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Machine Learning

Coherence Without Convergence: A New Protocol for Multi-Agent AI

Opening For the past year, most progress in multi-agent AI has followed a familiar pattern: Add more agents. Add more coordination. Watch...

Reddit - Artificial Intelligence · 1 min ·
Machine Learning

Week 6 AIPass update - answering the top questions from last post (file conflicts, remote models, scale)

Followup to last post with answers to the top questions from the comments. Appreciate everyone who jumped in. The most common one by a mi...

Reddit - Artificial Intelligence · 1 min ·
Llms

Honest ChatGPT vs Claude comparison after using both daily for a month

got tired of reading comparisons that were obvisously written by people who tested each tool for 20 minutes so i ran both at $20/month fo...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2512.03336] Single-Round Scalable Analytic Federated Learning
Machine Learning

[2512.03336] Single-Round Scalable Analytic Federated Learning

Abstract page for arXiv paper 2512.03336: Single-Round Scalable Analytic Federated Learning

arXiv - Machine Learning · 3 min ·
[2511.19413] UniGame: Turning a Unified Multimodal Model Into Its Own Adversary
Machine Learning

[2511.19413] UniGame: Turning a Unified Multimodal Model Into Its Own Adversary

Abstract page for arXiv paper 2511.19413: UniGame: Turning a Unified Multimodal Model Into Its Own Adversary

arXiv - Machine Learning · 4 min ·
[2511.14262] Object-Centric World Models for Causality-Aware Reinforcement Learning
Machine Learning

[2511.14262] Object-Centric World Models for Causality-Aware Reinforcement Learning

Abstract page for arXiv paper 2511.14262: Object-Centric World Models for Causality-Aware Reinforcement Learning

arXiv - Machine Learning · 4 min ·
[2511.04124] Decomposable Neuro Symbolic Regression
Machine Learning

[2511.04124] Decomposable Neuro Symbolic Regression

Abstract page for arXiv paper 2511.04124: Decomposable Neuro Symbolic Regression

arXiv - Machine Learning · 4 min ·
[2510.10102] PANTHER: Generative Pretraining Beyond Language for Sequential User Behavior Modeling
Llms

[2510.10102] PANTHER: Generative Pretraining Beyond Language for Sequential User Behavior Modeling

Abstract page for arXiv paper 2510.10102: PANTHER: Generative Pretraining Beyond Language for Sequential User Behavior Modeling

arXiv - Machine Learning · 4 min ·
[2510.08992] Constraints-of-Thought: A Framework for Constrained Reasoning in Language-Model-Guided Search
Llms

[2510.08992] Constraints-of-Thought: A Framework for Constrained Reasoning in Language-Model-Guided Search

Abstract page for arXiv paper 2510.08992: Constraints-of-Thought: A Framework for Constrained Reasoning in Language-Model-Guided Search

arXiv - Machine Learning · 4 min ·
[2510.06162] TabPFN-Wide: Continued Pre-Training for Extreme Feature Counts
Llms

[2510.06162] TabPFN-Wide: Continued Pre-Training for Extreme Feature Counts

Abstract page for arXiv paper 2510.06162: TabPFN-Wide: Continued Pre-Training for Extreme Feature Counts

arXiv - Machine Learning · 4 min ·
[2510.05825] Mitigating Premature Exploitation in Particle-based Monte Carlo for Inference-Time Scaling
Llms

[2510.05825] Mitigating Premature Exploitation in Particle-based Monte Carlo for Inference-Time Scaling

Abstract page for arXiv paper 2510.05825: Mitigating Premature Exploitation in Particle-based Monte Carlo for Inference-Time Scaling

arXiv - Machine Learning · 4 min ·
[2510.04618] Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Llms

[2510.04618] Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models

Abstract page for arXiv paper 2510.04618: Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models

arXiv - Machine Learning · 4 min ·
[2510.03904] LLM as an Algorithmist: Enhancing Anomaly Detectors via Programmatic Synthesis
Llms

[2510.03904] LLM as an Algorithmist: Enhancing Anomaly Detectors via Programmatic Synthesis

