most citedA Survey of Vibe Coding with Large Language Models

4 citations · 4 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

OSWorld-Science: A Benchmark of Computer Use Agents for Learning and Using Scientific Software

Dingyuan Dai, Heli Qi, Lei Liu +28

Scientific software presents a demanding test for computer-using agents based on visual language models (VLMs): completing a research workflow requires interpreting specialized int…

cs.SE2025

Multi-Docker-Eval: A `Shovel of the Gold Rush' Benchmark on Automatic Environment Building for Software Engineering

Kelin Fu, Tianyu Liu, Zeyu Shang +4

Automated environment configuration is a critical bottleneck in scaling software engineering (SWE) automation. To provide a reliable evaluation standard for this task, we present M…

cs.AI2025★ 4 cited

A Survey of Vibe Coding with Large Language Models

Yuyao Ge, Lingrui Mei, Zenghao Duan +12

The advancement of large language models (LLMs) has catalyzed a paradigm shift from code generation assistance to autonomous coding agents, enabling a novel development methodology…

cs.CL2025

Multilingual Multimodal Software Developer for Code Generation

Linzheng Chai, Jian Yang, Shukai Liu +12

The rapid advancement of Large Language Models (LLMs) has significantly improved code generation, yet most models remain text-only, neglecting crucial visual aids like diagrams and…

cs.CL2025

InvestAlign: Overcoming Data Scarcity in Aligning Large Language Models with Investor Decision-Making Processes under Herd Behavior

Huisheng Wang, Zhuoshi Pan, Hangjing Zhang +3

Aligning Large Language Models (LLMs) with investor decision-making processes under herd behavior is a critical challenge in behavioral finance, which grapples with a fundamental l…