activity
20232026
most citedInstruct or Interact? Exploring and Eliciting LLMs' Capability in Code Snippet Adaptation Through Prompt Engineering

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2026

AREX: Towards a Recursively Self-Improving Agent for Deep Research

Shuqi Lu, Chaofan Li, Kun Luo +21

Deep research requires agents to find answers that jointly satisfy multiple constraints. Discovering such answers is costly, whereas verifying a candidate can often be decomposed i…

cs.AI2026

AgentFactory: A Self-Evolving Framework Through Executable Subagent Accumulation and Reuse

Zhang Zhang, Shuqi Lu, Hongjin Qian +2

Building LLM-based agents has become increasingly important. Recent works on LLM-based agent self-evolution primarily record successful experiences as textual prompts or reflection…

cs.SE2026

AdaptEval: A Benchmark for Evaluating Large Language Models on Code Snippet Adaptation

Tanghaoran Zhang, Xinjun Mao, Shangwen Wang +6

Recent advancements in large language models (LLMs) have automated various software engineering tasks, with benchmarks emerging to evaluate their capabilities. However, for adaptat…

cs.SE2025

Large Language Models are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Tasks

Kang Yang, Xinjun Mao, Shangwen Wang +7

Pre-trained code models rely heavily on high-quality pre-training data, particularly human-written reference comments that bridge code and natural language. However, these comments…

cs.SE2024★ 1 cited

Instruct or Interact? Exploring and Eliciting LLMs' Capability in Code Snippet Adaptation Through Prompt Engineering

Tanghaoran Zhang, Yue Yu, Xinjun Mao +5

Code snippet adaptation is a fundamental activity in the software development process. Unlike code generation, code snippet adaptation is not a "free creation", which requires deve…

cs.SE2023

Enhancing Code Intelligence Tasks with ChatGPT

Kang Yang, Xinjun Mao, Shangwen Wang +6

Pre-trained code models have emerged as crucial tools in various code intelligence tasks. However, their effectiveness depends on the quality of the pre-training dataset, particula…

cs.SE2023

ROS package search for robot software development: a knowledge graph-based approach

Shuo Wang, Xinjun Mao, Shuo Yang +2

ROS (Robot Operating System) packages have become increasingly popular as a type of software artifact that can be effectively reused in robotic software development. Indeed, findin…