4 papers
LLM-Integrated Bayesian State Space Models for Multimodal Time-Series Forecasting
Sungjun Cho, Changho Shin, Suenggwan Jo +3
Forecasting in the real world requires integrating structured time-series data with unstructured textual information, but existing methods are architecturally limited by fixed inpu…
Reference-Specific Unlearning Metrics Can Hide the Truth: A Reality Check
Sungjun Cho, Dasol Hwang, Frederic Sala +3
Current unlearning metrics for generative models evaluate success based on reference responses or classifier outputs rather than assessing the core objective: whether the unlearned…
Quantifying Structure in CLIP Embeddings: A Statistical Framework for Concept Interpretation
Jitian Zhao, Chenghui Li, Frederic Sala +1
Concept-based approaches, which aim to identify human-understandable concepts within a model's internal representations, are a promising method for interpreting embeddings from dee…
Product Manifold Representations for Learning on Biological Pathways
Daniel McNeela, Frederic Sala, Anthony Gitter
Machine learning models that embed graphs in non-Euclidean spaces have shown substantial benefits in a variety of contexts, but their application has not been studied extensively i…