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[2602.00681] Audio-to-Image Bird Species Retrieval without Audio-Image Pairs via Text Distillation
Nlp

[2602.00681] Audio-to-Image Bird Species Retrieval without Audio-Image Pairs via Text Distillation

Abstract page for arXiv paper 2602.00681: Audio-to-Image Bird Species Retrieval without Audio-Image Pairs via Text Distillation

arXiv - Machine Learning · 4 min ·
[2601.22783] Compact Hypercube Embeddings for Fast Text-based Wildlife Observation Retrieval
Llms

[2601.22783] Compact Hypercube Embeddings for Fast Text-based Wildlife Observation Retrieval

Abstract page for arXiv paper 2601.22783: Compact Hypercube Embeddings for Fast Text-based Wildlife Observation Retrieval

arXiv - Machine Learning · 4 min ·
[2601.04854] Projected Autoregression: Autoregressive Language Generation in Continuous State Space
Llms

[2601.04854] Projected Autoregression: Autoregressive Language Generation in Continuous State Space

Abstract page for arXiv paper 2601.04854: Projected Autoregression: Autoregressive Language Generation in Continuous State Space

arXiv - Machine Learning · 4 min ·

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[2412.06014] Post-hoc Probabilistic Vision-Language Models
Llms

[2412.06014] Post-hoc Probabilistic Vision-Language Models

This article presents a novel approach to uncertainty estimation in vision-language models (VLMs) by proposing a post-hoc method that enh...

arXiv - Machine Learning · 3 min ·
[2410.03041] Minmax Trend Filtering: Generalizations of Total Variation Denoising via a Local Minmax/Maxmin Formula
Nlp

[2410.03041] Minmax Trend Filtering: Generalizations of Total Variation Denoising via a Local Minmax/Maxmin Formula

The paper introduces Minmax Trend Filtering (MTF), a novel approach to Total Variation Denoising (TVD) that utilizes a local minmax/maxmi...

arXiv - Machine Learning · 4 min ·
[2312.17111] Online Tensor Inference
Machine Learning

[2312.17111] Online Tensor Inference

The paper presents a novel framework for online tensor inference, addressing the challenges of real-time data processing in applications ...

arXiv - Machine Learning · 4 min ·
[2602.11151] Diffusion-Pretrained Dense and Contextual Embeddings
Llms

[2602.11151] Diffusion-Pretrained Dense and Contextual Embeddings

The paper introduces pplx-embed, a family of multilingual embedding models utilizing diffusion-pretrained language models for enhanced re...

arXiv - Machine Learning · 3 min ·
[2510.17406] Multi-Window Temporal Analysis for Enhanced Arrhythmia Classification: Leveraging Long-Range Dependencies in Electrocardiogram Signals
Machine Learning

[2510.17406] Multi-Window Temporal Analysis for Enhanced Arrhythmia Classification: Leveraging Long-Range Dependencies in Electrocardiogram Signals

This paper presents S4ECG, a novel deep learning architecture that enhances arrhythmia classification by analyzing multiple ECG windows, ...

arXiv - Machine Learning · 4 min ·
[2509.25826] Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models
Llms

[2509.25826] Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models

The paper presents Kairos, a novel time series foundation model that enhances zero-shot generalization by decoupling temporal heterogenei...

arXiv - Machine Learning · 4 min ·
[2509.14585] Online reinforcement learning via sparse Gaussian mixture model Q-functions
Machine Learning

[2509.14585] Online reinforcement learning via sparse Gaussian mixture model Q-functions

This paper presents an innovative online reinforcement learning framework using sparse Gaussian mixture model Q-functions, enhancing expl...

arXiv - Machine Learning · 3 min ·
[2509.10406] Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining
Machine Learning

[2509.10406] Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining

The paper introduces Multipole Semantic Attention (MuSe), a method that accelerates pretraining of transformers on long sequences by 36% ...

arXiv - Machine Learning · 3 min ·
[2504.16585] Leveraging Noisy Manual Labels as Useful Information: An Information Fusion Approach for Enhanced Variable Selection in Penalized Logistic Regression
Nlp

[2504.16585] Leveraging Noisy Manual Labels as Useful Information: An Information Fusion Approach for Enhanced Variable Selection in Penalized Logistic Regression

This paper explores how noisy manual labels can enhance variable selection in penalized logistic regression, proposing a novel algorithm ...

