1 citations · 1 across the 7 of their papers we have counts for
8 papers
The Token Tax of Epistemic Accuracy: Comparing RAG and Long-Context Architectures for Document-Grounded Generative AI Applications
Austin Hamilton, Ryan Singh, Michael Wise +6
Document-grounded assistants built on large language models are increasingly used in high-stakes, knowledge-intensive work. Their usefulness, however, may depend on how evidence is…
A Multimodal Manufacturing Safety Chatbot: Knowledge Base Design, Benchmark Development, and Evaluation of Multiple RAG Approaches
Ryan Singh, Austin Hamilton, Amanda White +8
Ensuring worker safety remains a critical challenge in modern manufacturing environments. Industry 5.0 reorients the prevailing manufacturing paradigm toward more human-centric ope…
JPC: Flexible Inference for Predictive Coding Networks in JAX
Francesco Innocenti, Paul Kinghorn, Will Yun-Farmbrough +3
We introduce JPC, a JAX library for training neural networks with Predictive Coding. JPC provides a simple, fast and flexible interface to train a variety of PC networks (PCNs) inc…
Learning in Hybrid Active Inference Models
Poppy Collis, Ryan Singh, Paul F Kinghorn +1
An open problem in artificial intelligence is how systems can flexibly learn discrete abstractions that are useful for solving inherently continuous problems. Previous work in comp…
Hybrid Recurrent Models Support Emergent Descriptions for Hierarchical Planning and Control
Poppy Collis, Ryan Singh, Paul F Kinghorn +1
An open problem in artificial intelligence is how systems can flexibly learn discrete abstractions that are useful for solving inherently continuous problems. Previous work has dem…
Only Strict Saddles in the Energy Landscape of Predictive Coding Networks?
Francesco Innocenti, El Mehdi Achour, Ryan Singh +1
Predictive coding (PC) is an energy-based learning algorithm that performs iterative inference over network activities before updating weights. Recent work suggests that PC can con…
Understanding Predictive Coding as an Adaptive Trust-Region Method
Francesco Innocenti, Ryan Singh, Christopher L. Buckley
Predictive coding (PC) is a brain-inspired local learning algorithm that has recently been suggested to provide advantages over backpropagation (BP) in biologically relevant scenar…
Attention: Marginal Probability is All You Need?
Ryan Singh, Christopher L. Buckley
Attention mechanisms are a central property of cognitive systems allowing them to selectively deploy cognitive resources in a flexible manner. Attention has been long studied in th…