4 papers
Partial Information Decomposition via Normalizing Flows in Latent Gaussian Distributions
Wenyuan Zhao, Adithya Balachandran, Chao Tian +1
The study of multimodality has garnered significant interest in fields where the analysis of interactions among multiple information sources can enhance predictive modeling, data f…
What One Cannot, Two Can: Two-Layer Transformers Provably Represent Induction Heads on Any-Order Markov Chains
Chanakya Ekbote, Marco Bondaschi, Nived Rajaraman +4
In-context learning (ICL) is a hallmark capability of transformers, through which trained models learn to adapt to new tasks by leveraging information from the input context. Prior…
QoQ-Med: Building Multimodal Clinical Foundation Models with Domain-Aware GRPO Training
Wei Dai, Peilin Chen, Chanakya Ekbote +1
Clinical decision-making routinely demands reasoning over heterogeneous data, yet existing multimodal language models (MLLMs) remain largely vision-centric and fail to generalize a…
CLIMB: Data Foundations for Large Scale Multimodal Clinical Foundation Models
Wei Dai, Peilin Chen, Malinda Lu +4
Recent advances in clinical AI have enabled remarkable progress across many clinical domains. However, existing benchmarks and models are primarily limited to a small set of modali…