Papers Code Generation
“Code Generation” 태그가 달린 논문 3,075편 · 필터 해제
Planning to Explore: Curiosity-Driven Planning for LLM Test Generation
The use of LLMs for code generation has naturally extended to code testing and evaluation. As codebases grow in size and complexity, so does the need for automated test generation. Current approaches for LLM-based test g…
Code GenerationACES: Who Tests the Tests? Leave-One-Out AUC Consistency for Code Generation
Selecting LLM-generated code candidates using LLM-generated tests is challenging because the tests themselves may be incorrect. Existing methods either treat all tests equally or rely on ad-hoc heuristics to filter unrel…
Code GenerationFrom Paper to Program: Externalizing and Diagnosing Knowledge Bottlenecks in AI-Assisted Quantum Many-Body Code Generation
Large language models can write scientific code, but direct paper-to-program translation remains fragile when correctness depends on tacit conventions rather than explicit equations. We frame this as a \textbf{knowledge-…
Code GenerationGraphic-Design-Bench: A Comprehensive Benchmark for Evaluating AI on Graphic Design Tasks
We introduce GraphicDesignBench (GDB), the first comprehensive benchmark suite designed specifically to evaluate AI models on the full breadth of professional graphic design tasks. Unlike existing benchmarks that focus o…
Spatial ReasoningCode GenerationSecPI: Secure Code Generation with Reasoning Models via Security Reasoning Internalization
Reasoning language models (RLMs) are increasingly used in programming. Yet, even state-of-the-art RLMs frequently introduce critical security vulnerabilities in generated code. Prior training-based approaches for secure …
Code GenerationToward Executable Repository-Level Code Generation via Environment Alignment
Large language models (LLMs) have achieved strong performance on code generation, but existing methods still struggle with repository-level code generation under executable validation. Under this evaluation setting, succ…
Code GenerationPersistent Cross-Attempt State Optimization for Repository-Level Code Generation
Large language models (LLMs) have achieved substantial progress in repository-level code generation. However, solving the same repository-level task often requires multiple attempts, while existing methods still optimize…
Code GenerationGBQA: A Game Benchmark for Evaluating LLMs as Quality Assurance Engineers
The autonomous discovery of bugs remains a significant challenge in modern software development. Compared to code generation, the complexity of dynamic runtime environments makes bug discovery considerably harder for lar…
Code GenerationIndustryCode: A Benchmark for Industry Code Generation
Code generation and comprehension by Large Language Models (LLMs) have emerged as core drivers of industrial intelligence and decision optimization, finding widespread application in fields such as finance, automation, a…
Code GenerationPrompt Compression in the Wild: Measuring Latency, Rate Adherence, and Quality for Faster LLM Inference
With the wide adoption of language models for IR -- and specifically RAG systems -- the latency of the underlying LLM becomes a crucial bottleneck, since the long contexts of retrieved passages lead large prompts and the…
Question AnsweringCode GenerationDecision-Theoretic Safety Assessment of Persona-Driven Multi-Agent Systems in O-RAN
Autonomous network management in Open Radio Access Networks requires intelligent decision making across conflicting objectives, yet existing LLM based multi agent systems employ homogeneous strategies and lack systematic…
Code GenerationDecision MakingAutomating Database-Native Function Code Synthesis with LLMs
Database systems incorporate an ever-growing number of functions in their kernels (a.k.a., database native functions) for scenarios like new application support and business migration. This growth causes an urgent demand…
Code GenerationMM-ReCoder: Advancing Chart-to-Code Generation with Reinforcement Learning and Self-Correction
Multimodal Large Language Models (MLLMs) have recently demonstrated promising capabilities in multimodal coding tasks such as chart-to-code generation. However, existing methods primarily rely on supervised fine-tuning (…
Reinforcement LearningCode GenerationAeroTherm-GPT: A Verification-Centered LLM Framework for Thermal Protection System Engineering Workflows
Integrating Large Language Models (LLMs) into hypersonic thermal protection system (TPS) design is bottlenecked by cascading constraint violations when generating executable simulation artifacts. General-purpose LLMs, tr…
Code GenerationApriel-1.5-OpenReasoner: RL Post-Training for General-Purpose and Efficient Reasoning
Building general-purpose reasoning models using reinforcement learning with verifiable rewards (RLVR) across diverse domains has been widely adopted by frontier open-weight models. However, their training recipes and dom…
Reinforcement LearningInstruction FollowingCode GenerationToken-Efficient Multimodal Reasoning via Image Prompt Packaging
Deploying large multimodal language models at scale is constrained by token-based inference costs, yet the cost-performance behavior of visual prompting strategies remains poorly characterized. We introduce Image Prompt …
Multimodal ReasoningSpatial ReasoningCode GenerationFrom Theory to Practice: Code Generation Using LLMs for CAPEC and CWE Frameworks
The increasing complexity and volume of software systems have heightened the importance of identifying and mitigating security vulnerabilities. The existing software vulnerability datasets frequently fall short in provid…
Vulnerability DetectionCode GenerationVoxelCodeBench: Benchmarking 3D World Modeling Through Code Generation
Evaluating code generation models for 3D spatial reasoning requires executing generated code in realistic environments and assessing outputs beyond surface-level correctness. We introduce a platform VoxelCode, for analyz…
Spatial ReasoningCode GenerationAgent psychometrics: Task-level performance prediction in agentic coding benchmarks
As the focus in LLM-based coding shifts from static single-step code generation to multi-step agentic interaction with tools and environments, understanding which tasks will challenge agents and why becomes increasingly …
Code GenerationRevision or Re-Solving? Decomposing Second-Pass Gains in Multi-LLM Pipelines
Multi-LLM revision pipelines, in which a second model reviews and improves a draft produced by a first, are widely assumed to derive their gains from genuine error correction. We question this assumption with a controlle…
Code Generation