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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

[2509.02892] Improving Generative Methods for Causal Evaluation via Simulation-Based Inference
Machine Learning

[2509.02892] Improving Generative Methods for Causal Evaluation via Simulation-Based Inference

Abstract page for arXiv paper 2509.02892: Improving Generative Methods for Causal Evaluation via Simulation-Based Inference

arXiv - Machine Learning · 4 min ·
[2509.00203] Estimating Parameter Fields in Multi-Physics PDEs from Scarce Measurements
Machine Learning

[2509.00203] Estimating Parameter Fields in Multi-Physics PDEs from Scarce Measurements

Abstract page for arXiv paper 2509.00203: Estimating Parameter Fields in Multi-Physics PDEs from Scarce Measurements

arXiv - Machine Learning · 4 min ·
[2508.10053] xRFM: Accurate, scalable, and interpretable feature learning models for tabular data
Machine Learning

[2508.10053] xRFM: Accurate, scalable, and interpretable feature learning models for tabular data

Abstract page for arXiv paper 2508.10053: xRFM: Accurate, scalable, and interpretable feature learning models for tabular data

arXiv - Machine Learning · 4 min ·
[2508.08935] LNN-PINN: A Unified Physics-Only Training Framework with Liquid Residual Blocks
Machine Learning

[2508.08935] LNN-PINN: A Unified Physics-Only Training Framework with Liquid Residual Blocks

Abstract page for arXiv paper 2508.08935: LNN-PINN: A Unified Physics-Only Training Framework with Liquid Residual Blocks

arXiv - Machine Learning · 3 min ·
[2508.04503] PRISM: Lightweight Multivariate Time-Series Classification through Symmetric Multi-Resolution Convolutional Layers
Machine Learning

[2508.04503] PRISM: Lightweight Multivariate Time-Series Classification through Symmetric Multi-Resolution Convolutional Layers

Abstract page for arXiv paper 2508.04503: PRISM: Lightweight Multivariate Time-Series Classification through Symmetric Multi-Resolution C...

arXiv - AI · 4 min ·
[2508.02812] Evaluating and Learning Robust Bandit Policies Under Uncertain Causal Mechanisms
Machine Learning

[2508.02812] Evaluating and Learning Robust Bandit Policies Under Uncertain Causal Mechanisms

Abstract page for arXiv paper 2508.02812: Evaluating and Learning Robust Bandit Policies Under Uncertain Causal Mechanisms

arXiv - Machine Learning · 3 min ·
[2507.13920] Causal Process Models: Reframing Dynamic Causal Graph Discovery as a Reinforcement Learning Problem
Machine Learning

[2507.13920] Causal Process Models: Reframing Dynamic Causal Graph Discovery as a Reinforcement Learning Problem

Abstract page for arXiv paper 2507.13920: Causal Process Models: Reframing Dynamic Causal Graph Discovery as a Reinforcement Learning Pro...

arXiv - Machine Learning · 3 min ·
[2507.12165] Multi-Component VAE with Gaussian Markov Random Field
Machine Learning

[2507.12165] Multi-Component VAE with Gaussian Markov Random Field

Abstract page for arXiv paper 2507.12165: Multi-Component VAE with Gaussian Markov Random Field

arXiv - Machine Learning · 3 min ·
[2506.21744] Federated Item Response Models: A Gradient-driven Privacy-preserving Framework for Distributed Psychometric Estimation
Machine Learning

[2506.21744] Federated Item Response Models: A Gradient-driven Privacy-preserving Framework for Distributed Psychometric Estimation

Abstract page for arXiv paper 2506.21744: Federated Item Response Models: A Gradient-driven Privacy-preserving Framework for Distributed ...

arXiv - Machine Learning · 4 min ·
[2506.08125] Not All Tokens Matter: Towards Efficient LLM Reasoning via Token Significance in Reinforcement Learning
Llms

[2506.08125] Not All Tokens Matter: Towards Efficient LLM Reasoning via Token Significance in Reinforcement Learning

