5 papers
NAIPv2: Debiased Pairwise Learning for Efficient Paper Quality Estimation
Penghai Zhao, Jinyu Tian, Qinghua Xing +5
The ability to estimate the quality of scientific papers is central to how both humans and AI systems will advance scientific knowledge in the future. However, existing LLM-based e…
A Literature Review of Literature Reviews in Pattern Analysis and Machine Intelligence
Penghai Zhao, Xin Zhang, Jiayue Cao +3
The rapid growth of research in Pattern Analysis and Machine Intelligence (PAMI) has rendered literature reviews essential for consolidating and interpreting knowledge across its m…
A Vision for Auto Research with LLM Agents
Chengwei Liu, Chong Wang, Jiayue Cao +16
This paper introduces Agent-Based Auto Research, a structured multi-agent framework designed to automate, coordinate, and optimize the full lifecycle of scientific research. Levera…
Advancing Textual Prompt Learning with Anchored Attributes
Zheng Li, Yibing Song, Ming-Ming Cheng +2
Textual-based prompt learning methods primarily employ multiple learnable soft prompts and hard class tokens in a cascading manner as text inputs, aiming to align image and text (c…
From Words to Worth: Newborn Article Impact Prediction with LLM
Penghai Zhao, Qinghua Xing, Kairan Dou +5
As the academic landscape expands, the challenge of efficiently identifying impactful newly published articles grows increasingly vital. This paper introduces a promising approach,…