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Semantic Parsing On Spider

評価指標

Accuracy

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

モデル名
Accuracy
Paper TitleRepository
code-davinci-002 175B (LEVER)81.9LEVER: Learning to Verify Language-to-Code Generation with Execution
T5-3B + PICARD71.9 PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models
RATSQL + BERT65.6RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers
RESDSQL-3B + NatSQL84.1RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL
Exact Set Matching19.7Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task
Graphix-3B + PICARD74.0Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsing
SADGA + GAP70.1SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL
RASAT+PICARD75.5RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL
RATSQL + GAP69.7Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training
RATSQL + Grammar-Augmented Pre-Training69.6GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing
0 of 10 row(s) selected.