Research & Innovation

Global: New VAE-Driven Inversion Method Enhances Fault Slip Prediction in CO₂ Storage SimulationsA team of scientists has introduced a variational autoencoder (VAE)–based data‑space inversion (DSI) framework that directly infers pressure,…

Global: Study Unifies Bias‑Correction Methods for LLM‑as‑Judge EvaluationsResearchers have introduced a unified statistical framework that assesses and improves the reliability of large language models (LLMs) when they are used as…

Global: New Hierarchical Teacher Framework Boosts Multi-Agent RL PerformanceIn a paper posted to arXiv in January 2026, researchers introduce a novel knowledge‑distillation approach designed to accelerate multi‑agent reinforcement learning (MARL)…

Global: Study Links Grokking to Norm Minimization on Zero-Loss ManifoldResearchers led by Tiberiu Musat released a preprint on arXiv that proposes a new theoretical explanation for the delayed generalization phenomenon…

Global: Transformer-Based Model Enhances Multi-step Forecasting on Dynamic GraphsResearchers introduced an end‑to‑end dynamic edge‑biased spatiotemporal model that processes time‑series node attributes alongside evolving adjacency matrices to predict several future steps…

Global: MO-GRPO Introduces Automatic Reward Normalization for Multi-Objective Reinforcement LearningA research team has presented MO-GRPO, an extension of Group Relative Policy Optimization, to mitigate reward‑hacking in multi‑objective reinforcement learning. The…

Global: Study Shows Topology‑Enhanced Ontology Neural Networks Boost Constraint SatisfactionA research paper posted to arXiv on January 8, 2026 presents a novel framework that blends topological information with neural‑network‑based reasoning…

Global: New Retrieval‑Augmented Model Improves Long‑Horizon Glucose ForecastingResearchers have introduced GlyRAG, a retrieval‑augmented forecasting framework that leverages large language models to contextualize continuous glucose monitor (CGM) data, aiming to improve…

Global: Twin Neural Networks Enable Inversion of Non-Injective FunctionsResearchers led by Sebastian J. Wetzel submitted a new preprint to arXiv on Jan. 8, 2026 that proposes a deterministic framework for inverting non‑injective…

Global: Bayesian Optimization Framework Enhances Gaussian Process Kernel SelectionResearchers introduced a new Bayesian optimization approach for choosing covariance kernels in Gaussian Process (GP) regression in a preprint posted to arXiv…