rubric

Introduces FinProBench, a benchmark for evaluating financial AI agents using role-grounded rubrics derived from real professional deliverables, and proposes an RGRC pipeline that improves evaluation for role-specialized tasks.

Introduces RubricReviewer, a rubric-driven framework for LLM-based peer review that explicitly generates paper-adaptive rubrics and combines a training-free evidence-gathering agent (Scout) with a trained human-aligned model (Aligner) to produce more comprehensive, discriminative, and robust reviews.

The author created an open-source rubric tool to evaluate agentic AI vendor documentation on tool-call correctness, loop termination, and multi-step state coherence, scored five vendors (Anthropic, OpenAI, LangGraph, Sierra, Salesforce), and requests feedback on methodology and potential bias toward public documentation depth.

This paper describes the development of an LLM-based tool using OpenAI's GPT models to evaluate approximately 1,200 Statements of Purpose for Purdue's SURF program, processing them in 4.6 hours and accelerating the review process compared to traditional human grading.

This paper proposes a learner model-based rubric to evaluate the adaptivity of Vision Language Models (VLMs) in mathematics education. Experiments show measurable differences in adaptivity across models and reveal that current VLMs struggle to produce consistent learner-adaptive instructional responses.