{"total":79,"rows":[{"id":"2109.05093","title":"PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models","created":"2021-09-10","cited_by_count":411,"area":null},{"id":"2201.05966","title":"UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models","created":"2022-01-16","cited_by_count":231,"area":null},{"id":"2402.17944","title":"Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey","created":"2024-02-27","cited_by_count":159,"area":null},{"id":"2305.04087","title":"Self-Edit: Fault-Aware Code Editor for Code Generation","created":"2023-05-06","cited_by_count":111,"area":null},{"id":"2212.10481","title":"Execution-Based Evaluation for Open-Domain Code Generation","created":"2022-12-20","cited_by_count":91,"area":null},{"id":"2208.03133","title":"Out of the BLEU: how should we assess quality of the Code Generation models?","created":"2022-08-05","cited_by_count":65,"area":null},{"id":"2305.12586","title":"Enhancing Few-shot Text-to-SQL Capabilities of Large Language Models: A Study on Prompt Design Strategies","created":"2023-05-21","cited_by_count":45,"area":null},{"id":"2310.09748","title":"Large Language Model-Aware In-Context Learning for Code Generation","created":"2023-10-15","cited_by_count":43,"area":null},{"id":"2104.05827","title":"Learning to Synthesize Data for Semantic Parsing","created":"2021-04-12","cited_by_count":41,"area":null},{"id":"2203.08388","title":"MCoNaLa: A Benchmark for Code Generation from Multiple Natural Languages","created":"2022-03-16","cited_by_count":41,"area":null},{"id":"2405.02213","title":"Automatic Programming: Large Language Models and Beyond","created":"2024-05-03","cited_by_count":36,"area":null},{"id":"2103.02227","title":"Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-domain Text-to-SQL Parsing","created":"2021-03-03","cited_by_count":33,"area":null},{"id":"2212.13492","title":"MultiSpider: Towards Benchmarking Multilingual Text-to-SQL Semantic Parsing","created":"2022-12-27","cited_by_count":22,"area":null},{"id":"2110.08525","title":"The Power of Prompt Tuning for Low-Resource Semantic Parsing","created":"2021-10-16","cited_by_count":21,"area":null},{"id":"2203.07781","title":"UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQL","created":"2022-03-15","cited_by_count":20,"area":null},{"id":"2101.12087","title":"Learning Structural Edits via Incremental Tree Transformations","created":"2021-01-28","cited_by_count":16,"area":null},{"id":"2104.13100","title":"Shellcode_IA32: A Dataset for Automatic Shellcode Generation","created":"2021-04-27","cited_by_count":16,"area":null},{"id":"2102.01563","title":"On Robustness of Neural Semantic Parsers","created":"2021-02-02","cited_by_count":14,"area":null},{"id":"2104.08041","title":"Cost-effective End-to-end Information Extraction for Semi-structured Document Images","created":"2021-04-16","cited_by_count":14,"area":null},{"id":"2302.01857","title":"KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair","created":"2023-02-03","cited_by_count":13,"area":null},{"id":"2302.13114","title":"Sequential Query Encoding For Complex Query Answering on Knowledge Graphs","created":"2023-02-25","cited_by_count":13,"area":null},{"id":"2210.17040","title":"CodeEditor: Learning to Edit Source Code with Pre-trained Models","created":"2022-10-31","cited_by_count":12,"area":null},{"id":"2208.10091","title":"Incorporating Domain Knowledge through Task Augmentation for Front-End JavaScript Code Generation","created":"2022-08-22","cited_by_count":11,"area":null},{"id":"2105.14796","title":"Improving Tree-Structured Decoder Training for Code Generation via Mutual Learning","created":"2021-05-31","cited_by_count":10,"area":null},{"id":"2106.00261","title":"Exploring Dynamic Selection of Branch Expansion Orders for Code Generation","created":"2021-06-01","cited_by_count":10,"area":null},{"id":"2109.05186","title":"Total Recall: a Customized Continual Learning Method for Neural Semantic Parsers","created":"2021-09-11","cited_by_count":9,"area":null},{"id":"2105.03317","title":"Toward Code Generation: A Survey and Lessons from Semantic Parsing","created":"2021-04-26","cited_by_count":8,"area":null},{"id":"2106.04447","title":"Reading StackOverflow Encourages