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Machine Learning

VulcanAMI Might Help

I open-sourced a large AI platform I built solo, working 16 hours a day, at my kitchen table, fueled by an inordinate degree of compulsio...

Reddit - Artificial Intelligence · 1 min ·
Machine Learning

[P] I tested Meta’s brain-response model on posts. It predicted the Elon one almost perfectly.

I built an experimental UI and visualization layer around Meta’s open brain-response model just to see whether this stuff actually works ...

Reddit - Machine Learning · 1 min ·
Machine Learning

[R] First open-source implementation of Hebbian fast-weight write-back for the BDH architecture

The BDH (Dragon Hatchling) paper (arXiv:2509.26507) describes a Hebbian synaptic plasticity mechanism where model weights update during i...

Reddit - Machine Learning · 1 min ·

All Content

[2603.21389] Task-Specific Efficiency Analysis: When Small Language Models Outperform Large Language Models
Llms

[2603.21389] Task-Specific Efficiency Analysis: When Small Language Models Outperform Large Language Models

Abstract page for arXiv paper 2603.21389: Task-Specific Efficiency Analysis: When Small Language Models Outperform Large Language Models

arXiv - Machine Learning · 3 min ·
[2603.21300] The Average Relative Entropy and Transpilation Depth determines the noise robustness in Variational Quantum Classifiers
Machine Learning

[2603.21300] The Average Relative Entropy and Transpilation Depth determines the noise robustness in Variational Quantum Classifiers

Abstract page for arXiv paper 2603.21300: The Average Relative Entropy and Transpilation Depth determines the noise robustness in Variati...

arXiv - Machine Learning · 4 min ·
[2603.21291] Closed-form conditional diffusion models for data assimilation
Machine Learning

[2603.21291] Closed-form conditional diffusion models for data assimilation

Abstract page for arXiv paper 2603.21291: Closed-form conditional diffusion models for data assimilation

arXiv - Machine Learning · 4 min ·
[2603.21139] Ontology-driven personalized information retrieval for XML documents
Machine Learning

[2603.21139] Ontology-driven personalized information retrieval for XML documents

Abstract page for arXiv paper 2603.21139: Ontology-driven personalized information retrieval for XML documents

arXiv - Machine Learning · 3 min ·
[2603.21042] Statistical Learning for Latent Embedding Alignment with Application to Brain Encoding and Decoding
Nlp

[2603.21042] Statistical Learning for Latent Embedding Alignment with Application to Brain Encoding and Decoding

Abstract page for arXiv paper 2603.21042: Statistical Learning for Latent Embedding Alignment with Application to Brain Encoding and Deco...

arXiv - Machine Learning · 3 min ·
[2603.20975] DiscoUQ: Structured Disagreement Analysis for Uncertainty Quantification in LLM Agent Ensembles
Llms

[2603.20975] DiscoUQ: Structured Disagreement Analysis for Uncertainty Quantification in LLM Agent Ensembles

Abstract page for arXiv paper 2603.20975: DiscoUQ: Structured Disagreement Analysis for Uncertainty Quantification in LLM Agent Ensembles

arXiv - Machine Learning · 3 min ·
[2603.20895] LLM Router: Prefill is All You Need
Llms

[2603.20895] LLM Router: Prefill is All You Need

Abstract page for arXiv paper 2603.20895: LLM Router: Prefill is All You Need

arXiv - Machine Learning · 3 min ·
[2603.20704] NDT: Non-Differential Transformer and Its Application to Sentiment Analysis
Machine Learning

[2603.20704] NDT: Non-Differential Transformer and Its Application to Sentiment Analysis

Abstract page for arXiv paper 2603.20704: NDT: Non-Differential Transformer and Its Application to Sentiment Analysis

arXiv - Machine Learning · 4 min ·
[2603.20696] High-dimensional online learning via asynchronous decomposition: Non-divergent results, dynamic regularization, and beyond
Nlp

[2603.20696] High-dimensional online learning via asynchronous decomposition: Non-divergent results, dynamic regularization, and beyond

Abstract page for arXiv paper 2603.20696: High-dimensional online learning via asynchronous decomposition: Non-divergent results, dynamic...

arXiv - Machine Learning · 3 min ·
[2603.20280] Mix-and-Match Pruning: Globally Guided Layer-Wise Sparsification of DNNs
Machine Learning

