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Machine Learning

easyaligner: Forced alignment with GPU acceleration and flexible text normalization (compatible with all w2v2 models on HF Hub) [P]

https://preview.redd.it/f4d5krhkjyvg1.png?width=1020&format=png&auto=webp&s=11310f377b22abbe3dd110cc7d362ba8aae35f8d I have b...

Reddit - Machine Learning · 1 min ·
UMKC Announces New Master of Science in Artificial Intelligence
Ai Infrastructure

UMKC Announces New Master of Science in Artificial Intelligence

UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...

AI News - General · 4 min ·
Llms

What is the current landscape on AI agents knowledge

Recently used "free" rates codex to give me a quick fastapi project sample. It gave me deprecated (a)app.on_event("startup). What are you...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2602.14759] Inner Loop Inference for Pretrained Transformers: Unlocking Latent Capabilities Without Training
Machine Learning

[2602.14759] Inner Loop Inference for Pretrained Transformers: Unlocking Latent Capabilities Without Training

The paper presents 'Inner Loop Inference,' a method for enhancing pretrained Transformers by iteratively refining outputs during inferenc...

arXiv - Machine Learning · 4 min ·
[2602.14728] D2-LoRA: A Synergistic Approach to Differential and Directional Low-Rank Adaptation
Machine Learning

[2602.14728] D2-LoRA: A Synergistic Approach to Differential and Directional Low-Rank Adaptation

D2-LoRA introduces a novel method for efficient fine-tuning in machine learning, achieving significant accuracy improvements while minimi...

arXiv - Machine Learning · 4 min ·
[2602.13357] AdaCorrection: Adaptive Offset Cache Correction for Accurate Diffusion Transformers
Machine Learning

[2602.13357] AdaCorrection: Adaptive Offset Cache Correction for Accurate Diffusion Transformers

The paper introduces AdaCorrection, a framework that enhances the efficiency of Diffusion Transformers by correcting cache misalignment, ...

arXiv - AI · 3 min ·
[2602.14729] Scale redundancy and soft gauge fixing in positively homogeneous neural networks
Machine Learning

[2602.14729] Scale redundancy and soft gauge fixing in positively homogeneous neural networks

This paper explores the concept of scale redundancy in positively homogeneous neural networks, introducing gauge-adapted coordinates and ...

arXiv - AI · 3 min ·
[2602.14701] Unbiased Approximate Vector-Jacobian Products for Efficient Backpropagation
Machine Learning

[2602.14701] Unbiased Approximate Vector-Jacobian Products for Efficient Backpropagation

This paper presents methods to enhance the efficiency of backpropagation in deep learning by using unbiased approximate vector-Jacobian p...

arXiv - Machine Learning · 3 min ·
[2602.13350] Detecting Brick Kiln Infrastructure at Scale: Graph, Foundation, and Remote Sensing Models for Satellite Imagery Data
Machine Learning

[2602.13350] Detecting Brick Kiln Infrastructure at Scale: Graph, Foundation, and Remote Sensing Models for Satellite Imagery Data

This paper presents a novel approach to detecting brick kiln infrastructure using high-resolution satellite imagery, focusing on a new mo...

arXiv - AI · 4 min ·
[2602.13339] An Integrated Causal Inference Framework for Traffic Safety Modeling with Semantic Street-View Visual Features
Machine Learning

[2602.13339] An Integrated Causal Inference Framework for Traffic Safety Modeling with Semantic Street-View Visual Features

This article presents a novel causal inference framework for traffic safety modeling, utilizing semantic features from street-view images...

arXiv - AI · 4 min ·
[2602.14635] Alignment Adapter to Improve the Performance of Compressed Deep Learning Models
Machine Learning

[2602.14635] Alignment Adapter to Improve the Performance of Compressed Deep Learning Models

The paper introduces the Alignment Adapter (AlAd), a method to enhance the performance of compressed deep learning models by aligning the...

arXiv - Machine Learning · 3 min ·
[2602.14626] Concepts' Information Bottleneck Models
Machine Learning

[2602.14626] Concepts' Information Bottleneck Models

This article presents the Concepts' Information Bottleneck Models, which enhance the interpretability of predictions in machine learning ...

