2 citations · 3 across the 8 of their papers we have counts for
4 papers · 1 filter
Later Is Better: Token Reduction for ViTs Under Distribution Shift
Hyeongheon Cha, Hyungjun Yoon, Sung-Ju Lee
Training-free token reduction accelerates vision transformers by removing redundant tokens across layers, recovering most of the original accuracy at a fraction of the compute. The…
TimeNet: An Extensible Unified Data Infrastructure for Next-Generation Temporal Foundation Models
Martin Maritsch, Timo Stoffregen, Thomas Kaar +36
Temporal Foundation Models (TFMs) aim to generalize across domains, datasets, and tasks. Yet, their development remains constrained by fragmented, task-specific data formats, annot…
Wearable Foundation Models Should Go Beyond Static Encoders
Yu Yvonne Wu, Yuwei Zhang, Hyungjun Yoon +8
Wearable foundation models (WFMs), trained on large volumes of data collected by affordable, always-on devices, have demonstrated strong performance on short-term, well-defined hea…
ConSensus: Multi-Agent Collaboration for Multimodal Sensing
Hyungjun Yoon, Mohammad Malekzadeh, Sung-Ju Lee +2
Large language models (LLMs) are increasingly grounded in sensor data to perceive and reason about human physiology and the physical world. However, accurately interpreting heterog…