Papers with MCScript

2 papers
BLCU-NLP at COIN-Shared Task1: Stagewise Fine-tuning BERT for Commonsense Inference in Everyday Narrations (D19-60)

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Challenge: Experimental results show that our system achieves significant improvements over the baseline systems with 84.2% accuracy on the official test dataset.
Approach: They propose a system to inject more external knowledge into everyday narrations . they use a pre-trained BERT model to fine-tune on a machine reading comprehension dataset .
Outcome: The proposed system achieves significant improvements over baseline systems with 84.2% accuracy on the official test dataset.
ABSEval: An Agent-based Framework for Script Evaluation (2024.emnlp-main)

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Challenge: Existing studies on script evaluation of large language models (LLMs) have not evaluated scripts generated by LLMs due to their logical structure, sequential organization, and open-ended nature.
Approach: They propose to use a script evaluation dataset to evaluate LLM scripts . they propose to develop an agent-based script evaluation framework ABSEval to evaluate scripts.
Outcome: The proposed framework provides superior accuracy and relevance, aligning closely with human evaluation.

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