RINI: Seeing the Prior Is Not Enough

arXiv:2609.33284 · cs.AI · Submitted 2026-09-27 · Read on arXiv

cs.AI

Submitted: 2026-09-27

Updated: 2026-09-27

Comments: 55 pages, 4 figures

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

Terminology

• Core — 18× in this paper · explained in 2 episodes
• Benchmark — 9× in this paper · explained in 2 episodes
• Aggregation — 7× in this paper · explained in 1 episode
• Commentary — 6× in this paper · explained in 2 episodes
• Provenance — 6× in this paper · explained in 3 episodes
• Adaptation — 4× in this paper · explained in 1 episode
• Generative AI — 4× in this paper · explained in 2 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Generalization — 3× in this paper · explained in 13 episodes
• Token-Level Max-Sum — 3× in this paper
• Consistency — 2× in this paper · explained in 3 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Abstention — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Empirical Methods in Natural Language Processing — 1× in this paper
• Generative Model — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Sim-to-Real Transfer — 1× in this paper · explained in 2 episodes
• Unsupported Novelty Burden — 1× in this paper

Sources

• ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
• The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
• On the Limits of LLM-as-Judge for Scientific Novelty Assessment
• OpenNovelty: An LLM-powered Agentic System for Verifiable Scholarly Novelty Assessment

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• Agents' Last Exam
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems