most citedAI4Research: A Survey of Artificial Intelligence for Scientific Research

3 citations · 3 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2026

AnomalyAgent: Agentic Industrial Anomaly Synthesis via Tool-Augmented Reinforcement Learning

Jiaming Su, Tengchao Yang, Ruikang Zhang +3

Industrial anomaly generation is a crucial method for alleviating the data scarcity problem in anomaly detection tasks. Most existing anomaly synthesis methods rely on single-step…

cs.CL2026

Learning the Boundary of Solvability: Aligning LLMs to Detect Unsolvable Problems

Dengyun Peng, Qiguang Chen, Bofei Liu +6

Ensuring large language model (LLM) reliability requires distinguishing objective unsolvability (inherent contradictions) from subjective capability limitations (tasks exceeding mo…

cs.LG2025

A Survey on Cache Methods in Diffusion Models: Toward Efficient Multi-Modal Generation

Jiacheng Liu, Xinyu Wang, Yuqi Lin +10

Diffusion Models have become a cornerstone of modern generative AI for their exceptional generation quality and controllability. However, their inherent \textit{multi-step iteratio…

cs.CL2025

The Universal Landscape of Human Reasoning

Qiguang Chen, Jinhao Liu, Libo Qin +14

Understanding how information is dynamically accumulated and transformed in human reasoning has long challenged cognitive psychology, philosophy, and artificial intelligence. Exist…

cs.CL2025

AutoPR: Let's Automate Your Academic Promotion!

Qiguang Chen, Zheng Yan, Mingda Yang +10

As the volume of peer-reviewed research surges, scholars increasingly rely on social platforms for discovery, while authors invest considerable effort in promoting their work to en…

cs.CL20253 cited

AI4Research: A Survey of Artificial Intelligence for Scientific Research

Qiguang Chen, Mingda Yang, Libo Qin +13

Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs) such as OpenAI-o1 and DeepSeek-R1, have demonstrated remarkable capabilities in co…