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Huijie Lv

2 accepted papers

2026

Reasoning or Memorization? Unreliable Results of Reinforcement Learning Due to Data Contamination

AAAI 2026technical

Reasoning in large language models has long been a central research focus, and recent studies employing reinforcement learning (RL) have introduced diverse methods that yield substantial performance gains with minimal or even no external supervision. Surprisingly, some studies even suggest that rand

Cited by 0SourcePDFScholar
2025

Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable Metric

ACL 2025long

Data diversity is crucial for the instruction tuning of large language models. Existing studies have explored various diversity-aware data selection methods to construct high-quality datasets and enhance model performance. However, the fundamental problem of precisely defining and measuring data div…