https://github.com/juruomp/rat-sql-tc
공식 코드Pay More Attention to History: A Context Modelling Strategy for Conversational Text-to-SQL
Papers with Code 아카이브
Semantic Parsing
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 7
- 평가표
- 20
- 보존된 평가 기록
- 78
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/jvoas655/AViD-SP
공식 코드https://github.com/jvoas655/VG-SPICE
공식 코드https://github.com/jychen9811/doc-vton
공식 코드OccluMix: Towards De-Occlusion Virtual Try-on by Semantically-Guided Mixup
https://github.com/jzbjyb/omnitab
공식 코드OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answering
https://github.com/kakaoenterprise/RYANSQL
공식 코드https://github.com/karthikradhakrishnan96/ColloQL
공식 코드ColloQL: Robust Cross-Domain Text-to-SQL Over Search Queries
https://github.com/katherinewu312/lp-lm
공식 코드LP-LM: No Hallucinations in Question Answering with Logic Programming
https://github.com/kelvinguu/lang2program
공식 코드From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood
https://github.com/kepengxu/pgtformer
공식 코드Beyond Alignment: Blind Video Face Restoration via Parsing-Guided Temporal-Coherent Transformer
https://github.com/klee972/exec-filter
공식 코드Weakly Supervised Semantic Parsing with Execution-based Spurious Program Filtering
https://github.com/laqcce-cao/rsl-sql
공식 코드https://github.com/lastdance500/neural-symbolic-parsing
공식 코드Neural Semantic Parsing with Extremely Rich Symbolic Meaning Representations
https://github.com/layer6ai-labs/msc-sql
공식 코드MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translation
https://github.com/leuchine/self_play_picard
공식 코드https://github.com/lhrlab/chatkbqa
공식 코드https://github.com/libinnlp/hosdp
공식 코드https://github.com/lil-lab/spf
공식 코드https://github.com/litterbrother-xiao/overview-of-non-autoregressive-applications
공식 코드A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond
https://github.com/liuzhengzhe/3D-to-2D-Distillation-for-Indoor-Scene-Parsing
공식 코드https://github.com/longquanjiang/ontoscprompt
공식 코드Ontology-Guided, Hybrid Prompt Learning for Generalization in Knowledge Graph Question Answering
https://github.com/louchao98/chap_amr_parser
공식 코드https://github.com/lrlbbzl/ptd-sql
공식 코드PTD-SQL: Partitioning and Targeted Drilling with LLMs in Text-to-SQL
https://github.com/ltgoslo/text-graph-generalization
공식 코드https://github.com/lumia-group/rasat
공식 코드RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL
https://github.com/lupantech/InterGPS
공식 코드Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning
https://github.com/lyuqin/HydraNet-WikiSQL
공식 코드https://github.com/magic-yuantian/steps
공식 코드Interactive Text-to-SQL Generation via Editable Step-by-Step Explanations
https://github.com/magnumresearchgroup/bash_gen
공식 코드NL2CMD: An Updated Workflow for Natural Language to Bash Commands Translation
https://github.com/magnumresearchgroup/magnum-nlc2cmd
공식 코드NL2CMD: An Updated Workflow for Natural Language to Bash Commands Translation
https://github.com/mahadi-nahid/tabsqlify
공식 코드TabSQLify: Enhancing Reasoning Capabilities of LLMs Through Table Decomposition
https://github.com/mcandito/aux-tasks-biaffine-graph-parser-findingsacl22
공식 코드Auxiliary Tasks to Boost Biaffine Semantic Dependency Parsing
https://github.com/mcgill-nlp/magnifico
공식 코드https://github.com/mcxiaoxiao/MMSQL
공식 코드Evaluating and Enhancing LLMs for Multi-turn Text-to-SQL with Multiple Question Types
https://github.com/mcxiaoxiao/qda-sql
공식 코드QDA-SQL: Questions Enhanced Dialogue Augmentation for Multi-Turn Text-to-SQL
https://github.com/mdfahimanjum/llm-planning-with-reasoning
공식 코드When Reasoning Beats Scale: A 1.5B Reasoning Model Outranks 13B LLMs as Discriminator
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.