surprisal is Not a Theory
Surprisal Theory is often characterized as a computational-level explanation per (Marr, 1982). We argue in this work that, even though a computational level narrative has been used to support "representation-agnostic research" within computational psycholinguistics, the movement toward black box systems embodied by large language models (LLMs) does not exempt modelers using the surprisal metric from the representational decisions required by computational-level characterizations. In fact, we argue that the uncritical use of LLM-surprisal obfuscates the representational and algorithmic-level co
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- PossiblePossibly related (embedding) · 62%Understanding large language models demands distinguishing human projection from machine cognition - Nature →
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- LinkedLinked via arxiv author · 85%Andrés Buxó-Lugo →
“surprisal is Not a Theory”
- LinkedLinked via arxiv author · 85%Aniello De Santo →
“surprisal is Not a Theory”
- LinkedLinked via arxiv author · 85%Morgan Grobol →
“surprisal is Not a Theory”
