most citedLLM-based Automated Grading with Human-in-the-Loop

4 citations · 8 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Optimizing In-Context Demonstrations for LLM-based Automated Grading

Yucheng Chu, Hang Li, Kaiqi Yang +4

Automated assessment of open-ended student responses is a critical capability for scaling personalized feedback in education. While large language models (LLMs) have shown promise…

cs.AI2026

Confusion-Aware Rubric Optimization for LLM-based Automated Grading

Yucheng Chu, Hang Li, Kaiqi Yang +4

Accurate and unambiguous guidelines are critical for large language model (LLM) based graders, yet manually crafting these prompts is often sub-optimal as LLMs can misinterpret exp…

cs.AI2026

How Uncertain Is the Grade? A Benchmark of Uncertainty Metrics for LLM-Based Automatic Assessment

Hang Li, Kaiqi Yang, Xianxuan Long +9

The rapid rise of large language models (LLMs) is reshaping the landscape of automatic assessment in education. While these systems demonstrate substantial advantages in adaptabili…

cs.CL2025★ 2 cited

RAG LLMs are Not Safer: A Safety Analysis of Retrieval-Augmented Generation for Large Language Models

Bang An, Shiyue Zhang, Mark Dredze

Efforts to ensure the safety of large language models (LLMs) include safety fine-tuning, evaluation, and red teaming. However, despite the widespread use of the Retrieval-Augmented…

cs.CL2025

Enhancing LLM-Based Short Answer Grading with Retrieval-Augmented Generation

Yucheng Chu, Peng He, Hang Li +6

Short answer assessment is a vital component of science education, allowing evaluation of students' complex three-dimensional understanding. Large language models (LLMs) that posse…

cs.CL2025★ 4 cited

LLM-based Automated Grading with Human-in-the-Loop

Yucheng Chu, Hang Li, Kaiqi Yang +2

The rise of artificial intelligence (AI) technologies, particularly large language models (LLMs), has brought significant advancements to the field of education. Among various appl…

cs.CL2025★ 2 cited

A Survey on Post-training of Large Language Models

Guiyao Tie, Zeli Zhao, Dingjie Song +23

The emergence of Large Language Models (LLMs) has fundamentally transformed natural language processing, making them indispensable across domains ranging from conversational system…