arXiv:2607. 18529v1 Announce Type: cross Abstract: Teaching videos are becoming a major medium for education, creating a growing need for scalable evaluation of their pedagogical quality.
arXiv:2608. 08852v1 Announce Type: new Abstract: AI agents can now solve problems, answer like subject experts, and generate long-form multimodal content.
arXiv:2606. 06546v1 Announce Type: new Abstract: Evaluating large language models (LLMs) for education requires measuring how models teach, not only what they know.
PhoenixNest-Video is an evidence‑grounded multimodal agent designed for automated video interview assessment. It constructs a semantic video graph as working memory, retrieves information conditioned on rubrics across visual, audio, and textual streams, and outputs per‑criterion scores tied to the candidate’s materials. Trained with rubric‑based reinforcement learning, the system achieves 91.50% grade‑level accuracy on VInterview‑2025, outperforming larger proprietary models while providing traceable evidence for each score.
AI video generation has advanced rapidly and entered widespread commercial use. As a result, quality differences among videos produced by state-of-the-art AI video generation models~(AIVGMs) have become increasingly difficult to discern using conventional evaluation criteria, such as visual fidelity and semantic instruction following.
arXiv:2609.13824v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to evaluate the responses of other language models. This approach, known as LLM-as-a-Judge, is faste...
arXiv:2609.24083v1 Announce Type: new Abstract: Generative AI enables scalable production of educational videos, but current systems largely focus on producing visually coherent content rather than s...
arXiv:2608. 03206v1 Announce Type: cross Abstract: Large language models (LLMs) power educational applications from tutoring to essay scoring, but each is a point solution to a single task, and only recently have these point solutions been integrated into agents operating over a learning management system (LMS).
arXiv:2601.08654v3 Announce Type: replace Abstract: Rubric-based text evaluation increasingly relies on large language models (LLMs) as scalable judges, yet frozen black-box models can interpret the...
arXiv:2608. 09111v1 Announce Type: new Abstract: AI video generation has advanced rapidly and entered widespread commercial use.
arXiv:2605.14322v4 Announce Type: replace Abstract: Language agents are increasingly deployed in professional workflows, yet tutoring remains a high-stakes capability that existing evaluations only p...
arXiv:2607. 11276v1 Announce Type: cross Abstract: Ensuring the quality of educational materials requires more than standard proofreading: textbooks must be audited for factual accuracy, domain-specific technical correctness, and linguistic quality simultaneously -- a task that general-purpose grammar checkers cannot address.
arXiv:2411.02455v3 Announce Type: replace Abstract: The rapid adoption of generative AI has created new opportunities for teaching, learning, and quality assurance. Existing applications, however, re...