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20232026
most citedApplying Large Language Models and Chain-of-Thought for Automatic Scoring

13 citations · 36 across the 27 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024★ 3 cited

LMOD: A Large Multimodal Ophthalmology Dataset and Benchmark for Large Vision-Language Models

Zhenyue Qin, Yu Yin, Dylan Campbell +6

The prevalence of vision-threatening eye diseases is a significant global burden, with many cases remaining undiagnosed or diagnosed too late for effective treatment. Large vision-…

cs.CL2024★ 1 cited

Leveraging Large Language Models with Chain-of-Thought and Prompt Engineering for Traffic Crash Severity Analysis and Inference

Hao Zhen, Yucheng Shi, Yongcan Huang +2

Harnessing the power of Large Language Models (LLMs), this study explores the use of three state-of-the-art LLMs, specifically GPT-3.5-turbo, LLaMA3-8B, and LLaMA3-70B, for crash s…

cs.CL2024★ 2 cited

Unveiling Scoring Processes: Dissecting the Differences between LLMs and Human Graders in Automatic Scoring

Xuansheng Wu, Padmaja Pravin Saraf, Gyeonggeon Lee +3

Large language models (LLMs) have demonstrated strong potential in performing automatic scoring for constructed response assessments. While constructed responses graded by humans a…

cs.LG2024★ 2 cited

Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models

Yili Wang, Kaixiong Zhou, Ninghao Liu +2

Sharpness-aware minimization (SAM) has received increasing attention in computer vision since it can effectively eliminate the sharp local minima from the training trajectory and m…

cs.LG2024★ 1 cited

Rethinking Independent Cross-Entropy Loss For Graph-Structured Data

Rui Miao, Kaixiong Zhou, Yili Wang +3

Graph neural networks (GNNs) have exhibited prominent performance in learning graph-structured data. Considering node classification task, based on the i.i.d assumption among node…

cs.CL2024★ 1 cited

Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question Answering

Yucheng Shi, Qiaoyu Tan, Xuansheng Wu +3

Large Language Models (LLMs) have shown proficiency in question-answering tasks but often struggle to integrate real-time knowledge, leading to potentially outdated or inaccurate r…

cs.LG2024

Usable XAI: 10 Strategies Towards Exploiting Explainability in the LLM Era

Xuansheng Wu, Haiyan Zhao, Yaochen Zhu +9

Explainable AI (XAI) refers to techniques that provide human-understandable insights into the workings of AI models. Recently, the focus of XAI is being extended toward explaining…