3 papers
cs.CL2024
Interpreting Key Mechanisms of Factual Recall in Transformer-Based Language Models
Ang Lv, Yuhan Chen, Kaiyi Zhang +5
In this paper, we delve into several mechanisms employed by Transformer-based language models (LLMs) for factual recall tasks. We outline a pipeline consisting of three major steps…
cs.LG2024
Batch-ICL: Effective, Efficient, and Order-Agnostic In-Context Learning
Kaiyi Zhang, Ang Lv, Yuhan Chen +3
In this paper, by treating in-context learning (ICL) as a meta-optimization process, we explain why LLMs are sensitive to the order of ICL examples. This understanding leads us to…
cs.CL2023
An Analysis and Mitigation of the Reversal Curse
Ang Lv, Kaiyi Zhang, Shufang Xie +4
Recent research observed a noteworthy phenomenon in large language models (LLMs), referred to as the ``reversal curse.'' The reversal curse is that when dealing with two entities,…