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Llms

Moving Past "LLM Vibes" toward Structural Enforcement in AI Agents

We need to address the structural failure currently happening in the AI agent space: too many people are building a beautiful "pedestal" ...

Reddit - Artificial Intelligence · 1 min ·
Machine Learning

I am paying 50$ who help start AI model journey?

I am paying 50$ who help start AI model journey? I have basic face pics around 8-10. Now i need video contents with the same character. P...

Reddit - Artificial Intelligence · 1 min ·
Machine Learning

Built an open-source runtime layer to stop AI agents before they overspend or take risky actions — looking for feedback

If you’re experimenting with AI agents, you’ve probably run into this problem: once an agent starts calling tools, APIs, models, email sy...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2503.03206] An Analytical Theory of Spectral Bias in the Learning Dynamics of Diffusion Models
Machine Learning

[2503.03206] An Analytical Theory of Spectral Bias in the Learning Dynamics of Diffusion Models

Abstract page for arXiv paper 2503.03206: An Analytical Theory of Spectral Bias in the Learning Dynamics of Diffusion Models

arXiv - Machine Learning · 4 min ·
[2502.15567] Model Privacy: A Unified Framework for Understanding Model Stealing Attacks and Defenses
Machine Learning

[2502.15567] Model Privacy: A Unified Framework for Understanding Model Stealing Attacks and Defenses

Abstract page for arXiv paper 2502.15567: Model Privacy: A Unified Framework for Understanding Model Stealing Attacks and Defenses

arXiv - Machine Learning · 4 min ·
[2502.07977] RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent
Machine Learning

[2502.07977] RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent

Abstract page for arXiv paper 2502.07977: RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent

arXiv - Machine Learning · 4 min ·
[2502.02020] Causal Bandit Over Unknown Graphs: Upper Confidence Bounds With Backdoor Adjustment
Machine Learning

[2502.02020] Causal Bandit Over Unknown Graphs: Upper Confidence Bounds With Backdoor Adjustment

Abstract page for arXiv paper 2502.02020: Causal Bandit Over Unknown Graphs: Upper Confidence Bounds With Backdoor Adjustment

arXiv - Machine Learning · 4 min ·
[2501.15458] Amortized Safe Active Learning for Real-Time Data Acquisition: Pretrained Neural Policies From Simulated Nonparametric Functions
Machine Learning

[2501.15458] Amortized Safe Active Learning for Real-Time Data Acquisition: Pretrained Neural Policies From Simulated Nonparametric Functions

Abstract page for arXiv paper 2501.15458: Amortized Safe Active Learning for Real-Time Data Acquisition: Pretrained Neural Policies From ...

arXiv - Machine Learning · 4 min ·
[2411.18235] Certified Training with Branch-and-Bound for Lyapunov-stable Neural Control
Machine Learning

[2411.18235] Certified Training with Branch-and-Bound for Lyapunov-stable Neural Control

Abstract page for arXiv paper 2411.18235: Certified Training with Branch-and-Bound for Lyapunov-stable Neural Control

arXiv - AI · 4 min ·
[2410.07430] EventFlow: Forecasting Temporal Point Processes with Flow Matching
Machine Learning

[2410.07430] EventFlow: Forecasting Temporal Point Processes with Flow Matching

Abstract page for arXiv paper 2410.07430: EventFlow: Forecasting Temporal Point Processes with Flow Matching

arXiv - Machine Learning · 3 min ·
[2410.02260] FedScalar: Federated Learning with Scalar Communication for Bandwidth-Constrained Networks
Machine Learning

[2410.02260] FedScalar: Federated Learning with Scalar Communication for Bandwidth-Constrained Networks

Abstract page for arXiv paper 2410.02260: FedScalar: Federated Learning with Scalar Communication for Bandwidth-Constrained Networks

arXiv - Machine Learning · 3 min ·
[2307.09366] Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives
Machine Learning

[2307.09366] Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives

Abstract page for arXiv paper 2307.09366: Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Pers...

arXiv - Machine Learning · 4 min ·
[2305.03784] Neural Exploitation and Exploration of Contextual Bandits
Machine Learning

