Machine Learning

ML algorithms, training, and inference

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Machine Learning

[P] Trained a small BERT on 276K Kubernetes YAMLs using tree positional encoding instead of sequential

I trained a BERT-style transformer on 276K Kubernetes YAML files, replacing standard positional encoding with learned tree coordinates (d...

Reddit - Machine Learning · 1 min ·
Machine Learning

I am doing a multi-model graph database in pure Rust with Cypher, SQL, Gremlin, and native GNN looking for extreme speed and performance

Hi guys, I'm a PhD student in Applied AI and I've been building an embeddable graph database engine from scratch in Rust. I'd love feedba...

Reddit - Artificial Intelligence · 1 min ·
Llms

Chatgpt vs purpose built ai for cre underwriting: which one can finish the job?

I keep seeing people recommend chatgpt for financial modeling and I need to push back because I spent a month testing it for multifamily ...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2505.24840] The LLM Bottleneck: Why Open-Source Vision LLMs Struggle with Hierarchical Visual Recognition
Llms

[2505.24840] The LLM Bottleneck: Why Open-Source Vision LLMs Struggle with Hierarchical Visual Recognition

Abstract page for arXiv paper 2505.24840: The LLM Bottleneck: Why Open-Source Vision LLMs Struggle with Hierarchical Visual Recognition

arXiv - Machine Learning · 3 min ·
[2306.04810] Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry
Machine Learning

[2306.04810] Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry

Abstract page for arXiv paper 2306.04810: Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neur...

arXiv - Machine Learning · 4 min ·
[2502.05228] Physics-Informed Evolution: An Evolutionary Framework for Solving Quantum Control Problems Involving the Schrödinger Equation
Machine Learning

[2502.05228] Physics-Informed Evolution: An Evolutionary Framework for Solving Quantum Control Problems Involving the Schrödinger Equation

Abstract page for arXiv paper 2502.05228: Physics-Informed Evolution: An Evolutionary Framework for Solving Quantum Control Problems Invo...

arXiv - AI · 4 min ·
[2006.09534] Discriminative reconstruction via simultaneous dense and sparse coding
Machine Learning

[2006.09534] Discriminative reconstruction via simultaneous dense and sparse coding

Abstract page for arXiv paper 2006.09534: Discriminative reconstruction via simultaneous dense and sparse coding

arXiv - Machine Learning · 4 min ·
[2410.15281] LLM4AD: Large Language Models for Autonomous Driving -- Concept, Review, Benchmark, Experiments, and Future Trends
Llms

[2410.15281] LLM4AD: Large Language Models for Autonomous Driving -- Concept, Review, Benchmark, Experiments, and Future Trends

Abstract page for arXiv paper 2410.15281: LLM4AD: Large Language Models for Autonomous Driving -- Concept, Review, Benchmark, Experiments...

arXiv - AI · 4 min ·
[2410.10700] LLMs know their vulnerabilities: Uncover Safety Gaps through Natural Distribution Shifts
Llms

[2410.10700] LLMs know their vulnerabilities: Uncover Safety Gaps through Natural Distribution Shifts

Abstract page for arXiv paper 2410.10700: LLMs know their vulnerabilities: Uncover Safety Gaps through Natural Distribution Shifts

arXiv - AI · 4 min ·
[2408.13366] CodeRefine: A Pipeline for Enhancing LLM-Generated Code Implementations of Research Papers
Llms

[2408.13366] CodeRefine: A Pipeline for Enhancing LLM-Generated Code Implementations of Research Papers

Abstract page for arXiv paper 2408.13366: CodeRefine: A Pipeline for Enhancing LLM-Generated Code Implementations of Research Papers

arXiv - Machine Learning · 3 min ·
[2404.05290] MindSet: Vision. A toolbox for testing DNNs on key psychological experiments
Machine Learning

[2404.05290] MindSet: Vision. A toolbox for testing DNNs on key psychological experiments

Abstract page for arXiv paper 2404.05290: MindSet: Vision. A toolbox for testing DNNs on key psychological experiments

arXiv - AI · 4 min ·
[2401.11605] Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers
Machine Learning

[2401.11605] Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers

Abstract page for arXiv paper 2401.11605: Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers

arXiv - Machine Learning · 3 min ·
[2402.12760] A User-Friendly Framework for Generating Model-Preferred Prompts in Text-to-Image Synthesis
Machine Learning

