Software Engineering

Teaching Your Models to Understand Code via Focal Preference Alignment EMNLP 2025 TestEval: Benchmarking Large Language Models for Test Case Generation NAACL 2025 The Human in Interactive Machine Learning: Analysis and Perspectives for Ambient Intelligence (Abstract Reprint) IJCAI 2025 Thinking Before Running! Efficient Code Generation with Thorough Exploration and Optimal Refinement ACL 2025 Think-Search-Patch: A Retrieval-Augmented Reasoning Framework for Repository-Level Code Repair EMNLP 2025 TokenSmith: Streamlining Data Editing, Search, and Inspection for Large-Scale Language Model Training and Interpretability EMNLP 2025 ToolCoder: A Systematic Code-Empowered Tool Learning Framework for Large Language Models ACL 2025 Towards a Practical Tool for Music Composition: Using Constraint Programming to Model Chord Progressions and Modulations IJCAI 2025 Towards Effectively Leveraging Execution Traces for Program Repair with Code LLMs NAACL 2025 Transforming Code Understanding: Clustering-Based Retrieval for Improved Summarization in Domain-Specific Languages COLING 2025 Uncertainty-Aware Contrastive Learning with Hard Negative Sampling for Code Search Tasks AAAI 2025 UniDebugger: Hierarchical Multi-Agent Framework for Unified Software Debugging EMNLP 2025 UnitCoder: Scalable Code Synthesis from Pre-training Corpora EMNLP 2025 Unmasking Database Vulnerabilities: Zero-Knowledge Schema Inference Attacks in Text-to-SQL Systems NAACL 2025 UTBoost: Rigorous Evaluation of Coding Agents on SWE-Bench ACL 2025 VEP: A Two-stage Verification Toolchain for Full eBPF Programmability NSDI 2025 VeriLocc: End-to-End Cross-Architecture Register Allocation via LLM EMNLP 2025 VisualCoder: Guiding Large Language Models in Code Execution with Fine-grained Multimodal Chain-of-Thought Reasoning NAACL 2025 WAFFLE: Fine-tuning Multi-Modal Model for Automated Front-End Development ACL 2025 What can Large Language Models Capture about Code Functional Equivalence? NAACL 2025 What Can Youth Learn About Artificial Intelligence and Machine Learning in One Hour? Examining How Hour of Code Activities Address the Five Big Ideas of AI AAAI 2025 What Do Machine Learning Researchers Mean by “Reproducible”? AAAI 2025 Why Stop at One Error? Benchmarking LLMs as Data Science Code Debuggers for Multi-Hop and Multi-Bug Errors EMNLP 2025 AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters ACL 2024 Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving ICML 2024