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cs.CL2024
Evil twins are not that evil: Qualitative insights into machine-generated prompts
Nathanaël Carraz Rakotonirina, Corentin Kervadec, Francesca Franzon +1
It has been widely observed that language models (LMs) respond in predictable ways to algorithmically generated prompts that are seemingly unintelligible. This is both a sign that…
cs.CL2024
MemoryPrompt: A Light Wrapper to Improve Context Tracking in Pre-trained Language Models
Nathanaël Carraz Rakotonirina, Marco Baroni
Transformer-based language models (LMs) track contextual information through large, hard-coded input windows. We introduce MemoryPrompt, a leaner approach in which the LM is comple…