arXiv - Machine Learning · 3 min ·
[2602.13316] Semantic Waveforms for AI-Native 6G Networks
Machine Learning

[2602.13316] Semantic Waveforms for AI-Native 6G Networks

This paper introduces a novel semantic-aware waveform design framework for AI-native 6G networks, optimizing resource usage and communica...

arXiv - AI · 3 min ·
[2602.13315] IDPruner: Harmonizing Importance and Diversity in Visual Token Pruning for MLLMs
Llms

[2602.13315] IDPruner: Harmonizing Importance and Diversity in Visual Token Pruning for MLLMs

The paper presents IDPruner, a novel method for visual token pruning in Multimodal Large Language Models (MLLMs), balancing importance an...

arXiv - AI · 4 min ·
[2602.14553] Governing AI Forgetting: Auditing for Machine Unlearning Compliance
Machine Learning

[2602.14553] Governing AI Forgetting: Auditing for Machine Unlearning Compliance

The paper discusses the challenges of ensuring compliance with data deletion requests in AI systems, proposing a novel economic framework...

arXiv - AI · 4 min ·
[2602.14519] DeepMTL2R: A Library for Deep Multi-task Learning to Rank
Machine Learning

[2602.14519] DeepMTL2R: A Library for Deep Multi-task Learning to Rank

DeepMTL2R is an open-source library designed for deep multi-task learning to rank, integrating diverse relevance signals into a unified m...

arXiv - Machine Learning · 3 min ·
[2602.14495] Divine Benevolence is an $x^2$: GLUs scale asymptotically faster than MLPs
Llms

[2602.14495] Divine Benevolence is an $x^2$: GLUs scale asymptotically faster than MLPs

This paper explores the scaling laws of Gated Linear Units (GLUs) compared to Multi-Layer Perceptrons (MLPs), demonstrating that GLUs sca...

arXiv - Machine Learning · 4 min ·
[2602.13308] Learning to Select Like Humans: Explainable Active Learning for Medical Imaging
Machine Learning

[2602.13308] Learning to Select Like Humans: Explainable Active Learning for Medical Imaging

This paper presents an explainable active learning framework for medical imaging that enhances data efficiency and interpretability by in...

arXiv - AI · 4 min ·
[2602.14468] LACONIC: Length-Aware Constrained Reinforcement Learning for LLM
Llms

[2602.14468] LACONIC: Length-Aware Constrained Reinforcement Learning for LLM

LACONIC introduces a novel reinforcement learning method for large language models that balances response length and task performance, ac...

arXiv - Machine Learning · 3 min ·
[2602.14462] Silent Inconsistency in Data-Parallel Full Fine-Tuning: Diagnosing Worker-Level Optimization Misalignment
Llms

[2602.14462] Silent Inconsistency in Data-Parallel Full Fine-Tuning: Diagnosing Worker-Level Optimization Misalignment

This paper explores 'silent inconsistency' in data-parallel fine-tuning of large language models, identifying optimization misalignments ...

arXiv - Machine Learning · 4 min ·
[2602.14452] WiSparse: Boosting LLM Inference Efficiency with Weight-Aware Mixed Activation Sparsity
Llms

[2602.14452] WiSparse: Boosting LLM Inference Efficiency with Weight-Aware Mixed Activation Sparsity

The paper presents WiSparse, a novel method for enhancing the efficiency of large language model (LLM) inference by utilizing weight-awar...

arXiv - AI · 4 min ·
[2602.13290] AGORA: Agentic Green Orchestration Architecture for Beyond 5G Networks
Ai Agents

[2602.13290] AGORA: Agentic Green Orchestration Architecture for Beyond 5G Networks

The AGORA paper presents an innovative architecture for managing Beyond 5G networks, focusing on sustainability by integrating AI-driven ...

arXiv - AI · 4 min ·
[2602.14444] Broken Chains: The Cost of Incomplete Reasoning in LLMs
Llms

[2602.14444] Broken Chains: The Cost of Incomplete Reasoning in LLMs

The paper explores the impact of incomplete reasoning in large language models (LLMs), revealing how different reasoning modalities affec...

arXiv - AI · 4 min ·
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