Judgement

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4 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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Judgement in the Age of Jev: From Evaluation Scarcity to Evaluation Abundance
Oct 1, 2026Richard HillJudgement Value
Department of Computer Science, University of Huddersfield, Huddersfield, UK.
JudgeProfile: Understanding and Steering Subjectivity in LLM Judges
Sep 29, 2026Qi Cao, Kangning Liu, Xuan Kan +10Large Language Model Judges Judgement
Meta · University of California San Diego · The University of Hong Kong +1
Mnemon: Raw Records, Fast Judgments, Slow Thoughts
Sep 28, 2026Guangren WangAgentic Memory Peak Memory
Open-Jev Judgments on CallScreenBench: Calibrated One-Pass Scam Screening with a Small Language Model
Sep 21, 2026Simiao Ren, Kidus Zewde, Xingyu Shen +6Judgement Fraud Detection
Scam.ai (Reality Inc.)
When Hiring Becomes Agent-Mediated: Evaluating Access and Recurrence in Two-Agent Résumé Screening
Sep 17, 2026Jian Gao, Hang JiangJobs Screening
Northeastern University Boston, MA, USA
Gaze as Evidence for Common Grounding: A Cross-Corpus Analysis of MapTask and MUNDEX
Sep 16, 2026Nan Li, Albert Gatt, Massimo PoesioGaze Behavior Contextual Grounding
Utrecht University, Utrecht, The Netherlands · Queen Mary University of London, London, The United Kingdom
When Does Defendant Statement Matter? A Study of Bias and Persuasion in LLM-Simulated Jurors
Sep 9, 2026Cho-Ying WuJudgement Llm-As-A-Judge
Bosch AI Research
Epistemic Transfer in AI-Assisted Verification: A Framework and Evaluation Protocol
Aug 9, 2026Christoph TrattnerArtificial Intelligence Evaluation Category-Aware Atomic Claims
SFI MediaFutures, Research Centre for Responsible Media Technology and Innovation · Department of Information Science and Media Studies, University of Bergen, Norway
Generation or Judgement? A Paradigm Perspective on LLM-Based Emotion-Cause Pair Extraction in Conversation
Jul 29, 2026Weijie Feng, Hongchuang Wang, Binbin Liu +1Emotional Support Conversation Task Model Judgments
Hefei University of Technology
PROJECTMEM: A Local-First, Event-Sourced Memory and Judgment Layer for AI Coding Agents
Jun 10, 2026Ripon Chandra Malo, Tong QiuCoding Agents Model Context Protocol
University of Utah
AI Assistance for Human Review of Default Judgments
Jun 4, 2026Theodora Worledge, Othman Bensouda Koraichi, Daniel Bernal +4Court Judgement
1Stanford Computer Science, Stanford University · 2Deborah L. Rhode Center, Stanford Law School · University of Chicago Law School +1
Stability vs. Manipulability: Evaluating Robustness Under Post-Decision Interaction in LLM Judges
Jun 3, 2026Srimonti Dutta, Akshata Kishore MoharirLlm-As-A-Judge Large Language Model Judges
WAI USA Research Labs
UA-Legal-Bench: A Benchmark for Evaluating Large Language Models on Ukrainian Legal Reasoning
May 27, 2026Volodymyr OvcharovLegal Reasoning Tasks Legal Natural Language Processing Benchmarks
SecondLayer
JECA^2: Judgment-Explanation Consistent Adversarial Attack against Forensic Vision-Language Models
May 27, 2026Jiachen QianRecent Vision-Language Models Judgement
City University of Hong Kong
Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why
May 25, 2026Delip Rao, Chris Callison-BurchLarge Language Model Judges Judgement
University of Pennsylvania
Behavioral Coherence: A Method for Sensitive-Domain LLM Evaluation
Dec 15, 2025Anika Sharma, Malavika Mampally, Chidaksh Ravuru +2Large Language Model Evaluation Judgement
Society-Centered AI Lab UNC Chapel Hill, USA · School of Nursing UNC Chapel Hill, USA

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Judgement in the Age of Jev: From Evaluation Scarcity to Evaluation Abundance

Richard Hill

Department of Computer Science, University of Huddersfield, Huddersfield, UK.

Judgement Value Hypothesis

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Generative artificial intelligence has reduced the cost of producing plausible symbolic artefacts, leading recent organisation scholarship to identify evaluation and discernment as constraints under conditions of production abundance. This perspective examines a further possibility: that machine evaluation itself becomes inexpensive enough to be deployed routinely and at scale. The investigation is prompted by Jev, TypeSafe AI's specialised model for typed probabilistic decisions. TypeSafe explicitly invokes William Stanley Jevons to argue that lower-cost machine intelligence can unlock previously uneconomic uses. Treating this as a technological provocation rather than an established empirical result, the article formulates a conditional Jevons hypothesis for machine evaluation: sufficiently large reductions in the total marginal cost of usable machine evaluation may increase its organisational consumption where latent demand is substantial and complementary costs do not dominate. The article integrates rebound economics with research on cheap prediction, production abundance, machine evaluation, decision allocation, authority, reliance and Executive Judgement to examine this possible scarcity transition. It distinguishes prediction, machine evaluation, organisational judgement and authorisation as functional activities whose costs need not fall together. Evaluations can share evidence, criteria and errors; scale mis-specified rubrics; operate on representations from which consequential qualifications have disappeared; and change practical decision rights through thresholds and exception routing. The resulting research problem is when cheap machine evaluation substitutes for human evaluative work, when it redistributes or creates demands for judgement, and how it affects the grounds available at consequential organisational commitment.

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