论文笔记

按主题分类的论文总结和笔记。

最后更新：2025-06-17 19:26:49

主题导航

• Code Generation
  • 250613_Deployability-Centric Infrastructure-as-Code Generation: An LLM-based Iterative Framework
  • 250615_ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation
  • 250615_Deployability-Centric Infrastructure-as-Code Generation: An LLM-based Iterative Framework
  • 250615_Reinforcing Code Generation: Improving Text-to-SQL with Execution-Based Learning
  • 250615_DesignBench: A Comprehensive Benchmark for MLLM-based Front-end Code Generation
  • 250617_Reasoning as a Resource: Optimizing Fast and Slow Thinking in Code Generation Models
  • 250617_Prompt Variability Effects On LLM Code Generation
  • 250617_AutoGEEval++: A Multi-Level and Multi-Geospatial-Modality Automated Evaluation Framework for Large Language Models in Geospatial Code Generation on Google Earth Engine
  • 250617_Execution Guided Line-by-Line Code Generation
• General
  • 250612_PoLAR: Polar-Decomposed Low-Rank Adapter Representation
  • 250615_PoLAR: Polar-Decomposed Low-Rank Adapter Representation
  • 250615_VISCA: Inferring Component Abstractions for Automated End-to-End Testing
  • 250615_Can Theoretical Physics Research Benefit from Language Agents?
  • 250615_KnowCoder-V2: Deep Knowledge Analysis
  • 250617_Edit Flows: Flow Matching with Edit Operations
  • 250617_UTBoost: Rigorous Evaluation of Coding Agents on SWE-Bench
  • 250617_AutoMind: Adaptive Knowledgeable Agent for Automated Data Science
  • 250617_ReVeal: Self-Evolving Code Agents via Iterative Generation-Verification
• Machine Learning
  • 250612_XAI-Units: Benchmarking Explainability Methods with Unit Tests
  • 250612_Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning
  • 250613_The Impact of Software Testing with Quantum Optimization Meets Machine Learning
  • 250615_The Impact of Software Testing with Quantum Optimization Meets Machine Learning
  • 250615_Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning
  • 250615_ICPC-Eval: Probing the Frontiers of LLM Reasoning with Competitive Programming Contests
  • 250615_A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair
  • 250615_Table-r1: Self-supervised and Reinforcement Learning for Program-based Table Reasoning in Small Language Models
  • 250615_KramaBench: A Benchmark for AI Systems on Data-to-Insight Pipelines over Data Lakes
  • 250617_Repeton: Structured Bug Repair with ReAct-Guided Patch-and-Test Cycles
  • 250617_LLM-as-a-Judge for Reference-less Automatic Code Validation and Refinement for Natural Language to Bash in IT Automation
  • 250617_Identifying Helpful Context for LLM-based Vulnerability Repair: A Preliminary Study
  • 250617_code_transformed: The Influence of Large Language Models on Code
  • 250617_QiMeng-Attention: SOTA Attention Operator is generated by SOTA Attention Algorithm
• Software Engineering
  • 250612_Test Automation for Interactive Scenarios via Promptable Traffic Simulation
  • 250617_Understanding Software Engineering Agents Through the Lens of Traceability: An Empirical Study
  • 250617_AI5GTest: AI-Driven Specification-Aware Automated Testing and Validation of 5G O-RAN Components
• Software Testing
  • 250617_IntenTest: Stress Testing for Intent Integrity in API-Calling LLM Agents
  • 250617_Scalable Software Testing in Fast Virtual Platforms: Leveraging SystemC, QEMU and Containerization
• Test Generation
  • 250612_Automated Web Application Testing: End-to-End Test Case Generation with Large Language Models and Screen Transition Graphs
  • 250612_Hallucination to Consensus: Multi-Agent LLMs for End-to-End Test Generation with Accurate Oracles
  • 250612_On Mutation-Guided Unit Test Generation
  • 250612_GenFair: Systematic Test Generation for Fairness Fault Detection in Large Language Models
  • 250613_Automated Web Application Testing: End-to-End Test Case Generation with Large Language Models and Screen Transition Graphs
  • 250613_On Mutation-Guided Unit Test Generation
  • 250613_Can LLMs Generate Reliable Test Case Generators? A Study on Competition-Level Programming Problems
  • 250615_Automated Web Application Testing: End-to-End Test Case Generation with Large Language Models and Screen Transition Graphs
  • 250615_Hallucination to Consensus: Multi-Agent LLMs for End-to-End Test Generation with Accurate Oracles
  • 250615_On Mutation-Guided Unit Test Generation
  • 250615_GenFair: Systematic Test Generation for Fairness Fault Detection in Large Language Models
  • 250615_CodeContests+: High-Quality Test Case Generation for Competitive Programming
  • 250615_Can LLMs Generate Reliable Test Case Generators? A Study on Competition-Level Programming Problems
  • 250617_Boosting Rust Unit Test Coverage through Hybrid Program Analysis and Large Language Models
  • 250617_Leveraging GPT-4 for Vulnerability-Witnessing Unit Test Generation
  • 250617_Can LLMs Generate High-Quality Test Cases for Algorithm Problems? TestCase-Eval: A Systematic Evaluation of Fault Coverage and Exposure