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Type-Constrained Code Generation with Language Models
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-62688-3_47openalex-snapshot
Inhabitation in typed lambda-calculi (a syntactic approach)
inferredcites →https://doi.org/10.1007/978-3-662-44202-9_11openalex-snapshot
Understanding TypeScript
inferredcites →https://doi.org/10.1007/s10664-025-10614-4openalex-snapshot
Bugs in large language models generated code: an empirical study
inferredcites →https://doi.org/10.1016/b978-0-444-88074-1.50013-5openalex-snapshot
Type Systems for Programming Languages
inferredcites →https://doi.org/10.1017/s0956796804005131openalex-snapshot
FUNCTIONAL PEARL Linear lambda calculus and PTIME-completeness
inferredcites →https://doi.org/10.1109/icpc66645.2025.00058openalex-snapshot
Enhancing Code Generation for Low-Resource Languages: No Silver Bullet
inferredcites →https://doi.org/10.1109/icse.2017.75openalex-snapshot
To Type or Not to Type: Quantifying Detectable Bugs in JavaScript
inferredcites →https://doi.org/10.1109/icse55347.2025.00022openalex-snapshot
RustAssistant: Using LLMs to Fix Compilation Errors in Rust Code
inferredcites →https://doi.org/10.1109/sp46214.2022.9833571openalex-snapshot
Asleep at the Keyboard? Assessing the Security of GitHub Copilot’s Code Contributions
inferredcites →https://doi.org/10.1109/tse.2023.3267446openalex-snapshot
MultiPL-E: A Scalable and Polyglot Approach to Benchmarking Neural Code Generation
inferredcites →https://doi.org/10.1145/2254064.2254098openalex-snapshot
Type-directed completion of partial expressions
inferredcites →https://doi.org/10.1145/2491956.2462192openalex-snapshot
Complete completion using types and weights
inferredcites →https://doi.org/10.1145/3591278openalex-snapshot
Leveraging Rust Types for Program Synthesis
inferredcites →https://doi.org/10.1145/3591300openalex-snapshot
Prompting Is Programming: A Query Language for Large Language Models
inferredcites →https://doi.org/10.1145/3597503.3639226openalex-snapshot
Lost in Translation: A Study of Bugs Introduced by Large Language Models while Translating Code
inferredcites →https://doi.org/10.1145/3611643.3616271openalex-snapshot
Copiloting the Copilots: Fusing Large Language Models with Completion Engines for Automated Program Repair
inferredcites →https://doi.org/10.1145/3689728openalex-snapshot
Statically Contextualizing Large Language Models with Typed Holes
inferredcites →https://doi.org/10.1145/3703155openalex-snapshot
A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions
inferredcites →https://doi.org/10.1145/3714461openalex-snapshot
Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models
inferredcites →https://doi.org/10.1145/3747588openalex-snapshot
A Survey on Large Language Models for Code Generation
inferredcites →https://doi.org/10.1145/3770084openalex-snapshot
A Survey on LLM-based Code Generation for Low-Resource and Domain-Specific Programming Languages
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-main.576openalex-snapshot
On the Ability and Limitations of Transformers to Recognize Formal Languages
inferredcites →https://doi.org/10.18653/v1/2020.findings-emnlp.384openalex-snapshot
How Can Self-Attention Networks Recognize Dyck-n Languages?
inferredcites →https://doi.org/10.3233/faia240968openalex-snapshot
CoTran: An LLM-Based Code Translator Using Reinforcement Learning with Feedback from Compiler and Symbolic Execution
inferredcites →https://doi.org/10.4230/oasics.icpec.2025.4openalex-snapshot
Can Open Large Language Models Catch Vulnerabilities?
