Papers with Code 아카이브
Semantic Parsing
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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
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/hkunlp/icl-ceil
공식 코드https://github.com/hkunlp/symgen
공식 코드Generating Data for Symbolic Language with Large Language Models
https://github.com/hkunlp/unifiedskg
공식 코드https://github.com/hkustdial/nl2sql_handbook
공식 코드A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?
https://github.com/hlr/proceduralsemanticparsing
공식 코드The Role of Semantic Parsing in Understanding Procedural Text
https://github.com/hongwin/schema-r1
공식 코드Schema-R1: A reasoning training approach for schema linking in Text-to-SQL Task
https://github.com/hugochan/BAMnet
공식 코드Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases
https://github.com/huybery/r2sql
공식 코드Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing
https://github.com/hwy9855/gsr
공식 코드Less is More: Making Smaller Language Models Competent Subgraph Retrievers for Multi-hop KGQA
https://github.com/hyan5/learning_to_simulate_nl_feedback
공식 코드Learning to Simulate Natural Language Feedback for Interactive Semantic Parsing
https://github.com/ibm/amr-annotations
공식 코드https://github.com/ibm/graph_ensemble_learning
공식 코드https://github.com/ida-szubert/childes_ud2lf
공식 코드Cross-linguistically Consistent Semantic and Syntactic Annotation of Child-directed Speech
https://github.com/imayk/crush4sql
공식 코드CRUSH4SQL: Collective Retrieval Using Schema Hallucination For Text2SQL
https://github.com/imayk/scud4icl
공식 코드https://github.com/inbaroren/improving-compgen-in-semparse
공식 코드https://github.com/inbaroren/scfg-sampling-for-comp-gen
공식 코드https://github.com/interact-erc/geo-aligned
공식 코드https://github.com/interact-erc/tpol
공식 코드Translate First Reorder Later: Leveraging Monotonicity in Semantic Parsing
https://github.com/itayle/diverse-demonstrations
공식 코드Diverse Demonstrations Improve In-context Compositional Generalization
https://github.com/jacobandreas/geca
공식 코드https://github.com/janmbuys/DeepDeepParser
공식 코드https://github.com/jayetri/DrugEHRQA-A-Question-Answering-Dataset-on-Structured-and-Unstructured-Electronic-Health-Records
공식 코드https://github.com/jcyk/AMR-gs
공식 코드https://github.com/jcyk/AMR-parser
공식 코드https://github.com/jcyk/xamr
공식 코드https://github.com/jf87/footballdb
공식 코드Evaluating the Data Model Robustness of Text-to-SQL Systems Based on Real User Queries
https://github.com/jgroschwitz/grapes
공식 코드AMR Parsing is Far from Solved: GrAPES, the Granular AMR Parsing Evaluation Suite
https://github.com/jiangyctarheel/sq-transformer
공식 코드Inducing Systematicity in Transformers by Attending to Structurally Quantized Embeddings
https://github.com/jimxionggm/interactive-kbqa
공식 코드https://github.com/jkkummerfeld/text2sql-data
공식 코드https://github.com/jonathanherzig/semantic-parsing-annotation
공식 코드Don't paraphrase, detect! Rapid and Effective Data Collection for Semantic Parsing
https://github.com/jonathanherzig/span-based-sp
공식 코드Span-based Semantic Parsing for Compositional Generalization
https://github.com/jonathanherzig/zero-shot-semantic-parsing
공식 코드Decoupling Structure and Lexicon for Zero-Shot Semantic Parsing
https://github.com/jrimyak/parse_seq2seq
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.