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 751–800 of 1961 papers

TitleStatusHype
Feature-Rich Two-Stage Logistic Regression for Monolingual Alignment—0
Embedding WordNet Knowledge for Textual Entailment—0
Less for More: Enhanced Feedback-aligned Mixed LLMs for Molecule Caption Generation and Fine-Grained NLI Evaluation—0
Feedforward Legendre Memory Unit—0
BUAP: N-gram based Feature Evaluation for the Cross-Lingual Textual Entailment Task—0
Few-Shot Intent Classification by Gauging Entailment Relationship Between Utterance and Semantic Label—0
Annotation and Analysis of Discourse Relations, Temporal Relations and Multi-Layered Situational Relations in Japanese Texts—0
Few-Shot Learning with Siamese Networks and Label Tuning—0
How well do NLI models capture verb veridicality?—0
Few-Shot Natural Language Inference Generation with PDD: Prompt and Dynamic Demonstration—0
Compare, Compress and Propagate: Enhancing Neural Architectures with Alignment Factorization for Natural Language Inference—0
A Sequential Neural Encoder with Latent Structured Description for Modeling Sentences—0
Comparing Hallucination Detection Metrics for Multilingual Generation—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
Eliminating Reasoning via Inferring with Planning: A New Framework to Guide LLMs' Non-linear Thinking—0
Element-wise Bilinear Interaction for Sentence Matching—0
Comparing two acquisition systems for automatically building an English---Croatian parallel corpus from multilingual websites—0
Comparison and Combination of Sentence Embeddings Derived from Different Supervision Signals—0
Fine-grained Semantic Textual Similarity for Serbian—0
Fine-tune BERT with Sparse Self-Attention Mechanism—0
BUAP: Lexical and Semantic Similarity for Cross-lingual Textual Entailment—0
First steps towards a Predicate Matrix—0
First Train to Generate, then Generate to Train: UnitedSynT5 for Few-Shot NLI—0
EHU-ALM: Similarity-Feature Based Approach for Student Response Analysis—0
Efficient Tree-based Approximation for Entailment Graph Learning—0
Compositional Distributional Semantics Models in Chunk-based Smoothed Tree Kernels—0
BUAP: Evaluating Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment—0
Annotating the Focus of Negation in Japanese Text—0
Efficient Search for Transformation-based Inference—0
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasks—0
Focused Entailment Graphs for Open IE Propositions—0
Bridging Knowledge Gaps in Neural Entailment via Symbolic Models—0
Efficient Logical Inference for Semantic Processing—0
FrameNet+: Fast Paraphrastic Tripling of FrameNet—0
Framework for Weakly Supervised Causal Knowledge Extraction from Text—0
Assessing Language Comprehension in Large Language Models Using Construction Grammar—0
Bridging Fairness and Environmental Sustainability in Natural Language Processing—0
Annotating Relation Inference in Context via Question Answering—0
Efficiency in Ambiguity: Two Models of Probabilistic Semantics for Natural Language—0
A Hybrid System to apply Natural Language Inference over Dependency Trees—0
Assessing Out-of-Domain Language Model Performance from Few Examples—0
Compressing Sentence Representation with maximum Coding Rate Reduction—0
From Superficial Patterns to Semantic Understanding: Fine-Tuning Language Models on Contrast Sets—0
From Test-Taking to Test-Making: Examining LLM Authoring of Commonsense Assessment Items—0
Concept Extensions as the Basis for Vector-Space Semantics: Combining Distributional and Ontological Information about Entities—0
From Textual Entailment to Knowledgeable Machines—0
Fusion of Compositional Network-based and Lexical Function Distributional Semantic Models—0
Academic Case Reports Lack Diversity: Assessing the Presence and Diversity of Sociodemographic and Behavioral Factors related to Post COVID-19 Condition—0
Effective Context Selection in LLM-based Leaderboard Generation: An Empirical Study—0
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All datasetsSNLIRTEMultiNLIQNLIANLI testWNLILiDiRusRCBTERRaCommitmentBankSciTailFarsTail

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UnitedSynT5 (3B)% Test Accuracy94.7—Unverified
2UnitedSynT5 (335M)% Test Accuracy93.5—Unverified
3Neural Tree Indexers for Text Understanding% Test Accuracy93.1—Unverified
4EFL (Entailment as Few-shot Learner) + RoBERTa-large% 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 11B (fine-tuned)Accuracy92.5—Unverified
9T5-XXL 11BAccuracy92.5—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
8Adv-RoBERTa ensembleMatched91.1—Unverified
9DeBERTa (large)Matched91.1—Unverified
10SMARTRoBERTaDev Matched91.1—Unverified