Cheating: Adding Question Text Improves Extractive Code Generation","created":"2021-06-08","cited_by_count":8,"area":null},{"id":"2101.10708","title":"Few-Shot Semantic Parsing for New Predicates","created":"2021-01-26","cited_by_count":7,"area":null},{"id":"2104.05819","title":"Learning from Executions for Semantic Parsing","created":"2021-04-12","cited_by_count":7,"area":null},{"id":"2211.00818","title":"CodePAD: Sequence-based Code Generation with Pushdown Automaton","created":"2022-11-02","cited_by_count":7,"area":null},{"id":"2310.08759","title":"Question Answering for Electronic Health Records: A Scoping Review of datasets and models","created":"2023-10-12","cited_by_count":7,"area":null},{"id":"2101.00259","title":"Code Generation from Natural Language with Less Prior and More Monolingual Data","created":"2021-01-01","cited_by_count":6,"area":null},{"id":"2202.13972","title":"The impact of lexical and grammatical processing on generating code from natural language","created":"2022-02-28","cited_by_count":6,"area":null},{"id":"2308.04041","title":"InfeRE: Step-by-Step Regex Generation via Chain of Inference","created":"2023-08-08","cited_by_count":5,"area":null},{"id":"2108.05198","title":"Natural Language-Guided Programming","created":"2021-08-11","cited_by_count":4,"area":null},{"id":"2205.01293","title":"A Survey of Deep Learning Models for Structural Code Understanding","created":"2022-05-03","cited_by_count":4,"area":null},{"id":"2208.07461","title":"A Library for Representing Python Programs as Graphs for Machine Learning","created":"2022-08-15","cited_by_count":4,"area":null},{"id":"2410.03234","title":"Showing LLM-Generated Code Selectively Based on Confidence of LLMs","created":"2024-10-04","cited_by_count":4,"area":null},{"id":"2202.04847","title":"A Survey on Artificial Intelligence for Source Code: A Dialogue Systems Perspective","created":"2022-02-10","cited_by_count":3,"area":null},{"id":"2206.13354","title":"Transformer with Tree-order Encoding for Neural Program Generation","created":"2022-05-30","cited_by_count":3,"area":null},{"id":"2302.07845","title":"NL2CMD: An Updated Workflow for Natural Language to Bash Commands Translation","created":"2023-02-15","cited_by_count":3,"area":null},{"id":"2401.10716","title":"Structured Code Representations Enable Data-Efficient Adaptation of Code Language Models","created":"2024-01-19","cited_by_count":3,"area":null},{"id":"2503.13342","title":"Valid Text-to-SQL Generation with Unification-based DeepStochLog","created":"2025-03-17","cited_by_count":3,"area":null},{"id":"2106.03376","title":"A Globally Normalized Neural Model for Semantic Parsing","created":"2021-06-07","cited_by_count":2,"area":null},{"id":"2109.13066","title":"Prefix-to-SQL: Text-to-SQL Generation from Incomplete User Questions","created":"2021-09-15","cited_by_count":2,"area":null},{"id":"2203.15319","title":"Can NMT Understand Me? Towards Perturbation-based Evaluation of NMT Models for Code Generation","created":"2022-03-29","cited_by_count":2,"area":null},{"id":"2209.01566","title":"Towards Top-Down Automated Development in Limited Scopes: A Neuro-Symbolic Framework from Expressibles to Executables","created":"2022-09-04","cited_by_count":2,"area":null},{"id":"2305.19974","title":"Correcting Semantic Parses with Natural Language through Dynamic Schema Encoding","created":"2023-05-31","cited_by_count":2,"area":null},{"id":"2307.03130","title":"VisKoP: Visual Knowledge oriented Programming for Interactive Knowledge Base Question Answering","created":"2023-07-06","cited_by_count":2,"area":null},{"id":"2309.10506","title":"Enhancing Open-Domain Table Question Answering via Syntax- and Structure-aware Dense Retrieval","created":"2023-09-19","cited_by_count":2,"area":null},{"id":"2310.18662","title":"ASTormer: An AST Structure-aware Transformer Decoder for Text-to-SQL","created":"2023-10-28","cited_by_count":2,"area":null},{"id":"2407.10626","title":"NoviCode: Generating Programs from Natural Language Utterances by Novices","created":"2024-07-15","cited_by_count":2,"area":null},{"id":"2502.12490","title":"UniGenCoder: Merging Seq2Seq and Seq2Tree Paradigms for Unified Code Generation","created":"2025-02-18","cited_by_count":2,"area":null},{"id":"2106.04559","title":"Turing: