SOTAVerified

Semantic Parsing

Semantic Parsing is the task of transducing natural language utterances into formal meaning representations. The target meaning representations can be defined according to a wide variety of formalisms. This include linguistically-motivated semantic representations that are designed to capture the meaning of any sentence such as λ-calculus or the abstract meaning representations. Alternatively, for more task-driven approaches to Semantic Parsing, it is common for meaning representations to represent executable programs such as SQL queries, robotic commands, smart phone instructions, and even general-purpose programming languages like Python and Java.

Source: Tranx: A Transition-based Neural Abstract Syntax Parser for Semantic Parsing and Code Generation

Papers

Showing 51100 of 1202 papers

TitleStatusHype
UniRPG: Unified Discrete Reasoning over Table and Text as Program GenerationCode1
Text-to-Text Extraction and Verbalization of Biomedical Event GraphsCode1
OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question AnsweringCode1
BenchCLAMP: A Benchmark for Evaluating Language Models on Syntactic and Semantic ParsingCode1
Prompt Injection: Parameterization of Fixed InputsCode1
GraphQ IR: Unifying the Semantic Parsing of Graph Query Languages with One Intermediate RepresentationCode1
LAGr: Label Aligned Graphs for Better Systematic Generalization in Semantic ParsingCode1
RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQLCode1
Modern Baselines for SPARQL Semantic ParsingCode1
A Survey on Non-Autoregressive Generation for Neural Machine Translation and BeyondCode1
ArcaneQA: Dynamic Program Induction and Contextualized Encoding for Knowledge Base Question AnsweringCode1
pNLP-Mixer: an Efficient all-MLP Architecture for LanguageCode1
Improving Compositional Generalization with Latent Structure and Data AugmentationCode1
Systematic Generalization with Edge TransformersCode1
Contextual Semantic Parsing for Multilingual Task-Oriented DialoguesCode1
SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQLCode1
LAGr: Labeling Aligned Graphs for Improving Systematic Generalization in Semantic ParsingCode1
Program Transfer for Answering Complex Questions over Knowledge BasesCode1
DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language ModelsCode1
A Graph-Based Neural Model for End-to-End Frame Semantic ParsingCode1
PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language ModelsCode1
ReasonBERT: Pre-trained to Reason with Distant SupervisionCode1
Complex Knowledge Base Question Answering: A SurveyCode1
Focusing on Persons: Colorizing Old Images Learning from Modern Historical MoviesCode1
Compositional Generalization in Multilingual Semantic Parsing over WikidataCode1
Lexicon Learning for Few Shot Sequence ModelingCode1
Code Generation from Natural Language with Less Prior Knowledge and More Monolingual DataCode1
CogIE: An Information Extraction Toolkit for Bridging Texts and CogNetCode1
TAPEX: Table Pre-training via Learning a Neural SQL ExecutorCode1
AIT-QA: Question Answering Dataset over Complex Tables in the Airline IndustryCode1
Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange DataCode1
Lexicon Learning for Few-Shot Neural Sequence ModelingCode1
Structured Reordering for Modeling Latent Alignments in Sequence TransductionCode1
Syntax-augmented Multilingual BERT for Cross-lingual TransferCode1
Abstract Meaning Representation Guided Graph Encoding and Decoding for Joint Information ExtractionCode1
One SPRING to Rule Them Both: Symmetric AMR Semantic Parsing and Generation without a Complex PipelineCode1
Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic ReasoningCode1
Towards General Natural Language Understanding with Probabilistic WorldbuildingCode1
Constrained Language Models Yield Few-Shot Semantic ParsersCode1
Unlocking Compositional Generalization in Pre-trained Models Using Intermediate RepresentationsCode1