[2305.03784] Neural Exploitation and Exploration of Contextual Bandits

Abstract page for arXiv paper 2305.03784: Neural Exploitation and Exploration of Contextual Bandits

arXiv - Machine Learning · 3 min ·
[2301.01741] Graph State-Space Models and Latent Relational Inference
Machine Learning

[2301.01741] Graph State-Space Models and Latent Relational Inference

Abstract page for arXiv paper 2301.01741: Graph State-Space Models and Latent Relational Inference

arXiv - Machine Learning · 3 min ·
[2006.04363] Mitigating Value Hallucination in Dyna Planning via Multistep Predecessor Models
Machine Learning

[2006.04363] Mitigating Value Hallucination in Dyna Planning via Multistep Predecessor Models

Abstract page for arXiv paper 2006.04363: Mitigating Value Hallucination in Dyna Planning via Multistep Predecessor Models

arXiv - AI · 4 min ·
[2604.04930] Early Stopping for Large Reasoning Models via Confidence Dynamics
Machine Learning

[2604.04930] Early Stopping for Large Reasoning Models via Confidence Dynamics

Abstract page for arXiv paper 2604.04930: Early Stopping for Large Reasoning Models via Confidence Dynamics

arXiv - AI · 3 min ·
[2604.04920] PINNs in PDE Constrained Optimal Control Problems: Direct vs Indirect Methods
Machine Learning

[2604.04920] PINNs in PDE Constrained Optimal Control Problems: Direct vs Indirect Methods

Abstract page for arXiv paper 2604.04920: PINNs in PDE Constrained Optimal Control Problems: Direct vs Indirect Methods

arXiv - Machine Learning · 4 min ·
[2604.04898] QED-Nano: Teaching a Tiny Model to Prove Hard Theorems
Machine Learning

[2604.04898] QED-Nano: Teaching a Tiny Model to Prove Hard Theorems

Abstract page for arXiv paper 2604.04898: QED-Nano: Teaching a Tiny Model to Prove Hard Theorems

arXiv - AI · 4 min ·
[2604.04894] Rethinking Exploration in RLVR: From Entropy Regularization to Refinement via Bidirectional Entropy Modulation
Llms

[2604.04894] Rethinking Exploration in RLVR: From Entropy Regularization to Refinement via Bidirectional Entropy Modulation

Abstract page for arXiv paper 2604.04894: Rethinking Exploration in RLVR: From Entropy Regularization to Refinement via Bidirectional Ent...

arXiv - AI · 4 min ·
[2604.04872] Synthetic Sandbox for Training Machine Learning Engineering Agents
Llms

[2604.04872] Synthetic Sandbox for Training Machine Learning Engineering Agents

Abstract page for arXiv paper 2604.04872: Synthetic Sandbox for Training Machine Learning Engineering Agents

arXiv - Machine Learning · 4 min ·
[2604.04829] A Robust SINDy Autoencoder for Noisy Dynamical System Identification
Machine Learning

[2604.04829] A Robust SINDy Autoencoder for Noisy Dynamical System Identification

Abstract page for arXiv paper 2604.04829: A Robust SINDy Autoencoder for Noisy Dynamical System Identification

arXiv - Machine Learning · 3 min ·
[2604.04804] SkillX: Automatically Constructing Skill Knowledge Bases for Agents
Llms

[2604.04804] SkillX: Automatically Constructing Skill Knowledge Bases for Agents

Abstract page for arXiv paper 2604.04804: SkillX: Automatically Constructing Skill Knowledge Bases for Agents

arXiv - Machine Learning · 4 min ·
[2604.04828] Hybrid Fourier Neural Operator for Surrogate Modeling of Laser Processing with a Quantum-Circuit Mixer
Machine Learning

[2604.04828] Hybrid Fourier Neural Operator for Surrogate Modeling of Laser Processing with a Quantum-Circuit Mixer

Abstract page for arXiv paper 2604.04828: Hybrid Fourier Neural Operator for Surrogate Modeling of Laser Processing with a Quantum-Circui...

arXiv - Machine Learning · 4 min ·
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