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[2601.13227] Insider Knowledge: How Much Can RAG Systems Gain from Evaluation Secrets?
Llms

[2601.13227] Insider Knowledge: How Much Can RAG Systems Gain from Evaluation Secrets?

Abstract page for arXiv paper 2601.13227: Insider Knowledge: How Much Can RAG Systems Gain from Evaluation Secrets?

arXiv - AI · 3 min ·
[2601.22440] AI and My Values: User Perceptions of LLMs' Ability to Extract, Embody, and Explain Human Values from Casual Conversations
Llms

[2601.22440] AI and My Values: User Perceptions of LLMs' Ability to Extract, Embody, and Explain Human Values from Casual Conversations

Abstract page for arXiv paper 2601.22440: AI and My Values: User Perceptions of LLMs' Ability to Extract, Embody, and Explain Human Value...

arXiv - AI · 4 min ·
[2601.13222] Incorporating Q&A Nuggets into Retrieval-Augmented Generation
Nlp

[2601.13222] Incorporating Q&A Nuggets into Retrieval-Augmented Generation

Abstract page for arXiv paper 2601.13222: Incorporating Q&A Nuggets into Retrieval-Augmented Generation

arXiv - AI · 3 min ·

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Introducing Storage Buckets on the Hugging Face Hub
Open Source Ai

Introducing Storage Buckets on the Hugging Face Hub

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Hugging Face Blog · 9 min ·
[2509.21739] Noise-to-Notes: Diffusion-based Generation and Refinement for Automatic Drum Transcription
Machine Learning

[2509.21739] Noise-to-Notes: Diffusion-based Generation and Refinement for Automatic Drum Transcription

Abstract page for arXiv paper 2509.21739: Noise-to-Notes: Diffusion-based Generation and Refinement for Automatic Drum Transcription

arXiv - Machine Learning · 3 min ·
[2506.18812] Learning Physical Systems: Symplectification via Gauge Fixing in Dirac Structures
Machine Learning

[2506.18812] Learning Physical Systems: Symplectification via Gauge Fixing in Dirac Structures

Abstract page for arXiv paper 2506.18812: Learning Physical Systems: Symplectification via Gauge Fixing in Dirac Structures

arXiv - Machine Learning · 4 min ·
[2502.07584] Generalization Bounds for Markov Algorithms through Entropy Flow Computations
Nlp

[2502.07584] Generalization Bounds for Markov Algorithms through Entropy Flow Computations

Abstract page for arXiv paper 2502.07584: Generalization Bounds for Markov Algorithms through Entropy Flow Computations

arXiv - Machine Learning · 4 min ·
[2602.09229] Beyond the Unit Hypersphere: Embedding Magnitude in Contrastive Learning
Nlp

[2602.09229] Beyond the Unit Hypersphere: Embedding Magnitude in Contrastive Learning

Abstract page for arXiv paper 2602.09229: Beyond the Unit Hypersphere: Embedding Magnitude in Contrastive Learning

arXiv - Machine Learning · 3 min ·
[2510.07093] Non-Asymptotic Analysis of Efficiency in Conformalized Regression
Nlp

[2510.07093] Non-Asymptotic Analysis of Efficiency in Conformalized Regression

Abstract page for arXiv paper 2510.07093: Non-Asymptotic Analysis of Efficiency in Conformalized Regression

arXiv - Machine Learning · 3 min ·
[2509.25762] OPPO: Accelerating PPO-based RLHF via Pipeline Overlap
Llms

[2509.25762] OPPO: Accelerating PPO-based RLHF via Pipeline Overlap

Abstract page for arXiv paper 2509.25762: OPPO: Accelerating PPO-based RLHF via Pipeline Overlap

arXiv - Machine Learning · 3 min ·
[2507.10345] Some Super-approximation Rates of ReLU Neural Networks for Korobov Functions
Machine Learning

[2507.10345] Some Super-approximation Rates of ReLU Neural Networks for Korobov Functions

Abstract page for arXiv paper 2507.10345: Some Super-approximation Rates of ReLU Neural Networks for Korobov Functions

arXiv - Machine Learning · 3 min ·
[2506.23036] Parameter Stress Analysis in Reinforcement Learning: Applying Synaptic Filtering to Policy Networks
Nlp

[2506.23036] Parameter Stress Analysis in Reinforcement Learning: Applying Synaptic Filtering to Policy Networks

