23 citations · 68 across the 41 of their papers we have counts for
43 papers
SWE-Gate: Passing Functional Tests Is Not Enough for Software Engineering Agents
Xin He, Yanlin Wang, Mingwei Liu +3
Repository-level software engineering benchmarks have significantly advanced the evaluation of coding agents, but existing benchmarks primarily measure whether generated patches pa…
Efficient SWE Agent Benchmarking via Trajectory-Aware Evaluation
Kefeng Duan, Dewu Zheng, Yanlin Wang +7
Evaluating software engineering agents on realistic benchmarks is costly, since each task may require multi-step code exploration, modification, and test execution. Existing effici…
RepoReasoner: Evaluating Repository-Level Code Reasoning Ability of Long-Context Language Models
Yanlin Wang, Suiquan Wang, Yanli Wang +4
Recent large language models (LLMs) have shown strong performance on software engineering tasks, yet most existing benchmarks evaluate code reasoning at the function level, where a…
WebDesignIter: Co-Evolving Design Knowledge for Repository-Level Front-End Code Generation
Zheng Pei, Mingwei Liu, Zhenxi Chen +2
Front-end development accumulates change after change at the repository level, weaving complex cross-file dependencies that current LLM coding agents tuned for single-shot tasks ca…
The Ghosts of Polymarket: When Off-Chain Matches Meet On-Chain Reverts
Yiming Shen, Yuhan Jin, Shuohan Wu +2
Polymarket has emerged as a prominent prediction market platform and one of the fastest-growing applications in DeFi. To achieve low-latency trading, it adopts a hybrid architectur…
Dynamic analysis enhances issue resolution
Mingwei Liu, Zihao Wang, Zhenxi Chen +3
Resolving complex code defects from natural language descriptions remains a fundamental software engineering challenge. Recently, large language models (LLMs) have driven the creat…
RealSec-bench: A Benchmark for Evaluating Secure Code Generation in Real-World Repositories
Yanlin Wang, Ziyao Zhang, Chong Wang +5
Large Language Models (LLMs) have demonstrated remarkable capabilities in code generation, but their proficiency in producing secure code remains a critical, under-explored area. E…
ShortCoder: Knowledge-Augmented Syntax Optimization for Token-Efficient Code Generation
Sicong Liu, Yanxian Huang, Mingwei Liu +6
Code generation tasks aim to automate the conversion of user requirements into executable code, significantly reducing manual development efforts and enhancing software productivit…
AlignCoder: Aligning Retrieval with Target Intent for Repository-Level Code Completion
Tianyue Jiang, Yanli Wang, Yanlin Wang +5
Repository-level code completion remains a challenging task for existing code large language models (code LLMs) due to their limited understanding of repository-specific context an…
Knowledge-Graph-Driven Data Synthesis for Low-Resource Software Development: A HarmonyOS Case Study
Mingwei Liu, Zheng Pei, Yanlin Wang +5
In low-resource framework development (e.g., HarmonyOS), large language models (LLMs) often lack sufficient pre-training exposure, resulting in poor code generation performance. Al…
Knowledge Matters: Injecting Project and Testing Knowledge into LLM-based Unit Test Generation
Anji Li, Mingwei Liu, Zhenxi Chen +5
Automated unit test generation using large language models (LLMs) holds great promise but often struggles with generating tests that are both correct and maintainable in real-world…
Trace: Securing Smart Contract Repository Against Access Control Vulnerability
Chong Chen, Jiachi Chen, Lingfeng Bao +7
Smart contract vulnerabilities, particularly improper Access Control that allows unauthorized execution of restricted functions, have caused billions of dollars in losses. GitHub h…
Coinvisor: An RL-Enhanced Chatbot Agent for Interactive Cryptocurrency Investment Analysis
Chong Chen, Ze Liu, Lingfeng Bao +4
The cryptocurrency market offers significant investment opportunities but faces challenges including high volatility and fragmented information. Data integration and analysis are e…
Generating High-Quality Datasets for Code Editing via Open-Source Language Models
Zekai Zhang, Mingwei Liu, Zhenxi Chen +7
Code editing plays a vital role in software engineering, requiring developers to adjust existing code according to natural language instructions while keeping functionality intact…
Web3 x AI Agents: Landscape, Integrations, and Foundational Challenges
Yiming Shen, Jiashuo Zhang, Zhenzhe Shao +6
The convergence of Web3 technologies and AI agents is a rapidly evolving frontier that is reshaping decentralized ecosystems. This paper presents the first comprehensive landscape…
EvolMathEval: Towards Evolvable Benchmarks for Mathematical Reasoning via Evolutionary Testing
Shengbo Wang, Mingwei Liu, Zike Li +4
The rapid advancement of Large Language Models (LLMs) poses a significant challenge to existing mathematical reasoning benchmarks. However, these benchmarks tend to become easier o…
A Hierarchical and Evolvable Benchmark for Fine-Grained Code Instruction Following with Multi-Turn Feedback
Guoliang Duan, Mingwei Liu, Yanlin Wang +3
Large language models (LLMs) have advanced significantly in code generation, yet their ability to follow complex programming instructions with layered and diverse constraints remai…
FORGE: An LLM-driven Framework for Large-Scale Smart Contract Vulnerability Dataset Construction
Jiachi Chen, Yiming Shen, Jiashuo Zhang +7
High-quality smart contract vulnerability datasets are critical for evaluating security tools and advancing smart contract security research. Two major limitations of current manua…
SWE-Factory: Your Automated Factory for Issue Resolution Training Data and Evaluation Benchmarks
Lianghong Guo, Yanlin Wang, Caihua Li +6
Constructing large-scale datasets for the GitHub issue resolution task is crucial for both training and evaluating the software engineering capabilities of Large Language Models (L…
AdaDec: A Uncertainty-Guided Lookahead Decoding Framework for LLM-Based Code Generation
Kaifeng He, Mingwei Liu, Chong Wang +4
Code generation with large language models (LLMs) is highly sensitive to token selection during decoding, particularly at uncertain decision points that influence program logic. Wh…
FeedbackEval: A Benchmark for Evaluating Large Language Models in Feedback-Driven Code Repair Tasks
Dekun Dai, MingWei Liu, Anji Li +5
Code repair is a fundamental task in software development, facilitating efficient bug resolution and software maintenance. Although large language models (LLMs) have demonstrated c…
What to Retrieve for Effective Retrieval-Augmented Code Generation? An Empirical Study and Beyond
Wenchao Gu, Juntao Chen, Yanlin Wang +6
Repository-level code generation remains challenging due to complex code dependencies and the limitations of large language models (LLMs) in processing long contexts. While retriev…
RustEvo^2: An Evolving Benchmark for API Evolution in LLM-based Rust Code Generation
Linxi Liang, Jing Gong, Mingwei Liu +5
Large Language Models (LLMs) have become pivotal tools for automating code generation in software development. However, these models face significant challenges in producing versio…
NumScout: Unveiling Numerical Defects in Smart Contracts using LLM-Pruning Symbolic Execution
Jiachi Chen, Zhenzhe Shao, Shuo Yang +5
In recent years, the Ethereum platform has witnessed a proliferation of smart contracts, accompanied by exponential growth in total value locked (TVL). High-TVL smart contracts oft…