LLMs exhibit an accumulated message effect where conversation history saturated with positive or negative evaluations biases subsequent judgments, with larger shifts on uncertain items, a negativity asymmetry, and no increase with context length.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
AMEL: Accumulated Message Effects on LLM Judgments
LLMs exhibit an accumulated message effect where conversation history saturated with positive or negative evaluations biases subsequent judgments, with larger shifts on uncertain items, a negativity asymmetry, and no increase with context length.