[2603.20280] Mix-and-Match Pruning: Globally Guided Layer-Wise Sparsification of DNNs

Abstract page for arXiv paper 2603.20280: Mix-and-Match Pruning: Globally Guided Layer-Wise Sparsification of DNNs

arXiv - Machine Learning · 3 min ·
[2603.20218] An experimental study of KV cache reuse strategies in chunk-level caching systems
Llms

[2603.20218] An experimental study of KV cache reuse strategies in chunk-level caching systems

Abstract page for arXiv paper 2603.20218: An experimental study of KV cache reuse strategies in chunk-level caching systems

arXiv - Machine Learning · 3 min ·
[2603.22155] RAMPAGE: RAndomized Mid-Point for debiAsed Gradient Extrapolation
Nlp

[2603.22155] RAMPAGE: RAndomized Mid-Point for debiAsed Gradient Extrapolation

Abstract page for arXiv paper 2603.22155: RAMPAGE: RAndomized Mid-Point for debiAsed Gradient Extrapolation

arXiv - Machine Learning · 3 min ·
[2603.22030] On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriors
Machine Learning

[2603.22030] On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriors

Abstract page for arXiv paper 2603.22030: On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriors

arXiv - Machine Learning · 3 min ·
[2603.22000] CRPS-Optimal Binning for Conformal Regression
Nlp

[2603.22000] CRPS-Optimal Binning for Conformal Regression

Abstract page for arXiv paper 2603.22000: CRPS-Optimal Binning for Conformal Regression

arXiv - Machine Learning · 3 min ·
[2603.21977] BOOST-RPF: Boosted Sequential Trees for Radial Power Flow
Machine Learning

[2603.21977] BOOST-RPF: Boosted Sequential Trees for Radial Power Flow

Abstract page for arXiv paper 2603.21977: BOOST-RPF: Boosted Sequential Trees for Radial Power Flow

arXiv - Machine Learning · 4 min ·
[2603.21743] CellFluxRL: Biologically-Constrained Virtual Cell Modeling via Reinforcement Learning
Machine Learning

[2603.21743] CellFluxRL: Biologically-Constrained Virtual Cell Modeling via Reinforcement Learning

Abstract page for arXiv paper 2603.21743: CellFluxRL: Biologically-Constrained Virtual Cell Modeling via Reinforcement Learning

arXiv - Machine Learning · 3 min ·
[2603.21567] Kolmogorov Complexity Bounds for LLM Steganography and a Perplexity-Based Detection Proxy
Llms

[2603.21567] Kolmogorov Complexity Bounds for LLM Steganography and a Perplexity-Based Detection Proxy

Abstract page for arXiv paper 2603.21567: Kolmogorov Complexity Bounds for LLM Steganography and a Perplexity-Based Detection Proxy

arXiv - Machine Learning · 3 min ·
[2603.21354] The Workload-Router-Pool Architecture for LLM Inference Optimization: A Vision Paper from the vLLM Semantic Router Project
Llms

[2603.21354] The Workload-Router-Pool Architecture for LLM Inference Optimization: A Vision Paper from the vLLM Semantic Router Project

Abstract page for arXiv paper 2603.21354: The Workload-Router-Pool Architecture for LLM Inference Optimization: A Vision Paper from the v...

arXiv - Machine Learning · 4 min ·
[2603.21056] Semi-Supervised Learning with Balanced Deep Representation Distributions
Machine Learning

[2603.21056] Semi-Supervised Learning with Balanced Deep Representation Distributions

Abstract page for arXiv paper 2603.21056: Semi-Supervised Learning with Balanced Deep Representation Distributions

arXiv - Machine Learning · 4 min ·
[2603.20984] Joint Surrogate Learning of Objectives, Constraints, and Sensitivities for Efficient Multi-objective Optimization of Neural Dynamical Systems
Machine Learning

[2603.20984] Joint Surrogate Learning of Objectives, Constraints, and Sensitivities for Efficient Multi-objective Optimization of Neural Dynamical Systems

Abstract page for arXiv paper 2603.20984: Joint Surrogate Learning of Objectives, Constraints, and Sensitivities for Efficient Multi-obje...

arXiv - Machine Learning · 4 min ·
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