Fan Long — accepted AI-conference papers

2026

Scam2Prompt: A Scalable Framework for Auditing Malicious Scam Endpoints in Production LLMs

Zhiyang Chen, Tara Saba, Xun Deng, Xujie Si, Fan Long

ICML 2026poster

Large Language Models (LLMs) have become critical to modern software development, but their reliance on uncurated web-scale datasets for training introduces a significant security risk: the absorption and reproduction of malicious content. This risk materialized in November 2024, when a user suffere…

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2025

TypyBench: Evaluating LLM Type Inference for Untyped Python Repositories

Honghua Dong, Jiacheng Yang, Xun Deng, Yuhe Jiang, Gennady Pekhimenko, Fan Long +1

ICML 2025poster

Type inference for dynamic languages like Python is a persistent challenge in software engineering. While large language models (LLMs) have shown promise in code understanding, their type inference capabilities remain underexplored. We introduce `TypyBench`, a benchmark designed to evaluate LLMs' ty…

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