Likelihood Ranking doesn't Scale Like Prompting in LLMs

arXiv:2609.29390 · cs.CL · Submitted 2026-09-24 · Read on arXiv

cs.CL

Submitted: 2026-09-24

Updated: 2026-09-25

Terminology

• Accuracy — 14× in this paper · explained in 1 episode
• Consistency — 6× in this paper · explained in 3 episodes
• Perplexity — 5× in this paper · explained in 3 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Commentary — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Accuracy on Perplexity Score — 1× in this paper
• Akaike Information Criterion — 1× in this paper
• Calibration — 1× in this paper · explained in 7 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• LLM judge — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Twelfth International Conference on Learning Representations — 1× in this paper

Sources

• gpt-oss-120b & gpt-oss-20b Model Card
• Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
• Language Models (Mostly) Know What They Know
• Look at the Text: Instruction-Tuned Language Models are More Robust Multiple Choice Selectors than You Think

Related papers

• Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
• Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
• Subliminal Steering: Stronger Encoding of Hidden Signals
• MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
• The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
• Untangling the Mechanisms of Misleading Context in Medical Question Answering