2 citations · 4 across the 15 of their papers we have counts for
9 papers · 1 filter
Causal Information Exchange as a Necessary Condition for Adaptive Regulation: A Perturbational Framework for Life and Agency
Brian LuValle, Abicumaran Uthamacumaran, Hector Zenil
Information exchange can support living organisation without providing a sufficient criterion for life. We develop a perturbational framework that distinguishes causal transmission…
Reconstruction of Geometric and Structural Aspects of Undeciphered Messages by Information-theoretic Methods
Hector Zenil, Abicumaran Uthamacumaran
In previous work, we established sufficient conditions for recovering geometry and topology from non-random information, demonstrating reconstruction with the Arecibo message. Unde…
What Can Language Models Inherit from Solomonoff Induction? Limits, Attainable Properties, and What Served Conditionals Reveal
Luan Ozelim, Abicumaran Uthamacumaran, Hector Zenil
A familiar line of reasoning runs as follows: language models are flexible approximators trained under a strictly proper loss, so scale brings them closer to Solomonoff induction,…
Learning 3D biophysical cell properties from 2D images and cell-population statistics
Santiago Hernández-Orozco, Hector Zenil
Inferring 3D cellular properties from 2D microscopy is difficult when a reference instrument reports only population statistics rather than labels for individual cells. Here we dev…
Enhancing Clinical Decision Support and Differential Diagnosis with Knowledge Graphs, and Retrieval Augmented Generation in Generative AI
Henri Feto, Abicumaran Uthamacumaran, Hector Zenil
Diagnostic error carries a burden, while unconstrained large language models (LLMs) remain vulnerable to hallucination and weak integration of quantitative laboratory dynamics. We…
Measuring in-context algorithmic reasoning in language models against an exact Bayes-optimal reference
Luan Ozelim, Hector Zenil
Whether large language models perform algorithmic inference or pattern completion is hard to test, because most benchmarks supply answers but no distributional reference for what t…
Algorithmic Information Dynamics of Learning: A Certified, Differentiable Complexity Controller for Grokking
Luan Ozelim, Hector Zenil, Abicumaran Uthamacumaran
Algorithmic Information Dynamics (AID) studies systems by perturbing them and measuring changes in algorithmic complexity, but its usual estimator, the Block Decomposition Method,…
Patterns in Individual Blood Count Trajectories in the UK Biobank Characterise Disease-Specific Signatures and Anticipate Pan-Cancer Risk
Riya Nagar, Abicumaran Uthamacumaran, Adelaide de Vecchi +1
We investigate the longitudinal behaviour of blood markers from common haematological tests as a marker of disease and as a function of disease progression in a variety of conditio…
Large Language Models are Shannon Lossy Compressors Not Solomonoff Induction Estimators: Self-improvement and Singularity Are Not Near Without Symbolic Model Synthesis
Hector Zenil, Abicumaran Uthamacumaran, Luan Ozelim
We connect two questions in Algorithmic Information Theory (AIT), Machine Learning (ML) and Artificial General Intelligence (AGI): whether LLMs estimate Solomonoff induction, and w…