Introduces a mitigation technique that drops LLM accuracy on popular fiction character tasks from 96% to 72% by limiting verbatim memorization while retaining gist cues.
Exhibits insecurity and anxiety in his dialogues, making references to uncomfortable situations and questioning his own actions
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2024 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Beyond Math: Stories as a Testbed for Memorization-Constrained Reasoning in LLMs
Introduces a mitigation technique that drops LLM accuracy on popular fiction character tasks from 96% to 72% by limiting verbatim memorization while retaining gist cues.