arXiv AI
Phorecaster365: A Human-Supervised Reference Architecture for Hybrid Pharmaceutical Sales Forecasting and Planning Decision Support
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arXiv AI
Jul 22
Do AI-Native Biotechs Need Departments? Benchmarking Company World Models for AI-Driven Drug Development
arXiv:2607. 18696v1 Announce Type: new Abstract: AI-native biotechnology companies are often designed by copying human biotech org charts into agent roles.
arXiv AI
2d ago
On the Divergence of Accuracy and Mechanism Consistency in Time Series World Models
The paper introduces a formal framework and benchmark for time‑series world models (TSWMs) that separates state, actions, and exogenous inputs, and defines a new metric called mechanism consistency to evaluate whether model predictions move in the expected direction when actions change. Experiments on eight public datasets show that using a frozen latent prediction space and gated output fusion improves prediction accuracy, while prediction error and mechanism consistency often diverge, with the best‑performing models sometimes failing to exhibit consistent directional responses. Adding a directional supervision loss significantly boosts mechanism consistency without affecting mean‑absolute error, providing a practical recipe for building more reliable TSWMs.
arXiv Machine Learning
Aug 5
Forecasting Revenue with its Customer-Base Drivers: When and Why Coordination Helps
arXiv:2608. 02911v1 Announce Type: new Abstract: Revenue forecasts guide acquisition budgets, demand planning, and customer-based valuations, yet an aggregate forecast does not show whether change reflects acquisition, repeat purchasing, spending per order, or offsetting movements.
arXiv Computation and Language
Sep 21
TrialAtlas: Multi-Agent Research Organization for Clinical Trial Design and Optimization
arXiv:2609.21859v1 Announce Type: new Abstract: Nearly 90% of drugs entering clinical development ultimately fail, despite billions of dollars in investment. Pharmaceutical companies therefore rely o...
arXiv Machine Learning
Jun 16
Forecasting Bacterial Antimicrobial Resistance Trends Using Machine Learning on WHO GLASS Surveillance Data: A Retrieval-Augmented Generation Approach for Policy Decision Support
arXiv:2602. 22673v2 Announce Type: replace Abstract: Background: Antimicrobial resistance (AMR) is a global health threat.
arXiv AI
Jul 22
Censoring-Aware In-Context Learning for Generalized Supplier Lead Time Estimation in Supply Chain Planning
arXiv:2607. 18530v1 Announce Type: cross Abstract: Supplier lead time forecasting is a central input to material requirements planning, inventory optimization, and supply chain risk management.