Papers Code Generation
“Code Generation” 태그가 달린 논문 3,075편 · 필터 해제
CASCADE: Case-Based Continual Adaptation for Large Language Models During Deployment
Large language models (LLMs) have become a central foundation of modern artificial intelligence, yet their lifecycle remains constrained by a rigid separation between training and deployment, after which learning effecti…
Medical DiagnosisCode GenerationFrom Code to Prediction: Fine-Tuning LLMs for Neural Network Performance Classification in NNGPT
Automated Machine Learning (AutoML) frameworks increasingly leverage Large Language Models (LLMs) for tasks such as hyperparameter optimization and neural architecture code generation. However, current LLM-based approach…
Hyperparameter OptimizationImage ClassificationCode GenerationRose-SQL: Role-State Evolution Guided Structured Reasoning for Multi-Turn Text-to-SQL
Recent advances in Large Reasoning Models (LRMs) trained with Long Chain-of-Thought have demonstrated remarkable capabilities in code generation and mathematical reasoning. However, their potential in multi-turn Text-to-…
Mathematical ReasoningCode GenerationMeasuring and Mitigating Bias in Code Generated by Large Language Models
Large language models (LLMs) are widely recognised for their applications in natural language generation and are increasingly used for code generation tasks. However, concerns about bias in their generated outputs remain…
Code GenerationSay the Mission, Execute the Swarm: Agent-Enhanced LLM Reasoning in the Web-of-Drones
Large Language Models (LLMs) are increasingly explored as high-level reasoning engines for cyber-physical systems, yet their application to real-time UAV swarm management remains challenging due to heterogeneous interfac…
Code GenerationContextual Multi-Objective Optimization: Rethinking Objectives in Frontier AI Systems
Frontier AI systems perform best in settings with clear, stable, and verifiable objectives, such as code generation, mathematical reasoning, games, and unit-test-driven tasks. They remain less reliable in open-ended sett…
Mathematical ReasoningCode GenerationEngiAgent: Fully Connected Coordination of LLM Agents for Solving Open-ended Engineering Problems with Feasible Solutions
Engineering problem solving is central to real-world decision-making, requiring mathematical formulations that not only represent complex problems but also produce feasible solutions under data and physical constraints. …
Code GenerationMolViBench: Evaluating LLMs on Molecular Vibe Coding
Molecular Vibe Coding, a paradigm where chemists interact with LLMs to generate executable programs for molecular tasks, has emerged as a flexible alternative to chemical agents with predefined tools, enabling chemists t…
Code GenerationDrug DiscoveryLLM-Assisted Repository-Level Generation with Structured Spec-Driven Engineering
State-of-the-art Large Language Models (LLMs) excel in code generation at the function level. However, the output quality significantly declines when scaling to repository-level systems. Current workflows relying only on…
Code GenerationAI-Generated Smells: An Analysis of Code and Architecture in LLM and Agent-Driven Development
The promise of Large Language Models in automated software engineering is often measured by functional correctness, overlooking the critical issue of long term maintainability. This paper presents a systematic audit of t…
Code GenerationLiberating LLM Capabilities in Full-Duplex Speech Models
Speech-based large language models are typically constrained to spoken replies, which limits their user-facing outputs to what can be verbalized and suppresses text-native capabilities such as code generation, structured…
Code GenerationLearning Correct Behavior from Examples: Validating Sequential Execution in Autonomous Agents
As autonomous agents become increasingly sophisticated, validating their sequential behavior presents a significant challenge. Traditional testing approaches require manual specification, exact sequence matching, or thou…
Code GenerationGA-VisAgent: A Multi-Agent application for code generation and visualization in interactive learning
Geometric Algebra (GA) presents challenges to learners due to its highly abstract mathematical structure and complex operational rules, as translating algebraic manipulations into concrete geometric interpretations is a …
Code GenerationMAD-OPD: Breaking the Ceiling in On-Policy Distillation via Multi-Agent Debate
On-policy distillation (OPD) trains a student on its own trajectories under token-level teacher supervision, but existing methods are capped by a single-teacher capability ceiling: when the teacher errs, the student inhe…
Code GenerationUsing LLMs in Software Design: An Empirical Study of GitHub and A Practitioner Survey
Recent advancements in Large Language Models (LLMs) have demonstrated significant potential across a wide range of software engineering tasks, including software design, an area traditionally regarded as highly dependent…
Code GenerationCode World Model Preparedness Report
This report documents the preparedness assessment of Code World Model (CWM), a model for code generation and reasoning about code from Meta. We conducted pre-release testing across domains identified in our Frontier AI F…
Code GenerationSocial Bias in LLM-Generated Code: Benchmark and Mitigation
Large Language Models (LLMs) are increasingly deployed to generate code for human-centered applications where demographic fairness is critical. However, existing evaluations focus almost exclusively on functional correct…
Code GenerationImproving LLM Code Generation via Requirement-Aware Curriculum Reinforcement Learning
Code generation, which aims to automatically generate source code from given programming requirements, has the potential to substantially improve software development efficiency. With the rapid advancement of large langu…
Reinforcement LearningCode GenerationExploring Pass-Rate Reward in Reinforcement Learning for Code Generation
Reinforcement learning (RL) from unit-test feedback has become a standard post-training recipe for improving large language models (LLMs) on code generation. However, the pass-all-tests binary reward can be sparse, yield…
Reinforcement LearningCode GenerationThemis: Training Robust Multilingual Code Reward Models for Flexible Multi-Criteria Scoring
Reward models (RMs) have become an indispensable fixture of the language model (LM) post-training playbook, enabling policy alignment and test-time scaling. Research on the application of RMs in code generation, however,…
Cross-Lingual TransferCode Generation