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Xiao Zhan

3 accepted papers

2025

CASE-Bench: Context-Aware SafEty Benchmark for Large Language Models

ICML 2025poster

Aligning large language models (LLMs) with human values is essential for their safe deployment and widespread adoption. Current LLM safety benchmarks often focus solely on the refusal of individual problematic queries, which overlooks the importance of the context where the query occurs and may caus…

Cited by 0SourcePDFScholar
2025

Unlearning vs. Obfuscation: Are We Truly Removing Knowledge?

EMNLP 2025

Unlearning has emerged as a critical capability for large language models (LLMs) to support data privacy, regulatory compliance, and ethical AI deployment. Recent techniques often rely on obfuscation by injecting incorrect or irrelevant information to suppress knowledge. Such methods effectively con

2022

ShapeCrafter: A Recursive Text-Conditioned 3D Shape Generation Model

NeurIPS 2022accept

We present ShapeCrafter, a neural network for recursive text-conditioned 3D shape generation. Existing methods to generate text-conditioned 3D shapes consume an entire text prompt to generate a 3D shape in a single step. However, humans tend to describe shapes recursively---we may start with an init…