We have 4 of 15 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
BALMS is the first systematic benchmark of LLM-based agentic systems for longitudinal mental health sensing and highlights the need for longitudinal mental health agents that selectively retrieve history, ground temporal evidence, and reason over interpretable behavioral features.
SLIP (Sensor Language-Informed Pretraining), an open-source framework for learning language-aligned representations that generalize across diverse sensor setups, is introduced, offering broad implications for the development of sensor-language models.
TimeThink, a synthetic framework for eliciting compositional timeseries reasoning that employs a reinforcement learning with verifiable rewards (RLVR) training strategy that encourages explicit reasoning, significantly outperforms strong baselines on both synthetic and real-world benchmarks.
It is suggested that hip-based pretraining provides a useful starting point for wrist deployment, while highlighting the need for wrist-specific adaptation to handle higher signal variability.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
