9 papers
Predicting Signed Distance Functions for Visual Instance Segmentation
Emil Brissman, Joakim Johnander, Michael Felsberg
Visual instance segmentation is a challenging problem and becomes even more difficult if objects of interest varies unconstrained in shape. Some objects are well described by a rec…
Externalizing Research Synthesis and Validation in AI Scientists through a Research Harness
Zijian Wang, Hanqi Li, Ziyue Yang +17
AI systems can increasingly automate scientific workflows, but the reasoning that links prior evidence, generated ideas, experiments and final claims often remains implicit inside…
DeepSurvey: Enhancing Analytical Depth and Citation Reliability in Automated Survey Generation
Ziyue Yang, Da Ma, Hanqi Li +8
As scientific literature grows rapidly, automated survey generation has become a key capability for AI scientists and human researchers. However, existing systems suffer from limit…
AirQA: A Comprehensive QA Dataset for AI Research with Instance-Level Evaluation
Tiancheng Huang, Ruisheng Cao, Yuxin Zhang +8
The growing volume of academic papers has made it increasingly difficult for researchers to efficiently extract key information. While large language models (LLMs) based agents are…
Graph-based Approaches and Functionalities in Retrieval-Augmented Generation: A Comprehensive Survey
Zulun Zhu, Tiancheng Huang, Kai Wang +3
Large language models (LLMs) struggle with the factual error during inference due to the lack of sufficient training data and the most updated knowledge, leading to the hallucinati…
PaperGuide: Making Small Language-Model Paper-Reading Agents More Efficient
Zijian Wang, Tiancheng Huang, Hanqi Li +3
The accelerating growth of the scientific literature makes it increasingly difficult for researchers to track new advances through manual reading alone. Recent progress in large la…