activity
20242026
most citedAutoPLC: Generating Vendor-Aware Structured Text for Programmable Logic Controllers

2 citations · 2 across the 11 of their papers we have counts for

collaborators

13 papers

cs.SE2026

MRCoder: An Efficient Context Selecting Approach for Repository-Level Code Generation

Peiding Wang, Li Zhang, Fang Liu

Large language models (LLMs) have demonstrated strong capabilities in code generation. However, repository-level code generation remains challenging, as it requires effectively ide…

cs.SE2026

An Empirical Study of Interaction Smells in Multi-Turn Human-LLM Collaborative Code Generation

Binquan Zhang, Li Zhang, Lin Shi +6

Large Language Models (LLMs) have revolutionized code generation, evolving from static tools into dynamic conversational interfaces that facilitate complex, multi-turn collaborativ…

cs.SE2026

A Scalable Benchmark for Repository-Oriented Long-Horizon Conversational Context Management

Yang Liu, Li Zhang, Fang Liu +2

In recent years, large language models (LLMs) have advanced rapidly, substantially enhancing their code understanding and generation capabilities and giving rise to powerful code a…

cs.SE2026

CodeMEM: AST-Guided Adaptive Memory for Repository-Level Iterative Code Generation

Peiding Wang, Li Zhang, Fang Liu +2

Large language models (LLMs) substantially enhance developer productivity in repository-level code generation through interactive collaboration. However, as interactions progress,…

cs.SE2025

Decoding Human-LLM Collaboration in Coding: An Empirical Study of Multi-Turn Conversations in the Wild

Binquan Zhang, Li Zhang, Haoyuan Zhang +5

Large language models (LLMs) are increasingly acting as dynamic conversational interfaces, supporting multi-turn interactions that mimic human-like conversation and facilitate comp…

cs.SE2025

Are They All Good? Evaluating the Quality of CoTs in LLM-based Code Generation

Binquan Zhang, Li Zhang, Zhiwen Luo +4

Large language models (LLMs) have demonstrated impressive performance in code generation, particularly when augmented with chain-of-thought (CoT) prompting techniques. They break d…

cs.AI2025

LLM-Driven Collaborative Model for Untangling Commits via Explicit and Implicit Dependency Reasoning

Bo Hou, Xin Tan, Kai Zheng +3

Atomic commits, which address a single development concern, are a best practice in software development. In practice, however, developers often produce tangled commits that mix unr…

cs.SE2025

RepoScope: Leveraging Call Chain-Aware Multi-View Context for Repository-Level Code Generation

Yang Liu, Li Zhang, Fang Liu +6

Repository-level code generation aims to generate code within the context of a specified repository. Existing approaches typically employ retrieval-augmented generation (RAG) techn…

cs.SE2025

AdaptiveLLM: A Framework for Selecting Optimal Cost-Efficient LLM for Code-Generation Based on CoT Length

Junhang Cheng, Fang Liu, Chengru Wu +1

While Large Language Models (LLMs) have significantly advanced code generation efficiency, they face inherent challenges in balancing performance and inference costs across diverse…

cs.SE2025

EfficientEdit: Accelerating Code Editing via Edit-Oriented Speculative Decoding

Peiding Wang, Li Zhang, Fang Liu +7

Large Language Models (LLMs) have demonstrated remarkable capabilities in code editing, substantially enhancing software development productivity. However, the inherent complexity…

cs.SE2025

CodeIF-Bench: Evaluating Instruction-Following Capabilities of Large Language Models in Interactive Code Generation

Peiding Wang, Li Zhang, Fang Liu +4

Large Language Models (LLMs) have demonstrated exceptional performance in code generation tasks and have become indispensable programming assistants for developers. However, existi…

cs.AI2025

FastCoder: Accelerating Repository-level Code Generation via Efficient Retrieval and Verification

Qianhui Zhao, Li Zhang, Fang Liu +6

Code generation is a latency-sensitive task that demands high timeliness. However, with the growing interest and inherent difficulty in repository-level code generation, most exist…

cs.SE2024★ 2 cited

AutoPLC: Generating Vendor-Aware Structured Text for Programmable Logic Controllers

Donghao Yang, Aolang Wu, Tianyi Zhang +6

Among the programming languages for Programmable Logic Controllers (PLCs), Structured Text (ST) is widely adopted for industrial automation due to its expressiveness and flexibilit…