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

Showing 17511800 of 1961 papers

TitleStatusHype
UTexas: Natural Language Semantics using Distributional Semantics and Probabilistic Logic0
Learning to Distinguish Hypernyms and Co-HyponymsCode0
ECNU: One Stone Two Birds: Ensemble of Heterogenous Measures for Semantic Relatedness and Textual Entailment0
Semantic Roles in Grammar Engineering0
CECL: a New Baseline and a Non-Compositional Approach for the Sick Benchmark0
Addressing Class Imbalance for Improved Recognition of Implicit Discourse Relations0
Training a Korean SRL System with Rich Morphological Features0
Semantic Parsing using Distributional Semantics and Probabilistic Logic0
Structured Learning for Taxonomy Induction with Belief Propagation0
The Excitement Open Platform for Textual Inferences0
Efficient Logical Inference for Semantic Processing0
Is the Stanford Dependency Representation Semantic?0
Combining Word Patterns and Discourse Markers for Paradigmatic Relation Classification0
Focused Entailment Graphs for Open IE Propositions0
Evaluation for Partial Event Coreference0
Recognizing Implied Predicate-Argument Relationships in Textual Inference0
Towards a Benchmark of Natural Language Arguments0
Corpus Annotation through Crowdsourcing: Towards Best Practice Guidelines0
Annotating the Focus of Negation in Japanese Text0
Detecting Subevent Structure for Event Coreference Resolution0
Comparing two acquisition systems for automatically building an English---Croatian parallel corpus from multilingual websites0
Predicate Matrix: extending SemLink through WordNet mappings0
The Multilingual Paraphrase Database0
The Meta-knowledge of Causality in Biomedical Scientific Discourse0
A hierarchical taxonomy for classifying hardness of inference tasks0
Resource Creation and Evaluation for Multilingual Sentiment Analysis in Social Media Texts0
A SICK cure for the evaluation of compositional distributional semantic models0
Can Crowdsourcing be used for Effective Annotation of Arabic?0
On Paraphrase Identification Corpora0
DerivBase.hr: A High-Coverage Derivational Morphology Resource for Croatian0
Aligning Predicate-Argument Structures for Paraphrase Fragment Extraction0
Inducing Example-based Semantic Frames from a Massive Amount of Verb Uses0
Resolving Coreferent and Associative Noun Phrases in Scientific Text0
Using Minimal Recursion Semantics for Entailment Recognition0
Tuning HeidelTime for identifying time expressions in clinical texts in English and French0
Natural Language Reasoning Using Proof-Assistant Technology: Rich Typing and Beyond0
Annotating by Proving using SemAnTE0
Automatic Building and Using Parallel Resources for SMT from Comparable Corpora0
Natural Language Inference for Arabic Using Extended Tree Edit Distance with Subtrees0
First steps towards a Predicate Matrix0
IndoWordnet Visualizer: A Graphical User Interface for Browsing and Exploring Wordnets of Indian Languages0
Back to Basics for Monolingual Alignment: Exploiting Word Similarity and Contextual Evidence0
Improved CCG Parsing with Semi-supervised Supertagging0
Design and Realization of the EXCITEMENT Open Platform for Textual Entailment0
Detecting Bipolar Semantic Relations among Natural Language Arguments with Textual Entailment: a Study.0
From Textual Entailment to Knowledgeable Machines0
Determining is-a relationships for Textual Entailment0
Regular Patterns - Probably Approximately Correct Language Model0
A Logic-based Approach for Recognizing Textual Entailment Supported by Ontological Background Knowledge0
Automatic Knowledge Acquisition for Case Alternation between the Passive and Active Voices in Japanese0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UnitedSynT5 (3B)% Test Accuracy94.7Unverified
2UnitedSynT5 (335M)% Test Accuracy93.5Unverified
3EFL (Entailment as Few-shot Learner) + RoBERTa-large% Test Accuracy93.1Unverified
4Neural Tree Indexers for Text Understanding% Test Accuracy93.1Unverified
5RoBERTa-large+Self-Explaining% Test Accuracy92.3Unverified
6RoBERTa-large + self-explaining layer% Test Accuracy92.3Unverified
7CA-MTL% Test Accuracy92.1Unverified
8SemBERT% Test Accuracy91.9Unverified
9MT-DNN-SMARTLARGEv0% Test Accuracy91.7Unverified
10MT-DNN-SMART_100%ofTrainingDataDev Accuracy91.6Unverified
#ModelMetricClaimedVerifiedStatus
1Vega v2 6B (KD-based prompt transfer)Accuracy96Unverified
2PaLM 540B (fine-tuned)Accuracy95.7Unverified
3Turing NLR v5 XXL 5.4B (fine-tuned)Accuracy94.1Unverified
4ST-MoE-32B 269B (fine-tuned)Accuracy93.5Unverified
5DeBERTa-1.5BAccuracy93.2Unverified
6MUPPET Roberta LargeAccuracy92.8Unverified
7DeBERTaV3largeAccuracy92.7Unverified
8T5-XXL 11BAccuracy92.5Unverified
9T5-XXL 11B (fine-tuned)Accuracy92.5Unverified
10ST-MoE-L 4.1B (fine-tuned)Accuracy92.1Unverified
#ModelMetricClaimedVerifiedStatus
1UnitedSynT5 (3B)Matched92.6Unverified
2Turing NLR v5 XXL 5.4B (fine-tuned)Matched92.6Unverified
3T5-XXL 11B (fine-tuned)Matched92Unverified
4T5Matched92Unverified
5T5-11BMismatched91.7Unverified
6T5-3BMatched91.4Unverified
7ALBERTMatched91.3Unverified
8DeBERTa (large)Matched91.1Unverified
9Adv-RoBERTa ensembleMatched91.1Unverified
10SMARTRoBERTaDev Matched91.1Unverified