[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"glossary-position-bias::en":3,"gloss-cluster-position-bias::en":23,"gloss-next-position-bias::en":9},{"slug":4,"category":5,"name":6,"definition":7,"meta_desc":8,"faq":9,"schema_markup":9,"related":10},"position-bias","prompt-eng","Position Bias","Position bias is the tendency of an LLM to be swayed by where information sits rather than what it says — most visibly when the model acts as a judge or picks among options. In pairwise evaluation, judges often favor whichever candidate is presented first (or sometimes last) regardless of quality; the same effect shows up in multiple-choice tasks, where reordering the options changes the answer. It was documented prominently in LLM-as-judge work such as MT-Bench (Zheng et al., 2023) and is related to, but distinct from, 'lost in the middle,' where facts buried mid-context get underused. It matters because it silently corrupts any ranking, routing, or selection you build on top of a model, producing results that look principled but track order. For builders, the fixes are cheap: swap positions and average both orderings, randomize option order, and calibrate against a small human-labeled set. If a decision flips when you only reordered the inputs, position bias is doing the deciding — not the content.","Position bias is an LLM being swayed by where information sits rather than what it says — judges favour whichever answer came first, so you must swap and re-run.",null,[11,14,17,20],{"slug":12,"name":13},"llm-as-judge","LLM-as-Judge",{"slug":15,"name":16},"lost-in-the-middle","Lost in the Middle",{"slug":18,"name":19},"pairwise-evaluation","Pairwise Evaluation",{"slug":21,"name":22},"self-consistency","Self-Consistency",[24,28,31,34,38,41,44,47,50,53,56,59],{"slug":25,"category":5,"name":26,"updated_at":27},"analogical-prompting","Analogical Prompting","2026-08-24T02:46:37+00:00",{"slug":29,"category":5,"name":30,"updated_at":27},"automatic-prompt-optimization","Automatic Prompt Optimization",{"slug":32,"category":5,"name":33,"updated_at":27},"chain-of-density","Chain of Density (CoD)",{"slug":35,"category":5,"name":36,"updated_at":37},"chain-of-thought-prompting","Chain-of-Thought Prompting","2026-08-24T02:46:36+00:00",{"slug":39,"category":5,"name":40,"updated_at":27},"chain-of-verification","Chain-of-Verification",{"slug":42,"category":5,"name":43,"updated_at":37},"chunking","Chunking",{"slug":45,"category":5,"name":46,"updated_at":37},"constrained-decoding","Constrained Decoding",{"slug":48,"category":5,"name":49,"updated_at":37},"context-stuffing","Context Stuffing",{"slug":51,"category":5,"name":52,"updated_at":37},"delimiter","Delimiter",{"slug":54,"category":5,"name":55,"updated_at":27},"directional-stimulus-prompting","Directional Stimulus Prompting",{"slug":57,"category":5,"name":58,"updated_at":27},"emotion-prompting","Emotion Prompting",{"slug":60,"category":5,"name":61,"updated_at":37},"few-shot-prompting","Few-Shot Prompting"]