Zero-Shot Cross-lingual Semantic ParsingCode1
Learning Semantic Person Image Generation by Region-Adaptive NormalizationCode1
Learning to Synthesize Data for Semantic ParsingCode1
Learning from Executions for Semantic ParsingCode1
3D-to-2D Distillation for Indoor Scene ParsingCode1
Conversational Question Answering over Knowledge Graphs with Transformer and Graph Attention NetworksCode1
FeTaQA: Free-form Table Question AnsweringCode1
Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic ParsingCode1
Few-Shot Semantic Parsing for New PredicatesCode1
Teach me how to Label: Labeling Functions from Natural Language with Text-to-text TransformersCode1
Show:102550
← PrevPage 2 of 25Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ARTEMIS-DAAccuracy (Test)80.8Unverified
2SynTQA (Oracle)Test Accuracy77.5Unverified
3TabLaPAccuracy (Test)76.6Unverified
4SynTQA (GPT)Accuracy (Test)74.4Unverified
5Mix SCAccuracy (Test)73.6Unverified
6SynTQA (RF)Accuracy (Test)71.6Unverified
7CABINETAccuracy (Test)69.1Unverified
8NormTab+TabSQLifyAccuracy (Test)68.63Unverified
9Chain-of-TableAccuracy (Test)67.31Unverified
10Tab-PoTAccuracy (Test)66.78Unverified
#ModelMetricClaimedVerifiedStatus
1RESDSQL-3B + NatSQLAccuracy84.1Unverified
2code-davinci-002 175B (LEVER)Accuracy81.9Unverified
3RASAT+PICARDAccuracy75.5Unverified
4Graphix-3B + PICARDAccuracy74Unverified
5T5-3B + PICARDAccuracy71.9Unverified
6SADGA + GAPAccuracy70.1Unverified
7RATSQL + GAPAccuracy69.7Unverified
8RATSQL + Grammar-Augmented Pre-TrainingAccuracy69.6Unverified
9RATSQL + BERTAccuracy65.6Unverified
10Exact Set MatchingAccuracy19.7Unverified
#ModelMetricClaimedVerifiedStatus
1Dynamic Least-to-Most PromptingExact Match95Unverified
2LeARExact Match90.9Unverified
3T5-3B w/ Intermediate RepresentationsExact Match83.8Unverified
4Hierarchical Poset DecodingExact Match69Unverified
5Universal TransformerExact Match18.9Unverified
#ModelMetricClaimedVerifiedStatus
1ReaRevAccuracy76.4Unverified
2NSM+hAccuracy74.3Unverified
3CBR-KBQAAccuracy70Unverified
4STAGG (Yih et al., 2016)Accuracy63.9Unverified
5T5-11B (Raffel et al., 2020)Accuracy56.5Unverified
#ModelMetricClaimedVerifiedStatus
1CABINETDenotation accuracy (test)89.5Unverified
2TAPEX-Large (weak supervision)Denotation accuracy (test)89.5Unverified
3ReasTAP-Large (weak supervision)Denotation accuracy (test)89.2Unverified
4NL2SQL-BERTAccuracy89Unverified
5TAPAS-Large (weak supervision)Denotation accuracy (test)83.6Unverified
#ModelMetricClaimedVerifiedStatus
1PhraseTransformerAccuracy90.4Unverified
2TranxAccuracy86.2Unverified
3ASN (Rabinovich et al., 2017)Accuracy85.3Unverified
4ZH15 (Zhao and Huang, 2015)Accuracy84.2Unverified
#ModelMetricClaimedVerifiedStatus
1coarse2fineAccuracy88.2Unverified
2PhraseTransformerAccuracy87.9Unverified
3TranxAccuracy87.7Unverified
#ModelMetricClaimedVerifiedStatus
1PERIN + RobeCzechF192.36Unverified
2PERINF192.24Unverified
3HUJI-KUF158Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF180.52Unverified
2HUJI-KUF145Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF180.23Unverified
2HUJI-KUF152Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF194.16Unverified
2HUJI-KUF163Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF189.83Unverified
2HUJI-KUF162Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF192.73Unverified
2HUJI-KUF180Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF189.19Unverified
2HUJI-KUF154Unverified
#ModelMetricClaimedVerifiedStatus
1TAPEX-LargeDenotation Accuracy74.5Unverified
2TAPAS-LargeAccuracy67.2Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF176.4Unverified
2HUJI-KUF173Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF181.01Unverified
2HUJI-KUF175Unverified
#ModelMetricClaimedVerifiedStatus
1HSPEM66.18Unverified
#ModelMetricClaimedVerifiedStatus
1ReasonBERTRF1 Score41.3Unverified
#ModelMetricClaimedVerifiedStatus
1MeMCEExact40.3Unverified