5 papers indexed
Shujin Wu, Cheng Qian, Xiusi Chen, Heng Ji
Test-time scaling through iterative self-evolution with environment feedback, as demonstrated by AlphaEvolve, shows remarkable performance gains. We hypothesize that the success of such evolution frameworks hinges on meta-skills, such as self-reflection with environment feedback,…
A specialist tolerates blind spots that a generalist does not. Usually this is treated as a cost to be minimized. We treat it as a design variable: a deficiency can be kept because it pays and removed on demand in the rare situation where it would be fatal, by routing to a compen…
We report a pre-registered, two-part experiment on small economies of frontier language-model agents (Claude Opus 4.8), testing two quantitative predictions about coupled multi-agent systems: an information-theoretic capacity region for wealth growth under market coupling, and a…
Zhongyang Li, Yaqian Li, Faming Fang, Rinyoichi Takezoe, Zi-Hao Bo, Cheng Qian, et al.
Multimodal large language models (MLLMs) typically employ resampling-based projectors to transform dense visual features into a compact token sequence for language modeling. Most existing resamplers adopt a single, fixed aggregation scope via global cross-attention, which can blu…
Junzhe Jiang, Rongnian Tang, Weian Kang, Zengcai Xu, Cheng Qian
One of the basic requirements of an automated parking system is to quickly and accurately detect parking spaces. With the development of deep convolutional neural networks, parking space detection systems are becoming increasingly mature. However, the existing detection systems a…