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 1251–1300 of 1961 papers

TitleStatusHype
An Empirical Evaluation of various Deep Learning Architectures for Bi-Sequence Classification Tasks—0
An Empirical Study on End-to-End Sentence Modelling—0
An End-to-End Multi-task Learning Model for Fact Checking—0
A Neural Architecture Mimicking Humans End-to-End for Natural Language Inference—0
A New Dataset for Natural Language Inference from Code-mixed Conversations—0
An Exploration of Discourse-Based Sentence Spaces for Compositional Distributional Semantics—0
An Exploration of Dropout with RNNs for Natural Language Inference—0
中英文的文字蘊涵與閱讀測驗的初步探索 (An Exploration of Textual Entailment and Reading Comprehension for Chinese and English) [In Chinese]—0
An in-depth look at Euclidean disk embeddings for structure preserving parsing—0
ANLIzing the Adversarial Natural Language Inference Dataset—0
Annotating by Proving using SemAnTE—0
Annotating Entailment Relations for Shortanswer Questions—0
Annotating Factive Verbs—0
Annotating Relation Inference in Context via Question Answering—0
Annotating the Focus of Negation in Japanese Text—0
Annotation and Analysis of Discourse Relations, Temporal Relations and Multi-Layered Situational Relations in Japanese Texts—0
Annotation Artifacts in Natural Language Inference Data—0
An Optimal Quadratic Approach to Monolingual Paraphrase Alignment—0
A Note on Argumentative Topology: Circularity and Syllogisms as Unsolved Problems—0
An overview of Natural Language Inference Data Collection: The way forward?—0
An Overview Of Temporal Commonsense Reasoning and Acquisition—0
Answer Extraction for Why Arabic Questions Answering Systems: EWAQ—0
Answering Science Exam Questions Using Query Rewriting with Background Knowledge—0
Answering Science Exam Questions Using Query Reformulation with Background Knowledge—0
Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction—0
Answer Ranking for Product-Related Questions via Multiple Semantic Relations Modeling—0
Anti-Asian Hate Speech Detection via Data Augmented Semantic Relation Inference—0
ANU-CSIRO at MEDIQA 2019: Question Answering Using Deep Contextual Knowledge—0
Applying Deep Neural Network to Retrieve Relevant Civil Law Articles—0
APR: Architectural Pattern Recommender—0
A Probabilistic Lexical Model for Ranking Textual Inferences—0
Arabic Textual Entailment with Word Embeddings—0
ARAG: Agentic Retrieval Augmented Generation for Personalized Recommendation—0
ARC-NLP at PAN 2023: Transition-Focused Natural Language Inference for Writing Style Detection—0
A review corpus annotated for negation, speculation and their scope—0
Argument Novelty and Validity Assessment via Multitask and Transfer Learning—0
Argument structure of adverbial derivatives in Russian—0
ARS\_NITK at MEDIQA 2019:Analysing Various Methods for Natural Language Inference, Recognising Question Entailment and Medical Question Answering System—0
ASAP: Automatic Semantic Alignment for Phrases—0
ASAP-II: From the Alignment of Phrases to Textual Similarity—0
A Search Task Dataset for German Textual Entailment—0
A Semantically Enhanced Approach to Determine Textual Similarity—0
A Sequential Neural Encoder with Latent Structured Description for Modeling Sentences—0
A SICK cure for the evaluation of compositional distributional semantic models—0
A Simple Three-Step Approach for the Automatic Detection of Exaggerated Statements in Health Science News—0
ASOBEK at SemEval-2016 Task 1: Sentence Representation with Character N-gram Embeddings for Semantic Textual Similarity—0
Aspectuality Across Genre: A Distributional Semantics Approach—0
Assessing Language Comprehension in Large Language Models Using Construction Grammar—0
Assessing Out-of-Domain Language Model Performance from Few Examples—0
Assessing the Comparability of News Texts—0
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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