical Bias in Data and Models—0
Subword ELMo—0
SufiSent - Universal Sentence Representations Using Suffix Encodings—0
Supervised Distributional Hypernym Discovery via Domain Adaptation—0
Supervised Open Information Extraction—0
Surf at MEDIQA 2019: Improving Performance of Natural Language Inference in the Clinical Domain by Adopting Pre-trained Language Model—0
基於特徵為本及使用SVM 的文本對蘊涵關係的自動推論方法 (Textual Entailment Recognition Using Textual Features and SVM) [In Chinese]—0
SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference—0
SWOW-8500: Word Association task for Intrinsic Evaluation of Word Embeddings—0
SXUCFN-Core: STS Models Integrating FrameNet Parsing Information—0
SylloBio-NLI: Evaluating Large Language Models on Biomedical Syllogistic Reasoning—0
Synonym Acquisition Using Bilingual Comparable Corpora—0
Syntax-based Attention Model for Natural Language Inference—0
Systems' Agreements and Disagreements in Temporal Processing: An Extensive Error Analysis of the TempEval-3 Task—0
TAG Parser Evaluation using Textual Entailments—0
Tailor: Generating and Perturbing Text with Semantic Controls—0
TakeLab at SemEval-2018 Task12: Argument Reasoning Comprehension with Skip-Thought Vectors—0
Taking into account Inter-sentence Similarity for Update Summarization—0
Talking with the Theorem Prover to Interactively Solve Natural Language Inference—0
TALN-UPF: Taxonomy Learning Exploiting CRF-Based Hypernym Extraction on Encyclopedic Definitions—0
Targeted Data Generation: Finding and Fixing Model Weaknesses—0
Task-adaptive Pre-training and Self-training are Complementary for Natural Language Understanding—0
Task-Specific Attentive Pooling of Phrase Alignments Contributes to Sentence Matching—0
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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