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cs.CL2024
RNR: Teaching Large Language Models to Follow Roles and Rules
Kuan Wang, Alexander Bukharin, Haoming Jiang +9
Instruction fine-tuning (IFT) elicits instruction following capabilities and steers the behavior of large language models (LLMs) via supervised learning. However, existing models t…
cs.AI2024★ 4 cited
Inductive or Deductive? Rethinking the Fundamental Reasoning Abilities of LLMs
Kewei Cheng, Jingfeng Yang, Haoming Jiang +9
Reasoning encompasses two typical types: deductive reasoning and inductive reasoning. Despite extensive research into the reasoning capabilities of Large Language Models (LLMs), mo…