2 citations · 7 across the 19 of their papers we have counts for
5 papers · 2 filters
Deep Research: A Systematic Survey
Zhengliang Shi, Yiqun Chen, Haitao Li +23
Large language models (LLMs) have rapidly evolved from text generators into powerful problem solvers. Yet, many open tasks demand critical thinking, multi-source, and verifiable ou…
DeepScientist: Advancing Frontier-Pushing Scientific Findings Progressively
Yixuan Weng, Minjun Zhu, Qiujie Xie +4
While previous AI Scientist systems can generate novel findings, they often lack the focus to produce scientifically valuable contributions that address pressing human-defined chal…
AI-Generated Text is Non-Stationary: Detection via Temporal Tomography
Alva West, Yixuan Weng, Minjun Zhu +4
The field of AI-generated text detection has evolved from supervised classification to zero-shot statistical analysis. However, current approaches share a fundamental limitation: t…
T-Detect: Tail-Aware Statistical Normalization for Robust Detection of Adversarial Machine-Generated Text
Alva West, Luodan Zhang, Liuliu Zhang +3
Large language models (LLMs) have shown the capability to generate fluent and logical content, presenting significant challenges to machine-generated text detection, particularly t…
DeepReview: Improving LLM-based Paper Review with Human-like Deep Thinking Process
Minjun Zhu, Yixuan Weng, Linyi Yang +1
Large Language Models (LLMs) are increasingly utilized in scientific research assessment, particularly in automated paper review. However, existing LLM-based review systems face si…