PADM'E: Preference Alignment Data Synthesis for Meta-Evaluation of LM Agent Evaluators

arXiv:2609.36086 · cs.CL, cs.AI · Submitted 2026-09-28 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/chc012/padme

Terminology

• Accuracy — 45× in this paper · explained in 1 episode
• Steering — 32× in this paper · explained in 2 episodes
• Alignment — 22× in this paper · explained in 1 episode
• Benchmark — 21× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 5× in this paper · explained in 3 episodes
• Verification — 5× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• LLM judge — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Annotator Agreement — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• Information Asymmetry — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Agent Architectures — 1× in this paper · explained in 1 episode
• Agentic AI — 1× in this paper · explained in 1 episode
• Agentic Loop — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Information Leakage — 1× in this paper · explained in 2 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Positional Bias — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• TICKing All the Boxes: Generated Checklists Improve LLM Evaluation and Generation
• RubricEval: A Rubric-Level Meta-Evaluation Benchmark for LLM Judges in Instruction Following
• Evaluating Large Language Models at Evaluating Instruction Following
• Time to REFLECT: Can We Trust LLM Judges for Evidence-based Research Agents?
• SLMJury: Can Small Language Models Judge as Well as Large Ones?
• Atla Selene Mini: A General Purpose Evaluation Model
• Small Language Models are the Future of Agentic AI

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