CORDIAL: Calibrating Ordinal LLM Outputs from Few Labels

arXiv:2609.29807 · cs.CL, cs.LG · Submitted 2026-09-24 · Read on arXiv

cs.CL, cs.LG

Submitted: 2026-09-24

Updated: 2026-09-24

Terminology

• Calibration — 35× in this paper · explained in 7 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Large Language Model (LLM) — 2× in this paper · explained in 3 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Core — 1× in this paper · explained in 2 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Prompt Engineering — 1× in this paper · explained in 4 episodes

Sources

• Language Models (Mostly) Know What They Know
• Sentiment Analysis in the Era of Large Language Models: A Reality Check
• Auditing Multimodal LLM Raters: Central Tendency Bias in Clinical Ordinal Scoring
• GPT-4 Technical Report
• Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders
• Qwen2.5 Technical Report
• The Llama 3 Herd of Models
• Calibration of Ordinal Regression Networks
• Are LLMs Positionally Consistent Ordinal Classifiers? A Systematic Evaluation

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