[2402.12760] A User-Friendly Framework for Generating Model-Preferred Prompts in Text-to-Image Synthesis

Abstract page for arXiv paper 2402.12760: A User-Friendly Framework for Generating Model-Preferred Prompts in Text-to-Image Synthesis

arXiv - AI · 4 min ·
[2603.19091] Position: Spectral GNNs Are Neither Spectral Nor Superior for Node Classification
Machine Learning

[2603.19091] Position: Spectral GNNs Are Neither Spectral Nor Superior for Node Classification

Abstract page for arXiv paper 2603.19091: Position: Spectral GNNs Are Neither Spectral Nor Superior for Node Classification

arXiv - Machine Learning · 4 min ·
[2603.24402] AI-Supervisor: Autonomous AI Research Supervision via a Persistent Research World Model
Machine Learning

[2603.24402] AI-Supervisor: Autonomous AI Research Supervision via a Persistent Research World Model

Abstract page for arXiv paper 2603.24402: AI-Supervisor: Autonomous AI Research Supervision via a Persistent Research World Model

arXiv - AI · 4 min ·
[2603.16951] Minimum-Action Learning: Energy-Constrained Symbolic Model Selection for Physical Law Identification from Noisy Data
Machine Learning

[2603.16951] Minimum-Action Learning: Energy-Constrained Symbolic Model Selection for Physical Law Identification from Noisy Data

Abstract page for arXiv paper 2603.16951: Minimum-Action Learning: Energy-Constrained Symbolic Model Selection for Physical Law Identific...

arXiv - Machine Learning · 4 min ·
[2603.23610] Environment Maps: Structured Environmental Representations for Long-Horizon Agents
Llms

[2603.23610] Environment Maps: Structured Environmental Representations for Long-Horizon Agents

Abstract page for arXiv paper 2603.23610: Environment Maps: Structured Environmental Representations for Long-Horizon Agents

arXiv - AI · 4 min ·
[2601.21747] Temporal Sepsis Modeling: a Fully Interpretable Relational Way
Machine Learning

[2601.21747] Temporal Sepsis Modeling: a Fully Interpretable Relational Way

Abstract page for arXiv paper 2601.21747: Temporal Sepsis Modeling: a Fully Interpretable Relational Way

arXiv - AI · 3 min ·
[2603.08561] RetroAgent: From Solving to Evolving via Retrospective Dual Intrinsic Feedback
Llms

[2603.08561] RetroAgent: From Solving to Evolving via Retrospective Dual Intrinsic Feedback

Abstract page for arXiv paper 2603.08561: RetroAgent: From Solving to Evolving via Retrospective Dual Intrinsic Feedback

arXiv - AI · 4 min ·
[2601.18420] Gradient Regularized Natural Gradients
Machine Learning

[2601.18420] Gradient Regularized Natural Gradients

Abstract page for arXiv paper 2601.18420: Gradient Regularized Natural Gradients

arXiv - AI · 4 min ·
[2511.07436] Analysing Environmental Efficiency in AI for X-Ray Diagnosis
Llms

[2511.07436] Analysing Environmental Efficiency in AI for X-Ray Diagnosis

Abstract page for arXiv paper 2511.07436: Analysing Environmental Efficiency in AI for X-Ray Diagnosis

arXiv - AI · 4 min ·
[2601.02856] Electricity Price Forecasting: Bridging Linear Models, Neural Networks and Online Learning
Machine Learning

[2601.02856] Electricity Price Forecasting: Bridging Linear Models, Neural Networks and Online Learning

Abstract page for arXiv paper 2601.02856: Electricity Price Forecasting: Bridging Linear Models, Neural Networks and Online Learning

arXiv - Machine Learning · 4 min ·
[2601.00428] Interpretable ML Under the Microscope: Performance, Meta-Features, and the Regression-Classification Predictability Gap
Machine Learning

[2601.00428] Interpretable ML Under the Microscope: Performance, Meta-Features, and the Regression-Classification Predictability Gap

Abstract page for arXiv paper 2601.00428: Interpretable ML Under the Microscope: Performance, Meta-Features, and the Regression-Classific...

arXiv - Machine Learning · 4 min ·
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