https://github.com/taoshen58/MaSP
공식 코드Multi-Task Learning for Conversational Question Answering over a Large-Scale Knowledge Base
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/taoyds/spider
공식 코드https://github.com/taoyds/syntaxsql
공식 코드SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Task
https://github.com/taoyds/test-suite-sql-eval
공식 코드https://github.com/taoyds/typesql
공식 코드TypeSQL: Knowledge-based Type-Aware Neural Text-to-SQL Generation
https://github.com/tengwang0318/MLPrompt
공식 코드Large Language Models are Good Multi-lingual Learners : When LLMs Meet Cross-lingual Prompts
https://github.com/testzer0/ambiqt
공식 코드Benchmarking and Improving Text-to-SQL Generation under Ambiguity
https://github.com/text-to-sql-survey-coling22/text-to-sql-survey-coling22.github.io
공식 코드Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expect
https://github.com/tfzhou/MG-HumanParsing
공식 코드https://github.com/the-inscrutable-x/tacq
공식 코드Task-Circuit Quantization: Leveraging Knowledge Localization and Interpretability for Compression
https://github.com/thenamek/trustworthy-text2sql
공식 코드https://github.com/thu-bpm/chatgpt-sql
공식 코드A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability
https://github.com/thu-bpm/isesl-sql
공식 코드Semantic Enhanced Text-to-SQL Parsing via Iteratively Learning Schema Linking Graph
https://github.com/thu-keg/programtransfer
공식 코드Program Transfer for Answering Complex Questions over Knowledge Bases
https://github.com/tian14267/ls_mbert
공식 코드Incorporating Lexical and Syntactic Knowledge for Unsupervised Cross-Lingual Transfer
https://github.com/tidbcloud/tiinsight
공식 코드Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models
https://github.com/tomerwolgithub/question-decomposition-to-sql
공식 코드Weakly Supervised Text-to-SQL Parsing through Question Decomposition
https://github.com/tomsherborne/bootstrap
공식 코드https://github.com/tomsherborne/minotaur
공식 코드Optimal Transport Posterior Alignment for Cross-lingual Semantic Parsing
https://github.com/tomsherborne/xgr
공식 코드https://github.com/tomsherborne/zx-parse
공식 코드https://github.com/trais-lab/llm-structured-data
공식 코드Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?
https://github.com/tshu-w/dbcopilot
공식 코드DBCopilot: Natural Language Querying over Massive Databases via Schema Routing
https://github.com/tue-mps/panoptic_parts
공식 코드Cityscapes-Panoptic-Parts and PASCAL-Panoptic-Parts datasets for Scene Understanding
https://github.com/tzshi/squall
공식 코드On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries
https://github.com/u-alberta/nlpworkbench
공식 코드NLP Workbench: Efficient and Extensible Integration of State-of-the-art Text Mining Tools
https://github.com/udiNaveh/nlvr_tau_nlp_final_proj
공식 코드https://github.com/ufal/mrpipe-conll2019
공식 코드ÚFAL MRPipe at MRP 2019: UDPipe Goes Semantic in the Meaning Representation Parsing Shared Task
https://github.com/ufal/perin
공식 코드ÚFAL at MRP 2020: Permutation-invariant Semantic Parsing in PERIN
https://github.com/uiuc-kang-lab/elt-bench
공식 코드ELT-Bench: An End-to-End Benchmark for Evaluating AI Agents on ELT Pipelines
https://github.com/unbiarirang/prompt-injection
공식 코드https://github.com/vacancy/NSCL-PyTorch-Release
공식 코드https://github.com/vamsi995/paraphrase-generator
공식 코드https://github.com/venzino-han/probgate_ehrsql
공식 코드https://github.com/wangchunliu/chinese-sbn-parsing
공식 코드https://github.com/wangchunliu/drs-pretrained-lmm
공식 코드Pre-Trained Language-Meaning Models for Multilingual Parsing and Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.