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 1301–1350 of 1961 papers

TitleStatusHype
A Strong Lexical Matching Method for the Machine Comprehension Test—0
A Study of the Effect of Resolving Negation and Sentiment Analysis in Recognizing Text Entailment for Arabic—0
A Study of the Plausibility of Attention between RNN Encoders in Natural Language Inference—0
A Survey of Adversarial Defences and Robustness in NLP—0
A Survey of Paraphrasing and Textual Entailment Methods—0
A Survey on Recognizing Textual Entailment as an NLP Evaluation—0
Asynchronous Deep Interaction Network for Natural Language Inference—0
A synthetic data approach for domain generalization of NLI models—0
Attention-Based Convolutional Neural Network for Machine Comprehension—0
Attention Boosted Sequential Inference Model—0
Attention Mechanism, Transformers, BERT, and GPT: Tutorial and Survey—0
Attentive Tree-structured Network for Monotonicity Reasoning—0
A Two Level Model for Context Sensitive Inference Rules—0
A Type-Theoretical system for the FraCaS test suite: Grammatical Framework meets Coq—0
Augmenting NLP data to counter Annotation Artifacts for NLI Tasks—0
A Unified Kernel Approach for Learning Typed Sentence Rewritings—0
Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval Augmented Generation—0
PECO: Examining Single Sentence Label Leakage in Natural Language Inference Datasets through Progressive Evaluation of Cluster Outliers—0
Automatic Building and Using Parallel Resources for SMT from Comparable Corpora—0
Automatic Evaluation of Summary Using Textual Entailment—0
Automatic Extraction of Implicit Interpretations from Modal Constructions—0
Automatic Fact-Checking with Document-level Annotations using BERT and Multiple Instance Learning—0
Automatic Identification of Narrative Diegesis and Point of View—0
Automatic Knowledge Acquisition for Case Alternation between the Passive and Active Voices in Japanese—0
Automatic Nominalization of Clauses—0
Automatic Validation of Textual Attribute Values in E-commerce Catalog by Learning with Limited Labeled Data—0
AWE: Asymmetric Word Embedding for Textual Entailment—0
A Wide-Coverage Symbolic Natural Language Inference System—0
A Word-Embedding-based Sense Index for Regular Polysemy Representation—0
AXCEL: Automated eXplainable Consistency Evaluation using LLMs—0
Back to Basics for Monolingual Alignment: Exploiting Word Similarity and Contextual Evidence—0
Bag of Tricks for Effective Language Model Pretraining and Downstream Adaptation: A Case Study on GLUE—0
Bag-of-Vector Embeddings of Dependency Graphs for Semantic Induction—0
BaIT: Barometer for Information Trustworthiness—0
Balanced Adversarial Training: Balancing Tradeoffs Between Oversensitivity and Undersensitivity in NLP Models—0
BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla—0
BASHI: A Corpus of Wall Street Journal Articles Annotated with Bridging Links—0
Bayesian Optimization with LLM-Based Acquisition Functions for Natural Language Preference Elicitation—0
Behavior Analysis of NLI Models: Uncovering the Influence of Three Factors on Robustness—0
Benchmarking Retrieval-Augmented Large Language Models in Biomedical NLP: Application, Robustness, and Self-Awareness—0
BenLLMEval: A Comprehensive Evaluation into the Potentials and Pitfalls of Large Language Models on Bengali NLP—0
BERT-DRE: BERT with Deep Recursive Encoder for Natural Language Sentence Matching—0
BERT-Flow-VAE: A Weakly-supervised Model for Multi-Label Text Classification—0
Beyond English: The Impact of Prompt Translation Strategies across Languages and Tasks in Multilingual LLMs—0
Beyond Keywords: A Context-based Hybrid Approach to Mining Ethical Concern-related App Reviews—0
Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models—0
Bilinear Fusion of Commonsense Knowledge with Attention-Based NLI Models—0
Bilingual Tabular Inference: A Case Study on Indic Languages—0
BioAMA: Towards an End to End BioMedical Question Answering System—0
BIUTEE: A Modular Open-Source System for Recognizing Textual Entailment—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