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 901–950 of 1961 papers

TitleStatusHype
Language Clustering for Multilingual Named Entity Recognition—0
Few-Shot Intent Classification by Gauging Entailment Relationship Between Utterance and Semantic Label—0
Q^2: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering—0
Natural Language Inference using Neural Network and Tableau Method—0
Label Verbalization and Entailment for Effective Zero and Few-Shot Relation Extraction—0
Talking with the Theorem Prover to Interactively Solve Natural Language Inference—0
An in-depth look at Euclidean disk embeddings for structure preserving parsing—0
Paraphrasing Compound Nominalizations—0
TabPert : An Effective Platform for Tabular PerturbationCode0
Neural Natural Logic Inference for Interpretable Question AnsweringCode0
FacTeR-Check: Semi-automated fact-checking through Semantic Similarity and Natural Language Inference—0
Text Counterfactuals via Latent Optimization and Shapley-Guided SearchCode0
Learning-based Memetic Algorithm for Hard-label Textual Attack—0
IMPLI: Investigating NLI Models' Performance on Figurative Language—0
Few-Shot Learning with Siamese Networks and Label Tuning—0
FarFetched: An Entity-centric Approach for Reasoning on Textually Represented Environments—0
Unsupervised Natural Language Inference Using PHL Triplet GenerationCode0
DialogueScript: Using Dialogue Agents to Produce a Script—0
Practical Benefits of Feature Feedback Under Distribution Shift—0
Semantically Distributed Robust Optimization for Vision-and-Language InferenceCode0
A Logic-Based Framework for Natural Language Inference in DutchCode0
Analyzing the Effects of Reasoning Types on Cross-Lingual Transfer PerformanceCode0
Probing Language Models for Understanding of Temporal ExpressionsCode0
Curriculum Discovery through an Encompassing Curriculum Learning Framework—0
Logic Pre-Training of Language Models—0
Marked Attribute Bias in Natural Language InferenceCode0
MINIMAL: Mining Models for Data Free Universal Adversarial TriggersCode0
Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan LanguagesCode0
Knowledge-Enhanced Evidence Retrieval for Counterargument GenerationCode0
Weakly Supervised Explainable Phrasal Reasoning with Neural Fuzzy LogicCode0
Language Models as a Knowledge Source for Cognitive Agents—0
General Cross-Architecture Distillation of Pretrained Language Models into Matrix EmbeddingsCode0
Does External Knowledge Help Explainable Natural Language Inference? Automatic Evaluation vs. Human RatingsCode0
Comparing Text Representations: A Theory-Driven ApproachCode0
On the Language-specificity of Multilingual BERT and the Impact of Fine-tuningCode0
Task-adaptive Pre-training and Self-training are Complementary for Natural Language Understanding—0
Graph-based Retrieval for Claim Verification over Cross-Document Evidence—0
How May I Help You? Using Neural Text Simplification to Improve Downstream NLP TasksCode0
Counterfactual Adversarial Learning with Representation InterpolationCode0
Learning with Different Amounts of Annotation: From Zero to Many LabelsCode0
Label Verbalization and Entailment for Effective Zero- and Few-Shot Relation Extraction—0
Cross-Policy Compliance Detection via Question Answering—0
Unsupervised Pre-training with Structured Knowledge for Improving Natural Language Inference—0
Do Prompt-Based Models Really Understand the Meaning of their Prompts?Code0
Siamese Networks for Inference in Malayalam Language Texts—0
Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty EstimationCode0
A Generative Approach for Mitigating Structural Biases in Natural Language InferenceCode0
Prompt-Learning for Fine-Grained Entity Typing—0
Tailor: Generating and Perturbing Text with Semantic Controls—0
LadRa-Net: Locally-Aware Dynamic Re-read Attention Net for Sentence Semantic Matching—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