6 citations · 8 across the 7 of their papers we have counts for
8 papers
WebUIProof: Benchmarking WebUI Code Generators with UI-Agent Execution Harness
Yun-Yun Tsai, Yuning Mao, Shiqi Wang +2
Evaluating WebUI code generation at scale is difficult: outputs may compile and look plausible yet fail under user interaction, and prior benchmarks largely rely on free-form promp…
Parallel-SFT: Improving Zero-Shot Cross-Programming-Language Transfer for Code RL
Zhaofeng Wu, Shiqi Wang, Boya Peng +5
Modern language models demonstrate impressive coding capabilities in common programming languages (PLs), such as C++ and Python, but their performance in lower-resource PLs is ofte…
UTFix: Change Aware Unit Test Repairing using LLM
Shanto Rahman, Sachit Kuhar, Berk Cirisci +5
Software updates, including bug repair and feature additions, are frequent in modern applications but they often leave test suites outdated, resulting in undetected bugs and increa…
Planning-Aware Code Infilling via Horizon-Length Prediction
Yifeng Ding, Hantian Ding, Shiqi Wang +3
Fill-in-the-Middle (FIM), or infilling, has become integral to code language models, enabling generation of missing code given both left and right contexts. However, the current FI…
LeDex: Training LLMs to Better Self-Debug and Explain Code
Nan Jiang, Xiaopeng Li, Shiqi Wang +6
In the domain of code generation, self-debugging is crucial. It allows LLMs to refine their generated code based on execution feedback. This is particularly important because gener…
CodeFort: Robust Training for Code Generation Models
Yuhao Zhang, Shiqi Wang, Haifeng Qian +8
Code generation models are not robust to small perturbations, which often lead to incorrect generations and significantly degrade the performance of these models. Although improvin…
Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM
Gabriel Ryan, Siddhartha Jain, Mingyue Shang +4
Testing plays a pivotal role in ensuring software quality, yet conventional Search Based Software Testing (SBST) methods often struggle with complex software units, achieving subop…
Token Alignment via Character Matching for Subword Completion
Ben Athiwaratkun, Shiqi Wang, Mingyue Shang +7
Generative models, widely utilized in various applications, can often struggle with prompts corresponding to partial tokens. This struggle stems from tokenization, where partial to…