an Accurate and Interpretable Multi-Hypothesis Cross-Domain Natural Language Database Interface","created":"2021-06-08","cited_by_count":1,"area":null},{"id":"2204.13192","title":"Counterfactual Explanations for Natural Language Interfaces","created":"2022-04-27","cited_by_count":1,"area":null},{"id":"2211.04569","title":"Toward a Neural Semantic Parsing System for EHR Question Answering","created":"2022-11-08","cited_by_count":1,"area":null},{"id":"2211.07842","title":"Evaluating How Fine-tuning on Bimodal Data Effects Code Generation","created":"2022-11-15","cited_by_count":1,"area":null},{"id":"2305.06655","title":"QURG: Question Rewriting Guided Context-Dependent Text-to-SQL Semantic Parsing","created":"2023-05-11","cited_by_count":1,"area":null},{"id":"2401.06772","title":"Semantic Parsing for Question Answering over Knowledge Graphs","created":"2023-12-01","cited_by_count":1,"area":null},{"id":"2410.00414","title":"Semantic Parsing with Candidate Expressions for Knowledge Base Question Answering","created":"2024-10-01","cited_by_count":1,"area":null},{"id":"2111.00580","title":"Text Classification for Task-based Source Code Related Questions","created":"2021-10-31","cited_by_count":0,"area":null},{"id":"2112.13179","title":"Combining Improvements for Exploiting Dependency Trees in Neural Semantic Parsing","created":"2021-12-25","cited_by_count":0,"area":null},{"id":"2202.00367","title":"Natural Language to Code Using Transformers","created":"2022-02-01","cited_by_count":0,"area":null},{"id":"2202.03755","title":"Can We Generate Shellcodes via Natural Language? An Empirical Study","created":"2022-02-08","cited_by_count":0,"area":null},{"id":"2203.10744","title":"Programming Language Agnostic Mining of Code and Language Pairs with Sequence Labeling Based Question Answering","created":"2022-03-21","cited_by_count":0,"area":null},{"id":"2204.12186","title":"Faster and Better Grammar-based Text-to-SQL Parsing via Clause-level Parallel Decoding and Alignment Loss","created":"2022-04-26","cited_by_count":0,"area":null},{"id":"2208.09998","title":"Antecedent Predictions Are More Important Than You Think: An Effective Method for Tree-Based Code Generation","created":"2022-08-22","cited_by_count":0,"area":null},{"id":"2303.03540","title":"Judging Adam: Studying the Performance of Optimization Methods on ML4SE Tasks","created":"2023-03-06","cited_by_count":0,"area":null},{"id":"2403.11585","title":"Linguacodus: A Synergistic Framework for Transformative Code Generation in Machine Learning Pipelines","created":"2024-03-18","cited_by_count":0,"area":null},{"id":"2411.18923","title":"EzSQL: An SQL intermediate representation for improving SQL-to-text Generation","created":"2024-11-28","cited_by_count":0,"area":null},{"id":"2504.05759","title":"RETROcode: Leveraging a Code Database for Improved Natural Language to Code Generation","created":"2025-04-08","cited_by_count":0,"area":null},{"id":"2603.22519","title":"LLMON: An LLM-native Markup Language to Leverage Structure and Semantics at the LLM Interface","created":"2026-03-23","cited_by_count":0,"area":null},{"id":"2604.09952","title":"SLM Finetuning for Natural Language to Domain Specific Code Generation in Production","created":"2026-04-10","cited_by_count":0,"area":null},{"id":"2605.14117","title":"Generative Floor Plan Design with LLMs via Reinforcement Learning with Verifiable Rewards","created":"2026-05-13","cited_by_count":0,"area":null},{"id":"2608.18409","title":"Improving Natural-Language Combinatorial-Optimization Accuracy in Resource-Constrained Language Models via Formal Abstractions","created":"2026-08-19","cited_by_count":0,"area":null},{"id":"2608.26172","title":"DRL: A Deterministic Relational Middleware Layer for Transaction-Safe Enterprise NL2SQL Under Schema-Graph Scaling","created":"2026-07-23","cited_by_count":0,"area":null},{"id":"2609.33670","title":"Closing the Cross-Dialect Gap: Query Plans as a Portable Interface in Text-to-SQL","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2610.10760","title":"DOGS: Design-Space Sampling for Prompt-Driven Logo Generation","created":"2026-10-07","cited_by_count":0,"area":null}],"next_cursor":null}