inferredcites →https://doi.org/10.48550/arxiv.2307.09702openalex-snapshot
Efficient Guided Generation for Large Language Models
inferredcites →https://doi.org/10.48550/arxiv.2308.12950openalex-snapshot
Code Llama: Open Foundation Models for Code
inferredcites →https://doi.org/10.48550/arxiv.2309.05922openalex-snapshot
A Survey of Hallucination in Large Foundation Models
inferredcites →https://doi.org/10.48550/arxiv.2401.14196openalex-snapshot
DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence
inferredcites →https://doi.org/10.48550/arxiv.2402.19173openalex-snapshot
StarCoder 2 and The Stack v2: The Next Generation
inferredcites →https://doi.org/10.48550/arxiv.2405.01466openalex-snapshot
A Systematic Literature Review on Large Language Models for Automated Program Repair
inferredcites →https://doi.org/10.48550/arxiv.2406.04778openalex-snapshot
Compilation Quotient (CQ): A Metric for the Compilation Hardness of Programming Languages
inferredcites →https://doi.org/10.48550/arxiv.2407.02742openalex-snapshot
A Comparative Study of DSL Code Generation: Fine-Tuning vs. Optimized Retrieval Augmentation
inferredcites →https://doi.org/10.48550/arxiv.2407.05040openalex-snapshot
Code Less, Align More: Efficient LLM Fine-tuning for Code Generation with Data Pruning
inferredcites →https://doi.org/10.48550/arxiv.2407.06153openalex-snapshot
What's Wrong with Your Code Generated by Large Language Models? An Extensive Study
inferredcites →https://doi.org/10.48550/arxiv.2411.15100openalex-snapshot
XGrammar: Flexible and Efficient Structured Generation Engine for Large Language Models
inferredcites →https://doi.org/10.48550/arxiv.2412.14234openalex-snapshot
Syzygy: Dual Code-Test C to (safe) Rust Translation using LLMs and Dynamic Analysis
inferredcites →https://doi.org/10.5281/zenodo.15050214openalex-snapshot
eth-sri/type-aware-constrained-decoding: Reproduction Package for PLDI Submission
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-032-08620-4_13openalex-snapshot
Prompt-Guided Evaluation of GPT-4o, Gemini and DeepSeek on UML-to-Java Code Generation
inferred← citeshttps://doi.org/10.1007/s10586-026-05947-8openalex-snapshot
Bridging the paradigm debate: automating functional and procedural paradigm translation with lightweight open-source LLMs
inferred← citeshttps://doi.org/10.1016/j.eswa.2026.132389openalex-snapshot
Knowledge-enhanced graph reasoning for packaging design with engineering constraint validation
inferred← citeshttps://doi.org/10.1109/ase63991.2025.00344openalex-snapshot
Multiple Schema-Conformant Declarative Code Generation
inferred← citeshttps://doi.org/10.1145/3744916.3787779openalex-snapshot
Distance-Guided Search in Program Synthesis with Imperfect LLM Solutions
inferred← citeshttps://doi.org/10.1145/3759425.3763383openalex-snapshot
Programming Language Techniques for Bridging LLM Code Generation Semantic Gaps
inferred← citeshttps://doi.org/10.1145/3759425.3763390openalex-snapshot
Position: Vibe Coding Needs Vibe Reasoning: Improving Vibe Coding with Formal Verification
inferred← citeshttps://doi.org/10.1145/3803437.3804873openalex-snapshot
From Syntactic Mimicry to Semantic Correctness: Behavioral Understanding in LLM Code Generation
inferred← citeshttps://doi.org/10.1145/3803437.3805571openalex-snapshot
Projectional Decoding: Towards Semantic-Aware LLM Generation
inferred← citeshttps://doi.org/10.1145/3808270openalex-snapshot
&inator: Correct, Precise C-to-Rust Interface Translation
inferred← citeshttps://doi.org/10.1145/3832783.3834419openalex-snapshot
SwiftGram: Dynamic Lexical Forking for Precise and Efficient Grammar-Constrained Decoding
inferred← citeshttps://doi.org/10.1145/3837062.3839354openalex-snapshot
Formally-Verified Training and Runtime Validation for Small Language Models Using Relational Specifications
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