arXiv - Machine Learning · 4 min ·
[2602.13168] Realistic Face Reconstruction from Facial Embeddings via Diffusion Models
Machine Learning

[2602.13168] Realistic Face Reconstruction from Facial Embeddings via Diffusion Models

This paper presents a novel framework for reconstructing realistic high-resolution face images from facial embeddings using diffusion mod...

arXiv - Machine Learning · 3 min ·
[2602.12937] Curriculum Learning and Pseudo-Labeling Improve the Generalization of Multi-Label Arabic Dialect Identification Models
Machine Learning

[2602.12937] Curriculum Learning and Pseudo-Labeling Improve the Generalization of Multi-Label Arabic Dialect Identification Models

This article presents a novel approach to Arabic Dialect Identification by framing it as a multi-label classification task, utilizing cur...

arXiv - Machine Learning · 4 min ·
[2602.12932] TFTF: Training-Free Targeted Flow for Conditional Sampling
Machine Learning

[2602.12932] TFTF: Training-Free Targeted Flow for Conditional Sampling

The paper presents a novel training-free method for conditional sampling in flow matching models, addressing the limitations of importanc...

arXiv - Machine Learning · 3 min ·
[2602.12923] Annealing in variational inference mitigates mode collapse: A theoretical study on Gaussian mixtures
Machine Learning

[2602.12923] Annealing in variational inference mitigates mode collapse: A theoretical study on Gaussian mixtures

This article presents a theoretical analysis of how annealing strategies can mitigate mode collapse in variational inference, particularl...

arXiv - Machine Learning · 3 min ·
[2602.12825] Reliable Hierarchical Operating System Fingerprinting via Conformal Prediction
Nlp

[2602.12825] Reliable Hierarchical Operating System Fingerprinting via Conformal Prediction

This paper presents a novel approach to Operating System fingerprinting using Conformal Prediction, addressing limitations in existing me...

arXiv - Machine Learning · 3 min ·
[2602.12778] Aspect-Based Sentiment Analysis for Future Tourism Experiences: A BERT-MoE Framework for Persian User Reviews
Machine Learning

[2602.12778] Aspect-Based Sentiment Analysis for Future Tourism Experiences: A BERT-MoE Framework for Persian User Reviews

This article presents a novel BERT-MoE framework for aspect-based sentiment analysis (ABSA) tailored for Persian user reviews in the tour...

arXiv - Machine Learning · 4 min ·
[2602.12510] Visual RAG Toolkit: Scaling Multi-Vector Visual Retrieval with Training-Free Pooling and Multi-Stage Search
Machine Learning

[2602.12510] Visual RAG Toolkit: Scaling Multi-Vector Visual Retrieval with Training-Free Pooling and Multi-Stage Search

The Visual RAG Toolkit enhances multi-vector visual retrieval by introducing a training-free pooling method and a multi-stage search proc...

arXiv - Machine Learning · 4 min ·
[2602.12575] Discovering Semantic Latent Structures in Psychological Scales: A Response-Free Pathway to Efficient Simplification
Nlp

[2602.12575] Discovering Semantic Latent Structures in Psychological Scales: A Response-Free Pathway to Efficient Simplification

This article presents a novel framework for simplifying psychological scales by discovering semantic latent structures without relying on...

arXiv - Machine Learning · 4 min ·
[2602.12445] RBCorr: Response Bias Correction in Language Models
Llms

[2602.12445] RBCorr: Response Bias Correction in Language Models

The paper presents RBCorr, a method for correcting response biases in language models, demonstrating its effectiveness across various mod...

arXiv - Machine Learning · 3 min ·
[2602.12426] Interference-Robust Non-Coherent Over-the-Air Computation for Decentralized Optimization
Nlp

[2602.12426] Interference-Robust Non-Coherent Over-the-Air Computation for Decentralized Optimization

This paper presents an interference-robust non-coherent over-the-air computation (IR-NCOTA) method for decentralized optimization, enhanc...

arXiv - Machine Learning · 3 min ·
[2602.12301] Beyond Musical Descriptors: Extracting Preference-Bearing Intent in Music Queries
Data Science

[2602.12301] Beyond Musical Descriptors: Extracting Preference-Bearing Intent in Music Queries

This article presents a novel dataset, MusicRecoIntent, aimed at understanding user intent in music queries by analyzing descriptors and ...

arXiv - Machine Learning · 3 min ·
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