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 19011950 of 1961 papers

TitleStatusHype
ICT: A Translation based Method for Cross-lingual Textual Entailment0
Multilingual WSD with Just a Few Lines of Code: the BabelNet API0
HDU: Cross-lingual Textual Entailment with SMT Features0
A Probabilistic Lexical Model for Ranking Textual Inferences0
SAGAN: A Machine Translation Approach for Cross-Lingual Textual Entailment0
Extracting Context-Rich Entailment Rules from Wikipedia Revision History0
SAGAN: An approach to Semantic Textual Similarity based on Textual Entailment0
Probabilistic Finite State Machines for Regression-based MT Evaluation0
janardhan: Semantic Textual Similarity using Universal Networking Language graph matching0
FBK: Cross-Lingual Textual Entailment Without Translation0
BIUTEE: A Modular Open-Source System for Recognizing Textual Entailment0
How do Negation and Modality Impact on Opinions?0
Semeval-2012 Task 8: Cross-lingual Textual Entailment for Content Synchronization0
SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity0
Identifying Untyped Relation Mentions in a Corpus given an Ontology0
DirRelCond3: Detecting Textual Entailment Across Languages With Conditions On Directional Text Relatedness Scores0
BUAP: Lexical and Semantic Similarity for Cross-lingual Textual Entailment0
Measuring Semantic Relatedness using Multilingual Representations0
JU\_CSE\_NLP: Language Independent Cross-lingual Textual Entailment System0
Combining Textual Entailment and Argumentation Theory for Supporting Online Debates Interactions0
Identifying hypernyms in distributional semantic spaces0
A Comparison of Chinese Parsers for Stanford Dependencies0
Crowdsourcing Inference-Rule Evaluation0
Unsupervised Relation Discovery with Sense Disambiguation0
CELI: An Experiment with Cross Language Textual Entailment0
Graph Based Similarity Measures for Synonym Extraction from Parsed Text0
Soft Cardinality + ML: Learning Adaptive Similarity Functions for Cross-lingual Textual Entailment0
Crosslingual Induction of Semantic Roles0
Identifying Constant and Unique Relations by using Time-Series Text0
University\_Of\_Sheffield: Two Approaches to Semantic Text Similarity0
Excitatory or Inhibitory: A New Semantic Orientation Extracts Contradiction and Causality from the Web0
Efficient Search for Transformation-based Inference0
Efficient Tree-based Approximation for Entailment Graph Learning0
Local and Global Context for Supervised and Unsupervised Metonymy Resolution0
Detecting Semantic Equivalence and Information Disparity in Cross-lingual Documents0
Towards Effective Tutorial Feedback for Explanation Questions: A Dataset and Baselines0
Predicting Structures in NLP: Constrained Conditional Models and Integer Linear Programming in NLP0
Match without a Referee: Evaluating MT Adequacy without Reference Translations0
Measuring Word Relatedness Using Heterogeneous Vector Space Models0
On-Demand Distributional Semantic Distance and Paraphrasing0
Semantic Textual Similarity for MT evaluation0
Taxonomy Induction Using Hierarchical Random Graphs0
Identifying science concepts and student misconceptions in an interactive essay writing tutor0
Annotating Factive Verbs0
Chinese Whispers: Cooperative Paraphrase Acquisition0
Buildind a Resource of Patterns Using Semantic Types0
Constructing a Question Corpus for Textual Semantic Relations0
Assessing the Comparability of News Texts0
Building Japanese Predicate-argument Structure Corpus using Lexical Conceptual Structure0
Affective Common Sense Knowledge Acquisition for Sentiment Analysis0
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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