Papers Code Generation
“Code Generation” 태그가 달린 논문 3,075편 · 필터 해제
Code2World: A GUI World Model via Renderable Code Generation
Autonomous GUI agents interact with environments by perceiving interfaces and executing actions. As a virtual sandbox, the GUI World model empowers agents with human-like foresight by enabling action-conditioned predicti…
Reinforcement LearningCode GenerationChain of Mindset: Reasoning with Adaptive Cognitive Modes
Human problem-solving is never the repetition of a single mindset, by which we mean a distinct mode of cognitive processing. When tackling a specific task, we do not rely on a single mindset; instead, we integrate multip…
Spatial ReasoningCode GenerationQuantum-Audit: Evaluating the Reasoning Limits of LLMs on Quantum Computing
Language models have become practical tools for quantum computing education and research, from summarizing technical papers to explaining theoretical concepts and answering questions about recent developments in the fiel…
Code GenerationACE-RTL: When Agentic Context Evolution Meets RTL-Specialized LLMs
Recent advances in LLMs have sparked growing interest in applying them to hardware design automation, particularly for accurate RTL code generation. Prior efforts follow two largely independent paths: (i) training domain…
Code GenerationWeak-Driven Learning: How Weak Agents make Strong Agents Stronger
As post-training optimization becomes central to improving large language models, we observe a persistent saturation bottleneck: once models grow highly confident, further training yields diminishing returns. While exist…
Mathematical ReasoningCode GenerationLLMs + Security = Trouble
We argue that when it comes to producing secure code with AI, the prevailing "fighting fire with fire" approach -- using probabilistic AI-based checkers or attackers to secure probabilistically generated code -- fails to…
Code GenerationGeo-Code: A Code Framework for Reverse Code Generation from Geometric Images Based on Two-Stage Multi-Agent Evolution
Program code serves as a bridge linking vision and logic, providing a feasible supervisory approach for enhancing the multimodal reasoning capability of large models through geometric operations such as auxiliary line co…
Multimodal ReasoningCode GenerationMARTI-MARS$^2$: Scaling Multi-Agent Self-Search via Reinforcement Learning for Code Generation
While the complex reasoning capability of Large Language Models (LLMs) has attracted significant attention, single-agent systems often encounter inherent performance ceilings in complex tasks such as code generation. Mul…
Multi-agent Reinforcement LearningCode GenerationSecure Code Generation via Online Reinforcement Learning with Vulnerability Reward Model
Large language models (LLMs) are increasingly used in software development, yet their tendency to generate insecure code remains a major barrier to real-world deployment. Existing secure code alignment methods often suff…
Vulnerability DetectionReinforcement LearningCode GenerationSurprisal-Guided Selection: Compute-Optimal Test-Time Strategies for Execution-Grounded Code Generation
Test-time training (TTT) adapts language models through gradient-based updates at inference. But is adaptation the right strategy? We study compute-optimal test-time strategies for verifiable execution-grounded (VEG) tas…
Code GenerationCodeCircuit: Toward Inferring LLM-Generated Code Correctness via Attribution Graphs
Current paradigms for code verification rely heavily on external mechanisms-such as execution-based unit tests or auxiliary LLM judges-which are often labor-intensive or limited by the judging model's own capabilities. T…
Code GenerationBEAGLE: Behavior-Enforced Agent for Grounded Learner Emulation
Simulating student learning behaviors in open-ended problem-solving environments holds potential for education research, from training adaptive tutoring systems to stress-testing pedagogical interventions. However, colle…
Knowledge TracingCode GenerationRAG Strategies for Natural Language-Based SQL Query and REST API Call Generation
Enterprise software systems commonly expose business functionality through both relational databases and REST APIs. Accessing these interfaces requires specialized technical knowledge, as users must determine whether a r…
Code GenerationEvoMAS: Evolutionary Generation of Multi-Agent Systems
Large language model (LLM)-based multi-agent systems (MAS) show strong promise for complex reasoning, planning, and tool-augmented tasks, but designing effective MAS architectures remains labor-intensive, brittle, and ha…
Code GenerationEGSS: Entropy-guided Stepwise Scaling for Reliable Software Engineering
Agentic Test-Time Scaling (TTS) has delivered state-of-the-art (SOTA) performance on complex software engineering tasks such as code generation and bug fixing. However, its practical adoption remains limited due to signi…
Computational EfficiencyCode GenerationALIVE: Awakening LLM Reasoning via Adversarial Learning and Instructive Verbal Evaluation
The quest for expert-level reasoning in Large Language Models (LLMs) has been hampered by a persistent \textit{reward bottleneck}: traditional reinforcement learning (RL) relies on scalar rewards that are \textbf{costly}…
Reinforcement LearningMathematical ReasoningDomain GeneralizationCode GenerationA Theoretical Analysis of Test-Driven Code Generation
Code assistants are increasingly utilized in test-driven software development, yet the theoretical mechanisms behind their environment-interaction strategies remain underexplored. We provide a probabilistic framework for…
Code GenerationTowards Green AI: Decoding the Energy of LLM Inference in Software Development
Context: AI-assisted tools are increasingly integrated into software development workflows, but their reliance on large language models (LLMs) introduces substantial computational and energy costs. Understanding and redu…
Code GenerationVisRefiner: Learning from Visual Differences for Screenshot-to-Code Generation
Screenshot-to-code generation aims to translate user interface screenshots into executable frontend code that faithfully reproduces the target layout and style. Existing multimodal large language models perform this mapp…
Reinforcement LearningCode GenerationDyTopo: Dynamic Topology Routing for Multi-Agent Reasoning via Semantic Matching
Multi-agent systems built from prompted large language models can improve multi-round reasoning, yet most existing pipelines rely on fixed, trajectory-wide communication patterns that are poorly matched to the stage-depe…
Mathematical ReasoningCode Generation