Papers by Zhouxiang Fang
ICL CIPHERS: Quantifying ”Learning” in In-Context Learning via Substitution Ciphers (2025.emnlp-main)
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| Challenge: | Recent studies suggest that In-Context Learning operates in dual modes . however, disentangling these modes remains a challenging goal . |
| Approach: | They propose a class of task reformulations based on substitution ciphers borrowed from classic cryptography. |
| Outcome: | The proposed model can solve tasks with a BIJECTIVE mapping, but it requires 'deciphering' the latent cipher. |
Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions (2025.naacl-long)
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| Challenge: | Medical board exams or general clinical questions do not capture the complexity of real clinical cases. |
| Approach: | They construct two datasets that are structured as multiple-choice question-answering tasks accompanied by expert-written explanations. |
| Outcome: | The proposed datasets are harder than previous benchmarks. |