4 papers
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…
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…
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…
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…