COM integrates geometric constraints into token initialization and training to preserve continuity and ordinality in time series tokens, improving token-based TS-LLM performance on benchmarks.
Timemae: Self-supervised rep- resentations of time series with decoupled masked autoen- coders
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
representative citing papers
DT-Pose reformulates WiFi HPE as domain-consistent representation learning via temporal contrastive masked pretraining plus hybrid topology-constrained decoding to yield more accurate and realistic 2D/3D poses.