Jiarong Liang 梁家榕
Research Assistant · University of Waterloo
Hi, I’m Jiarong Liang. I’m currently a Research Assistant at the University of Waterloo, advised by Wenhu Chen, working on natural language processing (NLP) and large language models (LLMs).
I completed my B.S. in Computer Science at South China University of Technology and my M.S. at Washington University in St. Louis.
News
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Meet ReGE, which efficiently consolidates an agent’s past attempts at a task into guidance that helps the same model do better on later attempts, letting GPT-5.6-Luna match GPT-5.6-Sol at only 28% of Sol’s cost. Read the paper or visit the project page.
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Released StopLoss, a small monitor that learns from finished runs to predict when a coding agent is about to fail, so doomed runs can be stopped early. Read the paper, browse the project page, or grab the models and training data.
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New preprint: FIM-Midtraining mid-trains code LLMs to fill in masked functions, a task that mirrors how an agent calls a tool and uses the result, and lifts SWE-Bench-Verified by about 3 points. The paper is on arXiv, and the checkpoints and 2.6B-token corpus are on Hugging Face.
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SWE-Next is out! It turns real merged GitHub pull requests into 2,308 self-verifying tasks for training software-engineering agents. See the paper, the project page, and the dataset.
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Introducing VisPhyWorld, which tests whether multimodal LLMs really understand physics by asking them to rebuild a video as runnable simulator code. The paper and benchmark data are available now.
Selected Publications
All publications →* denotes equal contribution
