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 1201–1250 of 1961 papers

TitleStatusHype
What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning—0
When Does Meaning Backfire? Investigating the Role of AMRs in NLI—0
Where's the meeting that was cancelled? existential implications of transitive verbs—0
Where Was Alexander the Great in 325 BC? Toward Understanding History Text with a World Model—0
"Who can help me?": Knowledge Infused Matching of Support Seekers and Support Providers during COVID-19 on Reddit—0
``Who said it, and Why?'' Provenance for Natural Language Claims—0
Why and How to Pay Different Attention to Phrase Alignments of Different Intensities—0
"Why is this misleading?": Detecting News Headline Hallucinations with Explanations—0
Would you Rather? A New Benchmark for Learning Machine Alignment with Cultural Values and Social Preferences—0
XD: Cross-lingual Knowledge Distillation for Polyglot Sentence Embeddings—0
XInfoTabS: Evaluating Multilingual Tabular Natural Language Inference—0
XLA: A Robust Unsupervised Data Augmentation Framework for Cross-Lingual NLP—0
XLDA: Cross-Lingual Data Augmentation for Natural Language Inference and Question Answering—0
XNLI 2.0: Improving XNLI dataset and performance on Cross Lingual Understanding (XLU)—0
XplaiNLI: Explainable Natural Language Inference through Visual Analytics—0
You Can Do Better! If You Elaborate the Reason When Making Prediction—0
Zero Alignment of Verb Arguments in a Parallel Treebank—0
Zero-shot and Few-shot Learning with Instruction-following LLMs for Claim Matching in Automated Fact-checking—0
Zero-Shot Aspect-Based Sentiment Analysis—0
Zero-shot Entailment of Leaderboards for Empirical AI Research—0
Zero-shot Event Extraction via Transfer Learning: Challenges and Insights—0
Zero-Shot Fact-Checking with Semantic Triples and Knowledge Graphs—0
Zero-shot Relation Classification as Textual Entailment—0
Extracting Context-Rich Entailment Rules from Wikipedia Revision History—0
Extractive NarrativeQA with Heuristic Pre-Training—0
FaBERT: Pre-training BERT on Persian Blogs—0
FactCheck Editor: Multilingual Text Editor with End-to-End fact-checking—0
FacTeR-Check: Semi-automated fact-checking through Semantic Similarity and Natural Language Inference—0
FACTOID: FACtual enTailment fOr hallucInation Detection—0
Factoring Statutory Reasoning as Language Understanding Challenges—0
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback—0
Faithful and Robust LLM-Driven Theorem Proving for NLI Explanations—0
Fake news stance detection using stacked ensemble of classifiers—0
Falsesum: Generating Document-level NLI Examples for Recognizing Factual Inconsistency in Summarization—0
FarFetched: An Entity-centric Approach for Reasoning on Textually Represented Environments—0
FBK: Cross-Lingual Textual Entailment Without Translation—0
FBK-HLT: An Effective System for Paraphrase Identification and Semantic Similarity in Twitter—0
FBK HLT-MT at SemEval-2016 Task 1: Cross-lingual Semantic Similarity Measurement Using Quality Estimation Features and Compositional Bilingual Word Embeddings—0
FBK-TR: SVM for Semantic Relatedeness and Corpus Patterns for RTE—0
FBK-UEdin Participation to the WMT13 Quality Estimation Shared Task—0
Towards Better Few-Shot and Finetuning Performance with Forgetful Causal Language Models—0
Feature-Rich Two-Stage Logistic Regression for Monolingual Alignment—0
Less for More: Enhanced Feedback-aligned Mixed LLMs for Molecule Caption Generation and Fine-Grained NLI Evaluation—0
Feedforward Legendre Memory Unit—0
Few-Shot Intent Classification by Gauging Entailment Relationship Between Utterance and Semantic Label—0
Few-Shot Learning with Siamese Networks and Label Tuning—0
Few-Shot Natural Language Inference Generation with PDD: Prompt and Dynamic Demonstration—0
Filtrage et régularisation pour améliorer la plausibilité des poids d’attention dans la tâche d’inférence en langue naturelle (Filtering and regularization to improve the plausibility of attention weights in NLI)—0
Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test?—0
Fine-grained Semantic Textual Similarity for Serbian—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