Abstract page for arXiv paper 2506.08125: Not All Tokens Matter: Towards Efficient LLM Reasoning via Token Significance in Reinforcement ...

arXiv - Machine Learning · 4 min ·
[2506.02371] SFBD Flow: A Continuous-Optimization Framework for Training Diffusion Models with Noisy Samples
Machine Learning

[2506.02371] SFBD Flow: A Continuous-Optimization Framework for Training Diffusion Models with Noisy Samples

Abstract page for arXiv paper 2506.02371: SFBD Flow: A Continuous-Optimization Framework for Training Diffusion Models with Noisy Samples

arXiv - Machine Learning · 3 min ·
[2506.01897] MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation
Llms

[2506.01897] MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation

Abstract page for arXiv paper 2506.01897: MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation

arXiv - Machine Learning · 4 min ·
[2505.24535] Beyond Linear Steering: Unified Multi-Attribute Control for Language Models
Llms

[2505.24535] Beyond Linear Steering: Unified Multi-Attribute Control for Language Models

Abstract page for arXiv paper 2505.24535: Beyond Linear Steering: Unified Multi-Attribute Control for Language Models

arXiv - AI · 3 min ·
[2505.21972] LLMs Judging LLMs: A Simplex Perspective
Llms

[2505.21972] LLMs Judging LLMs: A Simplex Perspective

Abstract page for arXiv paper 2505.21972: LLMs Judging LLMs: A Simplex Perspective

arXiv - AI · 4 min ·
[2505.21605] SoSBench: Benchmarking Safety Alignment on Six Scientific Domains
Llms

[2505.21605] SoSBench: Benchmarking Safety Alignment on Six Scientific Domains

Abstract page for arXiv paper 2505.21605: SoSBench: Benchmarking Safety Alignment on Six Scientific Domains

arXiv - AI · 4 min ·
[2505.14202] MSDformer: Multi-scale Discrete Transformer For Time Series Generation
Machine Learning

[2505.14202] MSDformer: Multi-scale Discrete Transformer For Time Series Generation

Abstract page for arXiv paper 2505.14202: MSDformer: Multi-scale Discrete Transformer For Time Series Generation

arXiv - Machine Learning · 4 min ·
[2505.13742] Understanding Task Representations in Neural Networks via Bayesian Ablation
Machine Learning

[2505.13742] Understanding Task Representations in Neural Networks via Bayesian Ablation

Abstract page for arXiv paper 2505.13742: Understanding Task Representations in Neural Networks via Bayesian Ablation

arXiv - AI · 3 min ·
[2505.12530] Enforcing Fair Predicted Scores on Intervals of Percentiles by Difference-of-Convex Constraints
Machine Learning

[2505.12530] Enforcing Fair Predicted Scores on Intervals of Percentiles by Difference-of-Convex Constraints

Abstract page for arXiv paper 2505.12530: Enforcing Fair Predicted Scores on Intervals of Percentiles by Difference-of-Convex Constraints

arXiv - Machine Learning · 4 min ·
[2505.12167] FABLE: A Localized, Targeted Adversarial Attack on Weather Forecasting Models
Machine Learning

[2505.12167] FABLE: A Localized, Targeted Adversarial Attack on Weather Forecasting Models

Abstract page for arXiv paper 2505.12167: FABLE: A Localized, Targeted Adversarial Attack on Weather Forecasting Models

arXiv - Machine Learning · 3 min ·
[2505.03530] A Multi-Level Causal Intervention Framework for Mechanistic Interpretability in Variational Autoencoders
Machine Learning

[2505.03530] A Multi-Level Causal Intervention Framework for Mechanistic Interpretability in Variational Autoencoders

Abstract page for arXiv paper 2505.03530: A Multi-Level Causal Intervention Framework for Mechanistic Interpretability in Variational Aut...

arXiv - Machine Learning · 4 min ·
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