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Machine Learning

[R] Structure Over Scale: Memory-First Reasoning and Depth-Pruned Efficiency in Magnus and Seed Architecture Auto-Discovery

Dataset Model Acc F1 Δ vs Log Δ vs Static Avg Params Peak Params Steps Infer ms Size Banking77-20 Logistic TF-IDF 92.37% 0.9230 +0.00pp +...

Reddit - Machine Learning · 1 min ·
DataCamp and LangChain Launch AI Engineering Learning Track
Ai Startups

DataCamp and LangChain Launch AI Engineering Learning Track

DataCamp, a leading online platform for data science and machine learning education, has partnered with LangChain, a prominent open-sourc...

AI News - General · 4 min ·
Ai Startups

Arkansas Tech launches new artificial intelligence track to meet growing workforce demand

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AI News - General · 1 min ·

All Content

[2509.23159] ProtoTS: Learning Hierarchical Prototypes for Explainable Time Series Forecasting
Machine Learning

[2509.23159] ProtoTS: Learning Hierarchical Prototypes for Explainable Time Series Forecasting

Abstract page for arXiv paper 2509.23159: ProtoTS: Learning Hierarchical Prototypes for Explainable Time Series Forecasting

arXiv - Machine Learning · 4 min ·
[2511.13111] NuBench: An Open Benchmark for Deep Learning-Based Event Reconstruction in Neutrino Telescopes
Machine Learning

[2511.13111] NuBench: An Open Benchmark for Deep Learning-Based Event Reconstruction in Neutrino Telescopes

Abstract page for arXiv paper 2511.13111: NuBench: An Open Benchmark for Deep Learning-Based Event Reconstruction in Neutrino Telescopes

arXiv - Machine Learning · 4 min ·
[2511.05271] DeepEyesV2: Toward Agentic Multimodal Model
Machine Learning

[2511.05271] DeepEyesV2: Toward Agentic Multimodal Model

Abstract page for arXiv paper 2511.05271: DeepEyesV2: Toward Agentic Multimodal Model

arXiv - AI · 4 min ·
[2510.23006] Understanding In-Context Learning Beyond Transformers: An Investigation of State Space and Hybrid Architectures
Llms

[2510.23006] Understanding In-Context Learning Beyond Transformers: An Investigation of State Space and Hybrid Architectures

Abstract page for arXiv paper 2510.23006: Understanding In-Context Learning Beyond Transformers: An Investigation of State Space and Hybr...

arXiv - AI · 3 min ·
[2510.05228] CMT-Benchmark: A Benchmark for Condensed Matter Theory Built by Expert Researchers
Llms

[2510.05228] CMT-Benchmark: A Benchmark for Condensed Matter Theory Built by Expert Researchers

Abstract page for arXiv paper 2510.05228: CMT-Benchmark: A Benchmark for Condensed Matter Theory Built by Expert Researchers

arXiv - Machine Learning · 4 min ·
[2303.00320] TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders
Machine Learning

[2303.00320] TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders

Abstract page for arXiv paper 2303.00320: TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders

arXiv - Machine Learning · 4 min ·
[2505.19764] Multi-View Encoders for Performance Prediction in LLM-Based Agentic Workflows
Llms

[2505.19764] Multi-View Encoders for Performance Prediction in LLM-Based Agentic Workflows

Abstract page for arXiv paper 2505.19764: Multi-View Encoders for Performance Prediction in LLM-Based Agentic Workflows

arXiv - Machine Learning · 4 min ·
[2601.21961] How do Visual Attributes Influence Web Agents? A Comprehensive Evaluation of User Interface Design Factors
Ai Startups

[2601.21961] How do Visual Attributes Influence Web Agents? A Comprehensive Evaluation of User Interface Design Factors

Abstract page for arXiv paper 2601.21961: How do Visual Attributes Influence Web Agents? A Comprehensive Evaluation of User Interface Des...

arXiv - AI · 4 min ·
[2506.20640] CoMind: Towards Community-Driven Agents for Machine Learning Engineering
Llms

[2506.20640] CoMind: Towards Community-Driven Agents for Machine Learning Engineering

Abstract page for arXiv paper 2506.20640: CoMind: Towards Community-Driven Agents for Machine Learning Engineering

arXiv - Machine Learning · 4 min ·
[2602.24277] Resources for Automated Evaluation of Assistive RAG Systems that Help Readers with News Trustworthiness Assessment
Nlp

[2602.24277] Resources for Automated Evaluation of Assistive RAG Systems that Help Readers with News Trustworthiness Assessment

