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
Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language InferenceCode1
Multi-Task Deep Neural Networks for Natural Language UnderstandingCode0
Visual Entailment: A Novel Task for Fine-Grained Image Understanding—0
EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language InferenceCode0
Multi-turn Inference Matching Network for Natural Language InferenceCode0
Learning to Selectively Transfer: Reinforced Transfer Learning for Deep Text Matching—0
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and BeyondCode1
A corpus of precise natural textual entailment problems—0
Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test?—0
Improving Retrieval-Based Question Answering with Deep Inference ModelsCode0
Attention Boosted Sequential Inference Model—0
Parameter Re-Initialization through Cyclical Batch Size Schedules—0
e-SNLI: Natural Language Inference with Natural Language ExplanationsCode1
GLoMo: Unsupervised Learning of Transferable Relational Graphs—0
Non-entailed subsequences as a challenge for natural language inference—0
Visual Entailment Task for Visually-Grounded Language Learning—0
Answering Science Exam Questions Using Query Reformulation with Background Knowledge—0
Combining Fact Extraction and Verification with Neural Semantic Matching NetworksCode0
Analyzing Compositionality-Sensitivity of NLI ModelsCode0
Combining Axiom Injection and Knowledge Base Completion for Efficient Natural Language InferenceCode0
Combining Similarity Features and Deep Representation Learning for Stance Detection in the Context of Checking Fake NewsCode0
Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data TasksCode0
Textual Entailment based Question Generation—0
Neural sentence generation from formal semantics—0
UCL Machine Reading Group: Four Factor Framework For Fact Finding (HexaF)—0
A mostly unlexicalized model for recognizing textual entailment—0
SIRIUS-LTG: An Entity Linking Approach to Fact Extraction and Verification—0
Integrating Entity Linking and Evidence Ranking for Fact Extraction and Verification—0
Zero-shot Relation Classification as Textual Entailment—0
Frame- and Entity-Based Knowledge for Common-Sense Argumentative ReasoningCode0
An End-to-End Multi-task Learning Model for Fact Checking—0
Robust Document Retrieval and Individual Evidence Modeling for Fact Extraction and Verification.Code0
Team SWEEPer: Joint Sentence Extraction and Fact Checking with Pointer Networks—0
Visual Interrogation of Attention-Based Models for Natural Language Inference and Machine Comprehension—0
Dialogue Natural Language Inference—0
Stress-Testing Neural Models of Natural Language Inference with Multiply-Quantified Sentences—0
Simplifying Neural Machine Translation with Addition-Subtraction Twin-Gated Recurrent NetworksCode0
A Simple Recurrent Unit with Reduced Tensor Product RepresentationsCode0
Testing the Generalization Power of Neural Network Models Across NLI Benchmarks—0
Learning Distributed Representations of Symbolic Structure Using Binding and Unbinding Operations—0
On Zero-shot Cross-lingual Transfer of Multilingual Neural Machine Translation—0
An Exploration of Dropout with RNNs for Natural Language Inference—0
BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingCode3
Training Complex Models with Multi-Task Weak SupervisionCode0
Revisiting neural relation classification in clinical notes with external informationCode0
Convolutional Interaction Network for Natural Language Inference—0
InferLite: Simple Universal Sentence Representations from Natural Language Inference Data—0
When data permutations are pathological: the case of neural natural language inferenceCode0
Structured Alignment Networks for Matching Sentences—0
Spot the Odd Man Out: Exploring the Associative Power of Lexical Resources—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