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 1351–1400 of 1961 papers

TitleStatusHype
Black-Box Analysis: GPTs Across Time in Legal Textual Entailment Task—0
BloombergGPT: A Large Language Model for Finance—0
Book Reviews: Recognizing Textual Entailment: Models and Applications by Ido Dagan, Dan Roth, Mark Sammons and Fabio Massimo Zanzotto—0
Boosting Neural Language Inference via Cascaded Interactive Reasoning—0
BreakingBERT@IITK at SemEval-2021 Task 9: Statement Verification and Evidence Finding with Tables—0
Bridging Fairness and Environmental Sustainability in Natural Language Processing—0
Bridging Knowledge Gaps in Neural Entailment via Symbolic Models—0
BUAP: Evaluating Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment—0
BUAP: Lexical and Semantic Similarity for Cross-lingual Textual Entailment—0
BUAP: N-gram based Feature Evaluation for the Cross-Lingual Textual Entailment Task—0
Buildind a Resource of Patterns Using Semantic Types—0
Building an Evaluation Scale using Item Response Theory—0
Building compositional semantics and higher-order inference system for a wide-coverage Japanese CCG parser—0
Building Japanese Predicate-argument Structure Corpus using Lexical Conceptual Structure—0
Building Japanese Textual Entailment Specialized Data Sets for Inference of Basic Sentence Relations—0
Calibrating Likelihoods towards Consistency in Summarization Models—0
Can Crowdsourcing be used for Effective Annotation of Arabic?—0
Can Explanations Be Useful for Calibrating Black Box Models?—0
Can Pre-trained Models Really Generate Single-Step Textual Entailment?—0
Can We Automate the Analysis of Online Child Sexual Exploitation Discourse?—0
Capture Human Disagreement Distributions by Calibrated Networks for Natural Language Inference—0
Capturing Label Distribution: A Case Study in NLI—0
CASE 2021 Task 2: Zero-Shot Classification of Fine-Grained Sociopolitical Events with Transformer Models—0
Causal Transformers: Improving the Robustness on Spurious Correlations—0
ccg2lambda: A Compositional Semantics System—0
CECL: a New Baseline and a Non-Compositional Approach for the Sick Benchmark—0
CELI: An Experiment with Cross Language Textual Entailment—0
Celi: EDITS and Generic Text Pair Classification—0
Cell-aware Stacked LSTMs for Modeling Sentences—0
CFILT-CORE: Semantic Textual Similarity using Universal Networking Language—0
ChatGPT as a Factual Inconsistency Evaluator for Text Summarization—0
ChatGPT-Crawler: Find out if ChatGPT really knows what it's talking about—0
Chinese Whispers: Cooperative Paraphrase Acquisition—0
CICBUAPnlp: Graph-Based Approach for Answer Selection in Community Question Answering Task—0
CLaC-CORE: Exhaustive Feature Combination for Measuring Textual Similarity—0
Clarify When Necessary: Resolving Ambiguity Through Interaction with LMs—0
Classification and Acquisition of Contradictory Event Pairs using Crowdsourcing—0
Classifying the reported ability in clinical mobility descriptions—0
CLATTER: Comprehensive Entailment Reasoning for Hallucination Detection—0
CLEAR: Contrastive Learning for Sentence Representation—0
CLex: A Lexicon for Exploring Color, Concept and Emotion Associations in Language—0
ClusterFormer: Neural Clustering Attention for Efficient and Effective Transformer—0
Clustering Examples in Multi-Dataset Benchmarks with Item Response Theory—0
Collaboration is all you need: LLM Assisted Safe Code Translation—0
Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation—0
Collecting Entailment Data for Pretraining: New Protocols and Negative Results—0
Collective Annotation of Linguistic Resources: Basic Principles and a Formal Model—0
Combining Natural Logic and Shallow Reasoning for Question Answering—0
Combining Textual Entailment and Argumentation Theory for Supporting Online Debates Interactions—0
Combining Word Patterns and Discourse Markers for Paradigmatic Relation Classification—0
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All datasetsSNLIRTEMultiNLIQNLIANLI testWNLILiDiRusRCBTERRaCommitmentBankSciTailFarsTail

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