Papers by Qihao Zhao

2 papers
Demystifying Data Organization for Enhanced LLM Training (2026.acl-long)

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Challenge: Large Language Models (LLMs) have revolutionized various fields, yet their training efficiency is heavily reliant on effective data curation.
Approach: They propose to reuse pre-computed sample-level scores originally generated for data efficiency and introduce two new data ordering methods to improve LLM training.
Outcome: The proposed methods improve the stability and performance of LLM training.
MMLU-CF: A Contamination-free Multi-task Language Understanding Benchmark (2025.acl-long)

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Challenge: Multiple-choice question datasets like Massive Multitask Language Understanding (MMLU) have inevitably led to benchmark contamination, resulting in unreliable evaluation.
Approach: They propose a contamination-free MCQ benchmark called MMLU-CF which reassesses LLMs’ understanding of world knowledge by averting both unintentional and malicious data contamination.
Outcome: The proposed MMLU-CF reassesses LLMs’ understanding of world knowledge by averting both unintentional and malicious data contamination.

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