6 papers
From 0-to-1 to 1-to-N: Reproducible Engineering Evidence for MetaAI Recursive Self-Design
Dun Li, Jiatao Li, Hongzhi Li
Recursive self-design refers to AI-assisted modification of the mechanisms by which an AI system is built, evaluated, and improved. This paper treats MetaAI not as a mature paradig…
Analyzing Cognitive Differences Among Large Language Models through the Lens of Social Worldview
Jiatao Li, Yanheng Li, Xiaojun Wan
Large Language Models significantly influence social interactions, decision-making, and information dissemination, underscoring the need to understand the implicit socio-cognitive…
Who Writes What: Unveiling the Impact of Author Roles on AI-generated Text Detection
Jiatao Li, Xiaojun Wan
The rise of Large Language Models (LLMs) necessitates accurate AI-generated text detection. However, current approaches largely overlook the influence of author characteristics. We…
AGENT-X: Adaptive Guideline-based Expert Network for Threshold-free AI-generated teXt detection
Jiatao Li, Mao Ye, Cheng Peng +2
Existing AI-generated text detection methods heavily depend on large annotated datasets and external threshold tuning, restricting interpretability, adaptability, and zero-shot eff…
Aspect-Guided Multi-Level Perturbation Analysis of Large Language Models in Automated Peer Review
Jiatao Li, Yanheng Li, Xinyu Hu +2
We propose an aspect-guided, multi-level perturbation framework to evaluate the robustness of Large Language Models (LLMs) in automated peer review. Our framework explores perturba…
Evaluating Self-Generated Documents for Enhancing Retrieval-Augmented Generation with Large Language Models
Jiatao Li, Xinyu Hu, Xunjian Yin +1
The integration of documents generated by LLMs themselves (Self-Docs) alongside retrieved documents has emerged as a promising strategy for retrieval-augmented generation systems.…