Abstract page for arXiv paper 2506.23036: Parameter Stress Analysis in Reinforcement Learning: Applying Synaptic Filtering to Policy Netw...

arXiv - Machine Learning · 4 min ·
[2406.14777] Learning to Cover: Online Learning and Optimization with Irreversible Decisions
Machine Learning

[2406.14777] Learning to Cover: Online Learning and Optimization with Irreversible Decisions

Abstract page for arXiv paper 2406.14777: Learning to Cover: Online Learning and Optimization with Irreversible Decisions

arXiv - Machine Learning · 4 min ·
[2603.05335] Bayes with No Shame: Admissibility Geometries of Predictive Inference
Machine Learning

[2603.05335] Bayes with No Shame: Admissibility Geometries of Predictive Inference

Abstract page for arXiv paper 2603.05335: Bayes with No Shame: Admissibility Geometries of Predictive Inference

arXiv - Machine Learning · 3 min ·
[2603.04859] Osmosis Distillation: Model Hijacking with the Fewest Samples
Machine Learning

[2603.04859] Osmosis Distillation: Model Hijacking with the Fewest Samples

Abstract page for arXiv paper 2603.04859: Osmosis Distillation: Model Hijacking with the Fewest Samples

arXiv - Machine Learning · 4 min ·
[2603.05353] InfoFlow KV: Information-Flow-Aware KV Recomputation for Long Context
Machine Learning

[2603.05353] InfoFlow KV: Information-Flow-Aware KV Recomputation for Long Context

Abstract page for arXiv paper 2603.05353: InfoFlow KV: Information-Flow-Aware KV Recomputation for Long Context

arXiv - Machine Learning · 3 min ·
[2603.05060] Asymptotic Behavior of Multi--Task Learning: Implicit Regularization and Double Descent Effects
Machine Learning

[2603.05060] Asymptotic Behavior of Multi--Task Learning: Implicit Regularization and Double Descent Effects

Abstract page for arXiv paper 2603.05060: Asymptotic Behavior of Multi--Task Learning: Implicit Regularization and Double Descent Effects

arXiv - Machine Learning · 3 min ·
[2603.04972] Functionality-Oriented LLM Merging on the Fisher--Rao Manifold
Llms

[2603.04972] Functionality-Oriented LLM Merging on the Fisher--Rao Manifold

Abstract page for arXiv paper 2603.04972: Functionality-Oriented LLM Merging on the Fisher--Rao Manifold

arXiv - Machine Learning · 3 min ·
[2603.04736] Distribution-Conditioned Transport
Machine Learning

[2603.04736] Distribution-Conditioned Transport

Abstract page for arXiv paper 2603.04736: Distribution-Conditioned Transport

arXiv - Machine Learning · 3 min ·
[2603.04692] Engineering Regression Without Real-Data Training: Domain Adaptation for Tabular Foundation Models Using Multi-Dataset Embeddings
Llms

[2603.04692] Engineering Regression Without Real-Data Training: Domain Adaptation for Tabular Foundation Models Using Multi-Dataset Embeddings

Abstract page for arXiv paper 2603.04692: Engineering Regression Without Real-Data Training: Domain Adaptation for Tabular Foundation Mod...

arXiv - Machine Learning · 4 min ·
[2603.04625] K-Means as a Radial Basis function Network: a Variational and Gradient-based Equivalence
Machine Learning

[2603.04625] K-Means as a Radial Basis function Network: a Variational and Gradient-based Equivalence

Abstract page for arXiv paper 2603.04625: K-Means as a Radial Basis function Network: a Variational and Gradient-based Equivalence

arXiv - Machine Learning · 4 min ·
[2602.09980] Supervised Metric Regularization Through Alternating Optimization for Multi-Regime Physics-Informed Neural Networks
Machine Learning

[2602.09980] Supervised Metric Regularization Through Alternating Optimization for Multi-Regime Physics-Informed Neural Networks

Abstract page for arXiv paper 2602.09980: Supervised Metric Regularization Through Alternating Optimization for Multi-Regime Physics-Info...

arXiv - Machine Learning · 4 min ·
[2602.07075] LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning
Llms

[2602.07075] LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning

Abstract page for arXiv paper 2602.07075: LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning

arXiv - Machine Learning · 4 min ·
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