Fundamental engineering principles can help identify disease biomarkers more quickly
phys.org·16h
⚙️systems theory
Joy & Curiosity #57
registerspill.thorstenball.com·2h
🏺ZIP Archaeology
Trillion-Scale Goldbach Verification on Consumer Hardware -novel Algorithm [pdf]
zenodo.org·2d·
Discuss: Hacker News
🔢Reed-Solomon Math
Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning
arxiviq.substack.com·2d·
Discuss: Substack
💻Local LLMs
A Proof of the Riemann Hypothesis
dev.to·3d·
Discuss: DEV
⚔️Lean Theorem
Categorical Invariants of Learning Dynamics
arxiv.org·5d
🕸️Algebraic Topology
Revisiting Long-context Modeling from Context Denoising Perspective
arxiv.org·4d
🔢Denotational Semantics
Conformalized Gaussian processes for online uncertainty quantification over graphs
arxiv.org·4d
📈Spectral Graph Theory
The Alignment Auditor: A Bayesian Framework for Verifying and Refining LLM Objectives
arxiv.org·4d
💻Local LLMs
KEO: Knowledge Extraction on OMIn via Knowledge Graphs and RAG for Safety-Critical Aviation Maintenance
arxiv.org·4d
🧠Intelligence Compression
XRPO: Pushing the limits of GRPO with Targeted Exploration and Exploitation
arxiv.org·3d
🎯Performance Proofs
On the Pure Quantum Polynomial Hierarchy and Quantified Hamiltonian Complexity
arxiv.org·3d
⚛️Quantum Algorithms
Automated Anomaly Detection in Account Takeover via Multi-Modal Graph Neural Network Fusion
dev.to·1d·
Discuss: DEV
🔍Vector Forensics
Counterfactual Identifiability via Dynamic Optimal Transport
arxiv.org·2d
🔍Vector Forensics
A Trustworthy Industrial Fault Diagnosis Architecture Integrating Probabilistic Models and Large Language Models
arxiv.org·5d
🧠Machine Learning
Automated Design of Peptide-Based Drug Candidates via Constrained Generative Adversarial Networks
dev.to·1d·
Discuss: DEV
🔍Vector Forensics
Feasibility-Aware Decision-Focused Learning for Predicting Parameters in the Constraints
arxiv.org·5d
🧠Machine Learning
A Noise Resilient Approach for Robust Hurst Exponent Estimation
arxiv.org·5d
🧠Machine Learning
LLC Artificial Intelligence Trained to Lie by Omission
dev.to·19h·
Discuss: DEV
📏Code Metrics
Evaluating the Sensitivity of LLMs to Harmful Contents in Long Input
arxiv.org·4d
📝ABNF Extensions