arxiv
PublishedJune 17, 2026 at 4:00 AM
The Critical Role of Model Selection in Causal Inference: A Comparative Analysis of Classification Models within the InferBERT Framework for Pharmacovigilance
Publisher summary· verbatim
arXiv:2606.17113v1 Announce Type: cross Abstract: Distinguishing causal adverse drug events (ADEs) from spurious correlations remains a central challenge in pharmacovigilance. The InferBERT framework integrates transformer models with Do-calculus, but its success hinges on the underlying classificat
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivBeyond a Single Direction: Chain-of-Thought Disrupts Simple Steering of Refusal2harxivRobustSpeechFlow: Learning Robust Text-to-Speech Trajectories via Augmentation-based Contrastive Flow Matching2harxivAn Auto-Scaling Approach for Serverless Environments Based on a Multi-Expert Consensus Mechanism2harxivCache-Aware Prompt Compression:A Two-Tier Cost Model for LLM API Caching2hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