8 citations · 8 across the 3 of their papers we have counts for
5 papers
HugAgent: A Human Simulation Benchmark for Individual-Level Reasoning
Chance Jiajie Li, Zhenze Mo, Yuhan Tang +11
Simulating human reasoning in open-ended tasks has long been a central aspiration in AI and cognitive science. While large language models now approximate human responses at scale,…
Object-level Correlation for Few-Shot Segmentation
Chunlin Wen, Yu Zhang, Jie Fan +5
Few-shot semantic segmentation (FSS) aims to segment objects of novel categories in the query images given only a few annotated support samples. Existing methods primarily build th…
Simulating Society Requires Simulating Thought
Chance Jiajie Li, Jiayi Wu, Zhenze Mo +10
Simulating society with large language models (LLMs), we argue, requires more than generating plausible behavior; it demands cognitively grounded reasoning that is structured, revi…
Toward Aligning Human and Robot Actions via Multi-Modal Demonstration Learning
Azizul Zahid, Jie Fan, Farong Wang +3
Understanding action correspondence between humans and robots is essential for evaluating alignment in decision-making, particularly in human-robot collaboration and imitation lear…
Towards Real Zero-Shot Camouflaged Object Segmentation without Camouflaged Annotations
Cheng Lei, Jie Fan, Xinran Li +4
Camouflaged Object Segmentation (COS) faces significant challenges due to the scarcity of annotated data, where meticulous pixel-level annotation is both labor-intensive and costly…