On the Fly Detection of Root Causes from Observed Data with Application to IT Systems
The article introduces a novel structural causal model and algorithm designed for the rapid detection of anomalies’…
ACTER: Diverse and Actionable Counterfactual Sequences for Explaining and Diagnosing RL Policies
This academic paper presents ACTER (Actionable CounTerfactual Sequences for Explaining Reinforcement Learning Outcomes), a new algorithm for…
Introspective Planning: Guiding Language-Enabled Agents to Refine Their Own Uncertainty
This academic paper discusses the concept of introspective planning for Large Language Models (LLMs). These models, which…
The Quantified Boolean Bayesian Network: Theory and Experiments with a Logical Graphical Model
Greg Coppola’s academic article titled ‘The Quantified Boolean Bayesian Network: Theory and Experiments with a Logical Graphical…
Predictive representations: building blocks of intelligence
The paper integrates the theory of reinforcement learning with work on cognition and neuroscience. It pays special…
Understanding the Weakness of Large Language Model Agents within a Complex Android Environment
The paper discusses the challenges faced by Large Language Models (LLMs) when applied to general-purpose software systems…
DAPlankton: Benchmark Dataset for Multi-instrument Plankton Recognition via Fine-grained Domain Adaptation
The article introduces a new dataset called DAPlankton that is aimed at developing and benchmarking domain adaptation…
An Ordinal Regression Framework for a Deep Learning Based Severity Assessment for Chest Radiographs
This research investigates using ordinal regression methods for categorizing disease severity in chest radiographs. The researchers propose…
Jacquard V2: Refining Datasets using the Human In the Loop Data Correction Method
The paper highlights the importance of large-scale datasets for training models in industrial automation, specifically vision-based robotic…
You Only Need One Color Space: An Efficient Network for Low-light Image Enhancement
The article presents a novel approach to Low-Light Image Enhancement (LLIE) using a new trainable color space,…