most citedText-Based Approaches to Item Difficulty Modeling in Large-Scale Assessments: A Systematic Review

1 citations · 1 across the 8 of their papers we have counts for

collaborators

14 papers

cs.CL2026

Towards Valid Student Simulation with Large Language Models

Zhihao Yuan, Yunze Xiao, Ming Li +4

This paper presents a conceptual and methodological framework for large language model (LLM) based student simulation in educational settings. The authors identify a core failure m…

cs.CL20251 cited

Text-Based Approaches to Item Difficulty Modeling in Large-Scale Assessments: A Systematic Review

Sydney Peters, Nan Zhang, Hong Jiao +3

Item difficulty plays a crucial role in test performance, interpretability of scores, and equity for all test-takers, especially in large-scale assessments. Traditional approaches…

cs.AI2025

Understanding the Thinking Process of Reasoning Models: A Perspective from Schoenfeld's Episode Theory

Ming Li, Nan Zhang, Chenrui Fan +6

While Large Reasoning Models (LRMs) generate extensive chain-of-thought reasoning, we lack a principled framework for understanding how these thoughts are structured. In this paper…

cs.LG2025

Generative Models for Synthetic Data: Transforming Data Mining in the GenAI Era

Dawei Li, Yue Huang, Ming Li +3

Generative models such as Large Language Models, Diffusion Models, and generative adversarial networks have recently revolutionized the creation of synthetic data, offering scalabl…

cs.CV2025

VisR-Bench: An Empirical Study on Visual Retrieval-Augmented Generation for Multilingual Long Document Understanding

Jian Chen, Ming Li, Jihyung Kil +6

Most organizational data in this world are stored as documents, and visual retrieval plays a crucial role in unlocking the collective intelligence from all these documents. However…

cs.CV2025

CaughtCheating: Is Your MLLM a Good Cheating Detective? Exploring the Boundary of Visual Perception and Reasoning

Ming Li, Chenguang Wang, Yijun Liang +6

Recent agentic Multi-Modal Large Language Models (MLLMs) such as GPT-o3 have achieved near-ceiling scores on various existing benchmarks, motivating a demand for more challenging t…