Search Results for author:
Found 3 papers, 0 papers with code
PACIT: Unlocking the Power of Examples for Better In-Context Instruction Tuning
Instruction tuning enhances the instruction following ability of large language models by finetuning with supervised instruction data.
Parameter-Efficient Tuning Helps Language Model Alignment
To this end, prior works incorporate controllable generations for alignment to make language models learn multiple preferences and provide outputs with different preferences during inference if asked.
RCOT: Detecting and Rectifying Factual Inconsistency in Reasoning by Reversing Chain-of-Thought
To detect factual inconsistency, RCoT first asks LLMs to reconstruct the problem based on generated solutions.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
