Across 252,000 paired trials on six LLMs, topical relevance and list position emerged as the strongest drivers of first citation in competitive RAG, with price information and recency providing consistent secondary gains.
Characterizing Positional Bias in Large Language Models: A Multi-Model Evaluation of Prompt Order Effects
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Constructs multi-video summarization benchmark and evaluates nine MLLMs showing positional bias is domain- and model-dependent with middle positions often weaker and budgets not uniformly fixing it.
citing papers explorer
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What Gets Cited: Competitive GEO in AI Answer Engines
Across 252,000 paired trials on six LLMs, topical relevance and list position emerged as the strongest drivers of first citation in competitive RAG, with price information and recency providing consistent secondary gains.
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A Systematic Evaluation of Positional Bias in Multi-Video Summarization with MLLMs
Constructs multi-video summarization benchmark and evaluates nine MLLMs showing positional bias is domain- and model-dependent with middle positions often weaker and budgets not uniformly fixing it.