28 papers
FedSceneX: Time-to-Target Orchestration for Same-Scene Multimodal Federated Edge Learning
Dhe Yeong Tchalla, Beining Wu, Jun Huang +2
Federated learning at the sensing edge is typically evaluated by communication rounds, yet a round does not represent a fixed amount of work. Even on identical hardware, the method…
CrystalMem: Elastic Memory for Self-Evolving LLM Agents via Knowledge Crystallization
Beining Wu, Jun Huang
Memory for self-evolving large language model (LLM) agents is often provisioned as if its byte budget only grows. Cloud platforms, however, adjust quotas with load and cost, and we…
INFUSER: Influence-Guided Self-Evolution Improves Reasoning
Siyu Chen, Miao Lu, Beining Wu +7
Self-evolution offers a scalable path to stronger reasoning: a pretrained language model improves itself with only minimal external supervision. Yet existing methods either depend…
Forget to Improve: On-Device LLM-Agent Continual Learning via Budget-Curated Memory
Beining Wu, Zihao Ding, Jun Huang +1
On-device language-model agents improve by accumulating experience in retrieved memory rather than by updating weights. This memory is hard-bounded and exposed: it consumes RAM and…
MorVess: Morphology-Aware Pulmonary Vessel Segmentation Network
Fuyou Mao, Yifei Chen, Beining Wu +9
Accurate pulmonary vessel segmentation remains challenging due to the sparse, tortuous, and multi-scale nature of vascular structures, where small branches are easily lost and topo…
HEad and neCK TumOR (HECKTOR) 2025: Benchmark of Segmentation, Diagnosis, and Prognosis in Multimodal PET/CT
Numan Saeed, Salma Hassan, Shahad Hardan +27
Head and neck cancers (HNC) represent a significant global health burden, with accurate tumor delineation being essential for effective radiotherapy planning. The complexity of the…