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Found 6 papers, 1 papers with code
Automatic Feedback Generation for Short Answer Questions using Answer Diagnostic Graphs
We propose an "answer diagnosis graph," integrating the text's logical structure with feedback templates.
Reducing the Cost: Cross-Prompt Pre-Finetuning for Short Answer Scoring
Specifically, given that scoring rubrics and reference answers differ for each prompt, we utilize key phrases, or representative expressions that the answer should contain to increase scores, and train a SAS model to learn the relationship between key phrases and answers using already annotated prompts (i. e., cross-prompts).
Japanese-English Sentence Translation Exercises Dataset for Automatic Grading
Using this dataset, we demonstrate the performance of baselines including finetuned BERT and GPT models with few-shot in-context learning.
Assessing Step-by-Step Reasoning against Lexical Negation: A Case Study on Syllogism
Large language models (LLMs) take advantage of step-by-step reasoning instructions, e. g., chain-of-thought (CoT) prompting.
Balancing Cost and Quality: An Exploration of Human-in-the-loop Frameworks for Automated Short Answer Scoring
Towards guaranteeing high-quality predictions, we present the first study of exploring the use of human-in-the-loop framework for minimizing the grading cost while guaranteeing the grading quality by allowing a SAS model to share the grading task with a human grader.
Preventing Critical Scoring Errors in Short Answer Scoring with Confidence Estimation
We introduce a new task formulation of SAS that matches the actual usage.
