AI RESEARCH
Decision-Level Ordinal Modeling for Multimodal Essay Scoring with Large Language Models
arXiv CS.AI
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ArXi:2603.14891v1 Announce Type: cross Automated essay scoring (AES) predicts multiple rubric-defined trait scores for each essay, where each trait follows an ordered discrete rating scale. Most LLM-based AES methods cast scoring as autoregressive token generation and obtain the final score via decoding and parsing, making the decision implicit. This formulation is particularly sensitive in multimodal AES, where the usefulness of visual inputs varies across essays and traits.