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Related papers: LLM-based Automated Grading with Human-in-the-Loop

200 papers

Optimizing large-language model (LLM) training on distributed domain-specific accelerator systems presents significant challenges due to its complex optimization space. Existing optimization methods, however, rely on time-consuming manual…

Multiagent Systems · Computer Science 2025-11-07 Yuran Ding , Xinwei Chen , Xiaofan Zhang , Zongwei Zhou

With the recent rapid increase in digitization across all major industries, acquiring programming skills has increased the demand for introductory programming courses. This has further resulted in universities integrating programming…

Large Language Models (LLMs) have demonstrated remarkable capabilities in open-ended text generation tasks. However, the inherent open-ended nature of these tasks implies that there is always room for improvement in the quality of model…

Computation and Language · Computer Science 2024-09-16 Ziqi Wang , Le Hou , Tianjian Lu , Yuexin Wu , Yunxuan Li , Hongkun Yu , Heng Ji

As qualitative researchers show growing interest in using automated tools to support interpretive analysis, a large language model (LLM) is often introduced into an analytic workflow as is, without systematic evaluation of interpretive…

Computation and Language · Computer Science 2026-04-02 Songhee Han , Jueun Shin , Jiyoon Han , Bung-Woo Jun , Hilal Ayan Karabatman

Evaluating Text Style Transfer (TST) is a complex task due to its multifaceted nature. The quality of the generated text is measured based on challenging factors, such as style transfer accuracy, content preservation, and overall fluency.…

Computation and Language · Computer Science 2023-09-26 Phil Ostheimer , Mayank Nagda , Marius Kloft , Sophie Fellenz

The field of artificial intelligence (AI) alignment aims to investigate whether AI technologies align with human interests and values and function in a safe and ethical manner. AI alignment is particularly relevant for large language models…

Human-Computer Interaction · Computer Science 2023-01-18 Thilo Hagendorff , Sarah Fabi

Automated text annotation is a compelling use case for generative large language models (LLMs) in social media research. Recent work suggests that LLMs can achieve strong performance on annotation tasks; however, these studies evaluate LLMs…

Computation and Language · Computer Science 2024-09-24 Nicholas Pangakis , Samuel Wolken

Large Language Models (LLMs) like GPT-4o can help automate text classification tasks at low cost and scale. However, there are major concerns about the validity and reliability of LLM outputs. By contrast, human coding is generally more…

Computation and Language · Computer Science 2025-01-17 Conrad Borchers , Danielle R. Thomas , Jionghao Lin , Ralph Abboud , Kenneth R. Koedinger

Text-based open-ended questions in academic formative and summative assessments help students become deep learners and prepare them to understand concepts for a subsequent conceptual assessment. However, grading text-based questions,…

Computers and Society · Computer Science 2024-01-17 Rujun Gao , Hillary E. Merzdorf , Saira Anwar , M. Cynthia Hipwell , Arun Srinivasa

Assessing writing in large classes for formal or informal learners presents a significant challenge. Consequently, most large classes, particularly in science, rely on objective assessment tools such as multiple-choice quizzes, which have a…

Computation and Language · Computer Science 2025-01-24 Chris Impey , Matthew Wenger , Nikhil Garuda , Shahriar Golchin , Sarah Stamer

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a…

Computation and Language · Computer Science 2023-08-29 Lixiang Yan , Lele Sha , Linxuan Zhao , Yuheng Li , Roberto Martinez-Maldonado , Guanliang Chen , Xinyu Li , Yueqiao Jin , Dragan Gašević

Automatic evaluation is an integral aspect of dialogue system research. The traditional reference-based NLG metrics are generally found to be unsuitable for dialogue assessment. Consequently, recent studies have suggested various unique,…

Computation and Language · Computer Science 2024-01-23 Chen Zhang , Luis Fernando D'Haro , Yiming Chen , Malu Zhang , Haizhou Li

Automated short answer grading (ASAG) is critical for scaling educational assessment, yet large language models (LLMs) often struggle with hallucinations and strict rubric adherence due to their reliance on generalized pre-training. While…

Computation and Language · Computer Science 2026-03-23 Yucheng Chu , Haoyu Han , Shen Dong , Hang Li , Kaiqi Yang , Yasemin Copur-Gencturk , Joseph Krajcik , Namsoo Shin , Hui Liu

Large Language Models (LLMs) have advanced artificial intelligence by enabling human-like text generation and natural language understanding. However, their reliance on static training data limits their ability to respond to dynamic,…

Artificial Intelligence · Computer Science 2026-04-02 Aditi Singh , Abul Ehtesham , Saket Kumar , Tala Talaei Khoei , Athanasios V. Vasilakos

Retrieval-augmented generation (RAG) systems are increasingly deployed in user-facing applications, yet systematic, human-centered evaluation of their outputs remains underexplored. Building on Gienapp's utility-dimension framework, we…

Artificial Intelligence · Computer Science 2025-10-01 Aline Mangold , Kiran Hoffmann

Rubric-based text evaluation increasingly uses large language models (LLMs) as scalable judges, but aligning frozen black-box models with human scoring standards remains challenging. We formulate this challenge as a criteria-transfer…

Computation and Language · Computer Science 2026-05-29 Yihan Hong , Huaiyuan Yao , Bolin Shen , Wanpeng Xu , Hua Wei , Yushun Dong

Advanced scientific user facilities, such as next generation X-ray light sources and self-driving laboratories, are revolutionizing scientific discovery by automating routine tasks and enabling rapid experimentation and characterizations.…

Instrumentation and Detectors · Physics 2025-09-03 Aikaterini Vriza , Michael H. Prince , Tao Zhou , Henry Chan , Mathew J. Cherukara

The conventional paradigm of using large language models (LLMs) for natural language generation (NLG) evaluation relies on pre-defined task definitions and evaluation criteria, positioning LLMs as "passive critics" that strictly follow…

Computation and Language · Computer Science 2025-02-18 Shuying Xu , Junjie Hu , Ming Jiang

Teaching assistants (TAs) are essential to grading and feedback provision in proof-based courses, yet these tasks are time-intensive and difficult to scale. Although Large Language Models (LLMs) have been studied for grading and feedback,…

Human-Computer Interaction · Computer Science 2026-03-02 Romina Mahinpei , Sofiia Druchyna , Manoel Horta Ribeiro

Work on instruction-tuned Large Language Models (LLMs) has used automatic methods based on text overlap and LLM judgments as cost-effective alternatives to human evaluation. In this paper, we perform a meta-evaluation of such methods and…

Computation and Language · Computer Science 2024-10-03 Ehsan Doostmohammadi , Oskar Holmström , Marco Kuhlmann