Abstract page for arXiv paper 2510.03904: LLM as an Algorithmist: Enhancing Anomaly Detectors via Programmatic Synthesis

arXiv - Machine Learning · 4 min ·
[2510.01349] To Augment or Not to Augment? Diagnosing Distributional Symmetry Breaking
Machine Learning

[2510.01349] To Augment or Not to Augment? Diagnosing Distributional Symmetry Breaking

Abstract page for arXiv paper 2510.01349: To Augment or Not to Augment? Diagnosing Distributional Symmetry Breaking

arXiv - Machine Learning · 4 min ·
[2509.22381] Enhancing Credit Risk Prediction: A Multi-stage Ensemble Pipeline
Machine Learning

[2509.22381] Enhancing Credit Risk Prediction: A Multi-stage Ensemble Pipeline

Abstract page for arXiv paper 2509.22381: Enhancing Credit Risk Prediction: A Multi-stage Ensemble Pipeline

arXiv - Machine Learning · 4 min ·
[2509.19601] Learning Genetic Circuit Modules with Neural Networks: Full Version
Machine Learning

[2509.19601] Learning Genetic Circuit Modules with Neural Networks: Full Version

Abstract page for arXiv paper 2509.19601: Learning Genetic Circuit Modules with Neural Networks: Full Version

arXiv - Machine Learning · 4 min ·
[2509.13007] ReTrack: Data Unlearning in Diffusion Models through Redirecting the Denoising Trajectory
Machine Learning

[2509.13007] ReTrack: Data Unlearning in Diffusion Models through Redirecting the Denoising Trajectory

Abstract page for arXiv paper 2509.13007: ReTrack: Data Unlearning in Diffusion Models through Redirecting the Denoising Trajectory

arXiv - Machine Learning · 3 min ·
[2509.17889] GaussianPSL: Soft partitioning for complex PSL problem
Machine Learning

[2509.17889] GaussianPSL: Soft partitioning for complex PSL problem

Abstract page for arXiv paper 2509.17889: GaussianPSL: Soft partitioning for complex PSL problem

arXiv - Machine Learning · 3 min ·
[2509.12573] No Need for Learning to Defer? A Training Free Deferral Framework to Multiple Experts through Conformal Prediction
Machine Learning

[2509.12573] No Need for Learning to Defer? A Training Free Deferral Framework to Multiple Experts through Conformal Prediction

Abstract page for arXiv paper 2509.12573: No Need for Learning to Defer? A Training Free Deferral Framework to Multiple Experts through C...

arXiv - Machine Learning · 4 min ·
[2509.04959] On the Normalization of Confusion Matrices: Methods and Geometric Interpretations
Machine Learning

[2509.04959] On the Normalization of Confusion Matrices: Methods and Geometric Interpretations

Abstract page for arXiv paper 2509.04959: On the Normalization of Confusion Matrices: Methods and Geometric Interpretations

arXiv - Machine Learning · 3 min ·
[2509.03417] Initialization Schemes for Kolmogorov-Arnold Networks: An Empirical Study
Machine Learning

[2509.03417] Initialization Schemes for Kolmogorov-Arnold Networks: An Empirical Study

Abstract page for arXiv paper 2509.03417: Initialization Schemes for Kolmogorov-Arnold Networks: An Empirical Study

arXiv - Machine Learning · 3 min ·
[2508.13773] PENGUIN: Enhancing Transformer with Periodic-Nested Group Attention for Long-term Time Series Forecasting
Machine Learning

[2508.13773] PENGUIN: Enhancing Transformer with Periodic-Nested Group Attention for Long-term Time Series Forecasting

Abstract page for arXiv paper 2508.13773: PENGUIN: Enhancing Transformer with Periodic-Nested Group Attention for Long-term Time Series F...

arXiv - Machine Learning · 3 min ·
[2508.04329] Forgetting: A New Mechanism Towards Better Large Language Model Fine-tuning
Llms

[2508.04329] Forgetting: A New Mechanism Towards Better Large Language Model Fine-tuning

Abstract page for arXiv paper 2508.04329: Forgetting: A New Mechanism Towards Better Large Language Model Fine-tuning

arXiv - Machine Learning · 4 min ·
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