SupportCal: Label-Free Calibration of Post-Trained LLMs via Reference Support and Corroboration

arXiv:2609.24303 · cs.LG, cs.CL · Submitted 2026-09-21 · Read on arXiv

cs.LG, cs.CL

Submitted: 2026-09-21

Updated: 2026-10-05

Comments: 14 pages, 5 figures, 6 tables

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Calibration — 53× in this paper · explained in 7 episodes
• Alignment — 7× in this paper · explained in 1 episode
• Empirical Methods in Natural Language Processing — 3× in this paper
• Ablation — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Expected Calibration Error — 2× in this paper
• International Conference on Machine Learning — 2× in this paper
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes

Sources

• DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
• Gemma 3 Technical Report
• The Llama 3 Herd of Models
• Mistral 7B
• Language Models (Mostly) Know What They Know
• Qwen2.5 Technical Report
• Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
• Qwen3 Technical Report
• Yi: Open Foundation Models by 01.AI

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