Abstract page for arXiv paper 2602.24277: Resources for Automated Evaluation of Assistive RAG Systems that Help Readers with News Trustwo...

arXiv - AI · 4 min ·
[2602.24119] Terminology Rarity Predicts Catastrophic Failure in LLM Translation of Low-Resource Ancient Languages: Evidence from Ancient Greek
Llms

[2602.24119] Terminology Rarity Predicts Catastrophic Failure in LLM Translation of Low-Resource Ancient Languages: Evidence from Ancient Greek

Abstract page for arXiv paper 2602.24119: Terminology Rarity Predicts Catastrophic Failure in LLM Translation of Low-Resource Ancient Lan...

arXiv - AI · 4 min ·
[2602.24096] DiffusionHarmonizer: Bridging Neural Reconstruction and Photorealistic Simulation with Online Diffusion Enhancer
Generative Ai

[2602.24096] DiffusionHarmonizer: Bridging Neural Reconstruction and Photorealistic Simulation with Online Diffusion Enhancer

Abstract page for arXiv paper 2602.24096: DiffusionHarmonizer: Bridging Neural Reconstruction and Photorealistic Simulation with Online D...

arXiv - Machine Learning · 4 min ·
[2602.24238] Time Series Foundation Models as Strong Baselines in Transportation Forecasting: A Large-Scale Benchmark Analysis
Llms

[2602.24238] Time Series Foundation Models as Strong Baselines in Transportation Forecasting: A Large-Scale Benchmark Analysis

Abstract page for arXiv paper 2602.24238: Time Series Foundation Models as Strong Baselines in Transportation Forecasting: A Large-Scale ...

arXiv - Machine Learning · 3 min ·
[2602.24060] Task Complexity Matters: An Empirical Study of Reasoning in LLMs for Sentiment Analysis
Llms

[2602.24060] Task Complexity Matters: An Empirical Study of Reasoning in LLMs for Sentiment Analysis

Abstract page for arXiv paper 2602.24060: Task Complexity Matters: An Empirical Study of Reasoning in LLMs for Sentiment Analysis

arXiv - AI · 4 min ·
[2602.24201] Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics
Machine Learning

[2602.24201] Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics

Abstract page for arXiv paper 2602.24201: Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics

arXiv - Machine Learning · 3 min ·
[2602.24014] Interpretable Debiasing of Vision-Language Models for Social Fairness
Llms

[2602.24014] Interpretable Debiasing of Vision-Language Models for Social Fairness

Abstract page for arXiv paper 2602.24014: Interpretable Debiasing of Vision-Language Models for Social Fairness

arXiv - AI · 3 min ·
[2602.24009] Jailbreak Foundry: From Papers to Runnable Attacks for Reproducible Benchmarking
Llms

[2602.24009] Jailbreak Foundry: From Papers to Runnable Attacks for Reproducible Benchmarking

Abstract page for arXiv paper 2602.24009: Jailbreak Foundry: From Papers to Runnable Attacks for Reproducible Benchmarking

arXiv - Machine Learning · 4 min ·
[2602.23949] HotelQuEST: Balancing Quality and Efficiency in Agentic Search
Llms

[2602.23949] HotelQuEST: Balancing Quality and Efficiency in Agentic Search

Abstract page for arXiv paper 2602.23949: HotelQuEST: Balancing Quality and Efficiency in Agentic Search

arXiv - AI · 3 min ·
[2602.23834] Enhancing Continual Learning for Software Vulnerability Prediction: Addressing Catastrophic Forgetting via Hybrid-Confidence-Aware Selective Replay for Temporal LLM Fine-Tuning
Llms

[2602.23834] Enhancing Continual Learning for Software Vulnerability Prediction: Addressing Catastrophic Forgetting via Hybrid-Confidence-Aware Selective Replay for Temporal LLM Fine-Tuning

Abstract page for arXiv paper 2602.23834: Enhancing Continual Learning for Software Vulnerability Prediction: Addressing Catastrophic For...

arXiv - Machine Learning · 4 min ·
[2602.23729] From Static Benchmarks to Dynamic Protocol: Agent-Centric Text Anomaly Detection for Evaluating LLM Reasoning
Llms

[2602.23729] From Static Benchmarks to Dynamic Protocol: Agent-Centric Text Anomaly Detection for Evaluating LLM Reasoning

Abstract page for arXiv paper 2602.23729: From Static Benchmarks to Dynamic Protocol: Agent-Centric Text Anomaly Detection for Evaluating...

arXiv - Machine Learning · 4 min ·
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Machine Learning Large Language Models Generative AI Natural Language Processing Computer Vision Robotics & Embodied AI

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