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Llms

[R] 94.42% on BANKING77 Official Test Split with Lightweight Embedding + Example Reranking (strict full-train protocol)

BANKING77 (77 fine-grained banking intents) is a well-established but increasingly saturated intent classification benchmark. did this wh...

Reddit - Machine Learning · 1 min ·
Llms

94.42% on BANKING77 Official Test Split — New Strong 2nd Place with Lightweight Embedding + Rerank (no 7B LLM)

94.42% Accuracy on Banking77 Official Test Split BANKING77-77 is deceptively hard: 77 fine-grained banking intents, noisy real-world quer...

Reddit - Artificial Intelligence · 1 min ·
Nlp

Built a Hybrid NAS tool for RNN architectures (HyNAS-R) – Looking for feedback for my final year evaluation [R]

Hi everyone, I'm currently in the evaluation phase of my Final Year Project and am looking for feedback on the system I've built. It's ca...

Reddit - Machine Learning · 1 min ·

All Content

[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 ·
[2602.13140] FlashSchNet: Fast and Accurate Coarse-Grained Neural Network Molecular Dynamics
Machine Learning

[2602.13140] FlashSchNet: Fast and Accurate Coarse-Grained Neural Network Molecular Dynamics

FlashSchNet presents a novel framework for molecular dynamics simulations, enhancing speed and accuracy through innovative techniques in ...

arXiv - Machine Learning · 4 min ·
[2602.13042] GPTZero: Robust Detection of LLM-Generated Texts
Llms

[2602.13042] GPTZero: Robust Detection of LLM-Generated Texts

GPTZero introduces a robust solution for detecting AI-generated texts, addressing concerns over text authenticity and misinformation in t...

arXiv - Machine Learning · 3 min ·
[2602.12982] Multi-Dimensional Visual Data Recovery: Scale-Aware Tensor Modeling and Accelerated Randomized Computation
Machine Learning

[2602.12982] Multi-Dimensional Visual Data Recovery: Scale-Aware Tensor Modeling and Accelerated Randomized Computation

The paper presents a novel approach to multi-dimensional visual data recovery using Scale-Aware Tensor Modeling and accelerated randomize...

arXiv - Machine Learning · 4 min ·
[2602.12756] Closing the Loop: A Control-Theoretic Framework for Provably Stable Time Series Forecasting with LLMs
Llms

[2602.12756] Closing the Loop: A Control-Theoretic Framework for Provably Stable Time Series Forecasting with LLMs

This paper introduces F-LLM, a control-theoretic framework for stable time series forecasting using large language models, addressing iss...

arXiv - Machine Learning · 4 min ·
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