Tootfinder

Fully Tensorized GPU-accelerated Multi-population Evolutionary Algorithm for Constrained Multiobjective Optimization Problems
Weixiong Huang, Rui Wang, Wenhua Li, Sheng Qi, Tianyu Luo, Delong Chen, Tao Zhang, Ling Wang
https://arxiv.org/abs/2509.19821

Fully Tensorized GPU-accelerated Multi-population Evolutionary Algorithm for Constrained Multiobjective Optimization Problems
Real world constrained multiobjective optimization problems (CMOPs) are prevalent and often come with stringent time-sensitive requirements. However, most contemporary constrained multiobjective evolutionary algorithms (CMOEAs) suffer from a number of drawbacks, including complex designs, low computational efficiency, and long convergence times, which are particularly pronounced when addressing time-sensitive CMOPs. Although research on accelerating evolutionary algorithms using GPU parallelism…

MOOM: Maintenance, Organization and Optimization of Memory in Ultra-Long Role-Playing Dialogues
Weishu Chen, Jinyi Tang, Zhouhui Hou, Shihao Han, Mingjie Zhan, Zhiyuan Huang, Delong Liu, Jiawei Guo, Zhicheng Zhao, Fei Su
https://arxiv.org/abs/2509.11860

MOOM: Maintenance, Organization and Optimization of Memory in Ultra-Long Role-Playing Dialogues
Memory extraction is crucial for maintaining coherent ultra-long dialogues in human-robot role-playing scenarios. However, existing methods often exhibit uncontrolled memory growth. To address this, we propose MOOM, the first dual-branch memory plugin that leverages literary theory by modeling plot development and character portrayal as core storytelling elements. Specifically, one branch summarizes plot conflicts across multiple time scales, while the other extracts the user's character profil…

🇺🇦 #NowPlaying on KEXP's #Early
Angie Stone:
🎵 Wish I Didn’t Miss You
#AngieStone
https://gregdelon.bandcamp.com/album/delon-angie-stone-wish-i-didn-t-miss-you-bootleg
https://open.spotify.com/track/3tZm76otWH20xzJC7icHCk

MCL-AD: Multimodal Collaboration Learning for Zero-Shot 3D Anomaly Detection
Gang Li, Tianjiao Chen, Mingle Zhou, Min Li, Delong Han, Jin Wan
https://arxiv.org/abs/2509.10282 ht…

MCL-AD: Multimodal Collaboration Learning for Zero-Shot 3D Anomaly Detection
Zero-shot 3D (ZS-3D) anomaly detection aims to identify defects in 3D objects without relying on labeled training data, making it especially valuable in scenarios constrained by data scarcity, privacy, or high annotation cost. However, most existing methods focus exclusively on point clouds, neglecting the rich semantic cues available from complementary modalities such as RGB images and texts priors. This paper introduces MCL-AD, a novel framework that leverages multimodal collaboration learnin…

Crosslisted article(s) found for cs.CG. https://arxiv.org/list/cs.CG/new
[1/1]:
- Robust Barycenters of Persistence Diagrams
Keanu Sisouk, Eloi Tanguy, Julie Delon, Julien Tierny

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[3/3]:
- MCL-AD: Multimodal Collaboration Learning for Zero-Shot 3D Anomaly Detection
Gang Li, Tianjiao Chen, Mingle Zhou, Min Li, Delong Han, Jin Wan

Emergent Inductance from Chiral Orbital Currents in a Bulk Ferrimagnet
Gang Cao, Hengdi Zhao, Yu Zhang, Alex Fix, Tristan R. Cao, Dhruva Ananth, Yifei Ni, Gabriel Schebel, Rahul Nandkishore, Itamar Kimchi, Hua Chen, Feng Ye, Lance E. DeLong
https://arxiv.org/abs/2509.05492

Emergent Inductance from Chiral Orbital Currents in a Bulk Ferrimagnet
We report the discovery of a new form of inductance in the bulk ferrimagnet Mn3Si2Te6, which features strong spin-orbit coupling, large magnetic anisotropy, and pronounced magnetoelastic interactions. Below its Curie temperature, Mn3Si2Te6 hosts chiral orbital currents (COC) that circulate within the crystal lattice and give rise to collective electronic behavior [1]. By applying a magnetic field along the hard c axis and driving the system with low-frequency currents, we uncover a giant induct…

Replaced article(s) found for math.MG. https://arxiv.org/list/math.MG/new
[1/1]:
- On rectifiability of Delone sets in intermediate regularity
Irene Inoquio-Renteria, Rodolfo Viera