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cs.CL2024★ 1 cited
Inference-Time Decontamination: Reusing Leaked Benchmarks for Large Language Model Evaluation
Qin Zhu, Qingyuan Cheng, Runyu Peng +5
The training process of large language models (LLMs) often involves varying degrees of test data contamination. Although current LLMs are achieving increasingly better performance…
cs.CL2024
In-Memory Learning: A Declarative Learning Framework for Large Language Models
Bo Wang, Tianxiang Sun, Hang Yan +3
The exploration of whether agents can align with their environment without relying on human-labeled data presents an intriguing research topic. Drawing inspiration from the alignme…