1 citations · 4 across the 13 of their papers we have counts for
15 papers
Assembling Insights for Agentic Machine Learning Engineering Systems
Bihui Jin, Yinxi Li, Kaiyuan Wang +1
Agentic machine learning engineering (MLE) is an emerging AI4SE application for complex ML tasks and a step toward recursive self-improvement of AI systems. Recent agentic MLE syst…
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…
Compile by Training: Turning Natural-Language Specifications into Local Neural Functions
Yuntian Deng, Pengyu Nie, Stuart Shieber
Many recurring text functions are easy to describe but difficult to implement with rules, while calling a large remote model for every input introduces repeated cost, latency, and…
What Makes a Good Bug Report for an AI Agent?
Lara Khatib, Noble Saji Mathews, Meiyappan Nagappan +2
Automated program repair (APR) agents are transitioning from research benchmarks to developer workflows, yet they still begin with bug reports written for human developers. While d…
Program-as-Weights: A Programming Paradigm for Fuzzy Functions
Wentao Zhang, Liliana Hotsko, Woojeong Kim +3
Many everyday programming tasks resist clean rule-based implementation, such as alerting on important log lines, repairing malformed JSON, or ranking search results by intent, and…
TestEvo-Bench: An Executable and Live Benchmark for Test and Code Co-Evolution
Jiale Amber Wang, Kaiyuan Wang, Pengyu Nie
Software tests and code evolve together: a code change should be followed by new or updated tests that record the new software behavior. Yet existing test generation and update ben…
Code2LoRA: Hypernetwork-Generated Adapters for Code Language Models under Software Evolution
Liliana Hotsko, Yinxi Li, Yuntian Deng +1
Code language models need repository-level context to resolve imports, APIs, and project conventions. Existing methods inject this knowledge as long inputs (retrieved through RAG o…
Automated Modernization of Machine Learning Engineering Notebooks for Reproducibility
Bihui Jin, Kaiyuan Wang, Pengyu Nie
Interactive computational notebooks (e.g., Jupyter notebooks) are widely used in machine learning engineering (MLE) to program and share end-to-end pipelines, from data preparation…
TokDrift: When LLM Speaks in Subwords but Code Speaks in Grammar
Yinxi Li, Yuntian Deng, Pengyu Nie
Large language models (LLMs) for code rely on subword tokenizers, such as byte-pair encoding (BPE), learned from mixed natural language text and programming language code but drive…
NL in the Middle: Code Translation with LLMs and Intermediate Representations
Chi-en Amy Tai, Pengyu Nie, Lukasz Golab +1
Studies show that large language models (LLMs) produce buggy code translations. One promising avenue to improve translation accuracy is through intermediate representations, which…
Mix-of-Language-Experts Architecture for Multilingual Programming
Yifan Zong, Yuntian Deng, Pengyu Nie
Large language models (LLMs) have demonstrated impressive capabilities in aiding developers with tasks like code comprehension, generation, and translation. Supporting multilingual…
Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models
Bihui Jin, Jiayue Wang, Pengyu Nie
Machine learning developers frequently use interactive computational notebooks, such as Jupyter notebooks, to host code for data processing and model training. Jupyter notebooks pr…
InterTrans: Leveraging Transitive Intermediate Translations to Enhance LLM-based Code Translation
Marcos Macedo, Yuan Tian, Pengyu Nie +2
Code translation aims to convert a program from one programming language (PL) to another. This long-standing software engineering task is crucial for modernizing legacy systems, en…
Efficient Incremental Code Coverage Analysis for Regression Test Suites
Jiale Amber Wang, Kaiyuan Wang, Pengyu Nie
Code coverage analysis has been widely adopted in the continuous integration of open-source and industry software repositories to monitor the adequacy of regression test suites. Ho…
Energy-Efficient Software Development: A Multi-dimensional Empirical Analysis of Stack Overflow
Bihui Jin, Heng Li, Pengyu Nie +1
Energy consumption of software applications has emerged as a critical concern for developers to contemplate in their daily development processes. Previous studies have surveyed a l…