JuryProbe: An Empirical Consensus-Risk Diagnostic for Routing Reference-Free Factuality Judge Panels to Grounded Verification

arXiv:2608.20607 · cs.CL, cs.AI, cs.LG · Submitted 2026-08-20 · Read on arXiv

cs.CL, cs.AI, cs.LG

Submitted: 2026-08-20

Updated: 2026-08-27

Comments: Accepted at Transactions on Machine Learning Research (TMLR), 08/2026. 21 pages, 1 figure, 16 tables

Journal ref: Transactions on Machine Learning Research, 2026

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

Terminology

Grounding — 46× in this paper · explained in 3 episodes
Calibration — 40× in this paper · explained in 7 episodes
Verification — 27× in this paper · explained in 2 episodes
Verifier — 23× in this paper · explained in 2 episodes
Benchmark — 20× in this paper · explained in 2 episodes
Robustness — 9× in this paper · explained in 5 episodes
Distribution Shift — 7× in this paper · explained in 5 episodes
LLM judge — 6× in this paper · explained in 2 episodes
Aggregation — 4× in this paper · explained in 1 episode
Consistency — 4× in this paper · explained in 3 episodes
Hallucination — 3× in this paper · explained in 3 episodes
LLM-as-a-Judge — 3× in this paper · explained in 3 episodes
Accuracy — 2× in this paper · explained in 1 episode
Alignment — 1× in this paper · explained in 1 episode
Empirical Methods in Natural Language Processing — 1× in this paper
Generalization — 1× in this paper · explained in 13 episodes
Hallucination Detection — 1× in this paper · explained in 2 episodes
Instruction Tuning — 1× in this paper · explained in 2 episodes
Provenance — 1× in this paper · explained in 3 episodes
Redundancy — 1× in this paper · explained in 2 episodes

Sources

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