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
So-Called Non-Subsective Adjectives—0
LexSemTm: A Semantic Dataset Based on All-words Unsupervised Sense Distribution Learning—0
Detecting Stance in Tweets And Analyzing its Interaction with Sentiment—0
Sentence Embedding Evaluation Using Pyramid Annotation—0
Machine Comprehension using Rich Semantic Representations—0
ccg2lambda: A Compositional Semantics System—0
Towards Generalizable Sentence Embeddings—0
Most ``babies'' are ``little'' and most ``problems'' are ``huge'': Compositional Entailment in Adjective-Nouns—0
Annotating Relation Inference in Context via Question Answering—0
Combining Natural Logic and Shallow Reasoning for Question Answering—0
A critique of word similarity as a method for evaluating distributional semantic models—0
Learning Paraphrasing for Multiword Expressions—0
Harmonization of conflicting medical opinions using argumentation protocols and textual entailment - a case study on Parkinson disease—0
Syntax-based Attention Model for Natural Language Inference—0
Constructing a Natural Language Inference Dataset using Generative Neural NetworksCode0
An Empirical Evaluation of various Deep Learning Architectures for Bi-Sequence Classification Tasks—0
Neural Tree Indexers for Text UnderstandingCode0
Neural Semantic EncodersCode0
Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes—0
Neural Associative Memory for Dual-Sequence ModelingCode0
Addressing Limited Data for Textual Entailment Across Domains—0
Generating Natural Language Inference Chains—0
USFD at SemEval-2016 Task 6: Any-Target Stance Detection on Twitter with Autoencoders—0
ECNU at SemEval-2016 Task 1: Leveraging Word Embedding From Macro and Micro Views to Boost Performance for Semantic Textual Similarity—0
UniMelb at SemEval-2016 Task 3: Identifying Similar Questions by combining a CNN with String Similarity Measures—0
VENSESEVAL at Semeval-2016 Task 2 iSTS - with a full-fledged rule-based approach—0
Emergent: a novel data-set for stance classification—0
Unsupervised Learning of Prototypical Fillers for Implicit Semantic Role Labeling—0
SemEval-2016 Task 6: Detecting Stance in Tweets—0
SemEval-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual Evaluation—0
DLS@CU at SemEval-2016 Task 1: Supervised Models of Sentence Similarity—0
Regularizing Relation Representations by First-order Implications—0
JUNLP at SemEval-2016 Task 13: A Language Independent Approach for Hypernym Identification—0
ASOBEK at SemEval-2016 Task 1: Sentence Representation with Character N-gram Embeddings for Semantic Textual Similarity—0
UWB at SemEval-2016 Task 6: Stance Detection—0
SemEval-2016 Task 13: Taxonomy Extraction Evaluation (TExEval-2)—0
JU\_NLP at SemEval-2016 Task 6: Detecting Stance in Tweets using Support Vector Machines—0
Knowledge-Guided Linguistic Rewrites for Inference Rule VerificationCode0
NUIG-UNLP at SemEval-2016 Task 13: A Simple Word Embedding-based Approach for Taxonomy Extraction—0
FBK HLT-MT at SemEval-2016 Task 1: Cross-lingual Semantic Similarity Measurement Using Quality Estimation Features and Compositional Bilingual Word Embeddings—0
VUACLTL at SemEval 2016 Task 12: A CRF Pipeline to Clinical TempEval—0
SimiHawk at SemEval-2016 Task 1: A Deep Ensemble System for Semantic Textual Similarity—0
English Resource Semantics—0
Learning Natural Language Inference using Bidirectional LSTM model and Inner-AttentionCode0
Building an Evaluation Scale using Item Response Theory—0
Joint Learning of Sentence Embeddings for Relevance and EntailmentCode0
Machine Translation Evaluation Resources and Methods: A Survey—0
TEG-REP: A corpus of Textual Entailment Graphs based on Relation Extraction Patterns—0
Monolingual Social Media Datasets for Detecting Contradiction and Entailment—0
Passing a USA National Bar Exam: a First Corpus for Experimentation—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