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Machine Learning

[P] Federated Adversarial Learning

I'm a CS/ML engineering student in my 4th year, and I need help for a project I recently got assigned to (as an "end of the year" project...

Reddit - Machine Learning · 1 min ·
Llms

Anthropic is training Claude to recognize when its own tools are trying to manipulate it

One thing from Claude Code's source that I think is underappreciated. There's an explicit instruction in the system prompt: if the AI sus...

Reddit - Artificial Intelligence · 1 min ·
Llms

The Claude Code leak accidentally published the first complete blueprint for production AI agents. Here's what it tells us about where this is all going.

Most coverage of the Claude Code leak focuses on the drama or the hidden features. But the bigger story is that this is the first time we...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2509.23768] From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning
Llms

[2509.23768] From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning

Abstract page for arXiv paper 2509.23768: From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning

arXiv - AI · 3 min ·
[2512.18951] Benchmarking Attribute Discrimination in Infant-Scale Vision-Language Models
Llms

[2512.18951] Benchmarking Attribute Discrimination in Infant-Scale Vision-Language Models

Abstract page for arXiv paper 2512.18951: Benchmarking Attribute Discrimination in Infant-Scale Vision-Language Models

arXiv - Machine Learning · 3 min ·
[2509.03345] Do Language Models Follow Occam's Razor? An Evaluation of Parsimony in Inductive and Abductive Reasoning
Llms

[2509.03345] Do Language Models Follow Occam's Razor? An Evaluation of Parsimony in Inductive and Abductive Reasoning

Abstract page for arXiv paper 2509.03345: Do Language Models Follow Occam's Razor? An Evaluation of Parsimony in Inductive and Abductive ...

arXiv - AI · 4 min ·
[2512.10152] Rethinking Bivariate Causal Discovery Through the Lens of Exchangeability
Machine Learning

[2512.10152] Rethinking Bivariate Causal Discovery Through the Lens of Exchangeability

Abstract page for arXiv paper 2512.10152: Rethinking Bivariate Causal Discovery Through the Lens of Exchangeability

arXiv - Machine Learning · 4 min ·
[2512.01906] Delays in Spiking Neural Networks: A State Space Model Approach
Machine Learning

[2512.01906] Delays in Spiking Neural Networks: A State Space Model Approach

Abstract page for arXiv paper 2512.01906: Delays in Spiking Neural Networks: A State Space Model Approach

arXiv - Machine Learning · 4 min ·
[2504.15780] TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving
Llms

[2504.15780] TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving

Abstract page for arXiv paper 2504.15780: TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving

arXiv - AI · 4 min ·
[2503.03361] Concepts Learned Visually by Infants Can Contribute to Visual Learning and Understanding in AI Models
Machine Learning

[2503.03361] Concepts Learned Visually by Infants Can Contribute to Visual Learning and Understanding in AI Models

Abstract page for arXiv paper 2503.03361: Concepts Learned Visually by Infants Can Contribute to Visual Learning and Understanding in AI ...

arXiv - AI · 4 min ·
[2512.01678] Morphling: Fast, Fused, and Flexible GNN Training at Scale
Machine Learning

[2512.01678] Morphling: Fast, Fused, and Flexible GNN Training at Scale

Abstract page for arXiv paper 2512.01678: Morphling: Fast, Fused, and Flexible GNN Training at Scale

arXiv - Machine Learning · 4 min ·
[2511.22344] Cleaning the Pool: Progressive Filtering of Unlabeled Pools in Deep Active Learning
Machine Learning

[2511.22344] Cleaning the Pool: Progressive Filtering of Unlabeled Pools in Deep Active Learning

Abstract page for arXiv paper 2511.22344: Cleaning the Pool: Progressive Filtering of Unlabeled Pools in Deep Active Learning

arXiv - Machine Learning · 4 min ·
[2410.20894] Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots
Machine Learning

[2410.20894] Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots

Abstract page for arXiv paper 2410.20894: Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Deto...

arXiv - Machine Learning · 4 min ·
[2511.16992] FIRM: Federated In-client Regularized Multi-objective Alignment for Large Language Models
Llms

[2511.16992] FIRM: Federated In-client Regularized Multi-objective Alignment for Large Language Models

Abstract page for arXiv paper 2511.16992: FIRM: Federated In-client Regularized Multi-objective Alignment for Large Language Models

arXiv - Machine Learning · 4 min ·
[2511.14961] Graph Memory: A Structured and Interpretable Framework for Modality-Agnostic Embedding-Based Inference
Machine Learning

[2511.14961] Graph Memory: A Structured and Interpretable Framework for Modality-Agnostic Embedding-Based Inference

Abstract page for arXiv paper 2511.14961: Graph Memory: A Structured and Interpretable Framework for Modality-Agnostic Embedding-Based In...

arXiv - Machine Learning · 4 min ·
[2603.25741] Vega: Learning to Drive with Natural Language Instructions
Machine Learning

[2603.25741] Vega: Learning to Drive with Natural Language Instructions

Abstract page for arXiv paper 2603.25741: Vega: Learning to Drive with Natural Language Instructions

arXiv - AI · 3 min ·
[2510.13772] Tensor Gaussian Processes: Efficient Solvers for Nonlinear PDEs
Machine Learning

[2510.13772] Tensor Gaussian Processes: Efficient Solvers for Nonlinear PDEs

Abstract page for arXiv paper 2510.13772: Tensor Gaussian Processes: Efficient Solvers for Nonlinear PDEs

arXiv - Machine Learning · 4 min ·
[2603.25730] PackForcing: Short Video Training Suffices for Long Video Sampling and Long Context Inference
Machine Learning

[2603.25730] PackForcing: Short Video Training Suffices for Long Video Sampling and Long Context Inference

Abstract page for arXiv paper 2603.25730: PackForcing: Short Video Training Suffices for Long Video Sampling and Long Context Inference

arXiv - AI · 4 min ·
[2510.12453] Time-Correlated Video Bridge Matching
Machine Learning

[2510.12453] Time-Correlated Video Bridge Matching

Abstract page for arXiv paper 2510.12453: Time-Correlated Video Bridge Matching

arXiv - Machine Learning · 3 min ·
[2510.06790] Get RICH or Die Scaling: Profitably Trading Inference Compute for Robustness
Llms

[2510.06790] Get RICH or Die Scaling: Profitably Trading Inference Compute for Robustness

Abstract page for arXiv paper 2510.06790: Get RICH or Die Scaling: Profitably Trading Inference Compute for Robustness

arXiv - Machine Learning · 4 min ·
[2510.04900] Benchmarking M-LTSF: Frequency and Noise-Based Evaluation of Multivariate Long Time Series Forecasting Models
Machine Learning

[2510.04900] Benchmarking M-LTSF: Frequency and Noise-Based Evaluation of Multivariate Long Time Series Forecasting Models

Abstract page for arXiv paper 2510.04900: Benchmarking M-LTSF: Frequency and Noise-Based Evaluation of Multivariate Long Time Series Fore...

arXiv - Machine Learning · 4 min ·
[2603.25716] Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models
Machine Learning

[2603.25716] Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models

Abstract page for arXiv paper 2603.25716: Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models

arXiv - AI · 4 min ·
[2509.15199] CausalPre: Scalable and Effective Data Pre-Processing for Causal Fairness
Machine Learning

[2509.15199] CausalPre: Scalable and Effective Data Pre-Processing for Causal Fairness

Abstract page for arXiv paper 2509.15199: CausalPre: Scalable and Effective Data Pre-Processing for Causal Fairness

arXiv - Machine Learning · 4 min ·
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