Papers Code Generation
“Code Generation” 태그가 달린 논문 3,075편 · 필터 해제
Experience Graphs: The Data Foundation for Self-Improving Agents
The database community has repeatedly advanced the state of the art by recognizing that new workloads demand new system architectures. We argue that long-horizon agentic tasks -- code generation, scientific discovery, ha…
Code GenerationNeuReasoner: Theory-grounded Mapping of Reasoning Elicitation Boundaries
A growing body of work suggests that the reasoning capabilities of large language models are largely latent in their base form, with post-training primarily amplifying rather than introducing them. However, this evidence…
Arithmetic ReasoningCode GenerationDecision MakingAlgoSkill: Learning to Design Algorithms by Scheduling Human-Like Skills
Designing an algorithm from a natural-language problem statement requires identifying the problem structure, reading constraints, choosing a suitable paradigm, checking correctness, and refining complexity. Existing larg…
Code GenerationCitation Discipline in Spec-Driven Development: A Cross-Model Empirical Study of Output Determinism and Automated Hallucination Detection in LLM-Generated Code
Spec-Driven Development (SDD) frameworks guide Large Language Model (LLM)-powered code generation through formal specifications, yet they differ fundamentally in how they enforce traceability between requirements and gen…
Code GenerationFlipGuard: Defending Large Language Models Against Quantization-Conditioned Backdoor Attacks
Model quantization is essential for the efficient deployment of Large Language Models (LLMs), but introduces a critical vulnerability: Quantization-Conditioned Backdoor (QCB) attacks. In these attacks, malicious behavior…
Code GenerationReward-Free Code Alignment from Pretrained or Fine-Tuned LLM: Unpacking the Trade-offs for Code Generation
Large Language Model (LLM) alignment trains an LLM using preference data to produce outputs that better meet established quality standards. While LLM alignment techniques are studied for non-coding tasks, we know little …
Code GenerationAnimation2Code: Evaluating Temporal Visual Reasoning in Video-to-Code Generation
While recent vision-language models (VLMs) have achieved significant improvements on static visual-to-code tasks such as generating code for webpages, charts, or SVGs, it remains unclear whether they can recover temporal…
Visual ReasoningCode GenerationNebulaExp-8B: An Empirical Post-Training Pipeline via Full-Scale Ablation Research
Post-training alignment determines the reasoning and human preference following capabilities of large language models, yet most existing works withhold detailed data construction, filtering rules and training recipes, wh…
Reinforcement LearningMathematical ReasoningGeneral KnowledgeCode GenerationLibEvoBench: Probing Temporal Knowledge Stratification in Code Generation Models
Large software projects often depend on older versions of libraries, even as APIs continue to evolve across releases. This creates a challenge for LLMs: they must maintain knowledge of multiple API versions, not merely t…
Code GenerationQuantization Inflates Reasoning: Token Inflation as a Hidden Cost of Low-Bit Reasoning Models
Quantization is widely used to reduce the inference cost of large language models, but its effect on reasoning models is not fully captured by final-answer accuracy or per-token latency. We show that low-bit post-trainin…
Mathematical ReasoningQuestion AnsweringCode GenerationOPERA: Aligning Open-Ended Reasoning via Objective Perplexity-based Reinforcement Learning
Reinforcement Learning (RL) has enabled LLMs to excel in objective reasoning tasks such as mathematics and code generation. However, applying RL to open-ended tasks, such as creative writing, remains challenging because …
Reinforcement LearningCode GenerationOptimizing CUDA like a Human: Micro-Profiling Tools as Expert Surrogates for LLM-Based GPU Kernel Optimization
We present KernelPro, a closed-loop multi-agent system that automatically generates, profiles, and iteratively optimizes GPU kernel code by integrating large language model (LLM) code generation with hardware profiler fe…
Code GenerationCode SearchDream at SemEval-2026 Task 13: SALSA for Single-Pass Machine-Generated Code Detection
Large language models have transformed code generation, raising concerns around authorship, assessment integrity, and software trust. SemEval-2026 Task 13 Subtask A operationalizes detection as binary classification over…
parameter-efficient fine-tuningBinary ClassificationCode GenerationSoK: AI Secure Code Generation: Progress, Pitfalls, and Paths Forward
The increasing use of AI systems for code generation raises a central security question: what can today's models and coding agents actually do to produce secure code, where do they still fail, and what would move the fie…
Reinforcement LearningCode GenerationFinding the Evidence: Discovering Decision-Supporting Tokens for On-Policy Reasoning Distillation
On-policy distillation transfers reasoning ability through dense token-level supervision, yet the nature of the transferable signal remains unclear. We discover that reasoning chains contain two types of knowledge that r…
Code GenerationAI Scientists as Engines of Discovery: A Case for Development within Reformed Institutions
Agentic artificial intelligence (AI) systems are beginning to assist, accelerate, and partially automate scientific discovery, performing tasks that span literature synthesis, code generation, data analysis, hypothesis p…
Code GenerationReNIO: Reweighting Negative Trajectory Importance for LLM On-Policy Distillation
On-policy distillation (OPD) improves LLM reasoning by training a student model on its own generated outputs, but standard OPD treats all student-generated outputs (SGOs) equally regardless of their informativeness. We o…
Reinforcement LearningMathematical ReasoningCode GenerationText2DSL: LLM-Based Code Generation for Domain-Specific Languages
Domain-specific languages (DSLs) are widely used for managing operating system security policies, yet manually authoring rules in such languages demands high expertise and is error-prone. This paper formalises the task o…
Code GenerationCodeTeam: An LLM-Powered Multi-Agent Framework for Repository-Level Code Generation
Natural language to repository generation (NL2Repo) requires a system to construct an entire software repository from a natural-language requirements document. Compared with function-level code generation, this task dema…
Code GenerationDecision MakingSwarmX: Agentic Scheduling for Low-Latency Agentic Systems
Agentic AI applications compose multiple model calls and tool executions, creating new scheduling challenges for GPU-CPU clusters. Their inference time and model-call structure often depend on prompt semantics, making co…
Code Generation