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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

[2602.14089] TabTracer: Monte Carlo Tree Search for Complex Table Reasoning with Large Language Models
Llms

[2602.14089] TabTracer: Monte Carlo Tree Search for Complex Table Reasoning with Large Language Models

TabTracer introduces a novel Monte Carlo Tree Search framework for enhancing table reasoning in large language models, improving accuracy...

arXiv - AI · 4 min ·
[2602.13871] Ensemble-Conditional Gaussian Processes (Ens-CGP): Representation, Geometry, and Inference
Machine Learning

[2602.13871] Ensemble-Conditional Gaussian Processes (Ens-CGP): Representation, Geometry, and Inference

The paper presents Ensemble-Conditional Gaussian Processes (Ens-CGP), linking ensemble inference with conditional Gaussian laws, enhancin...

arXiv - Machine Learning · 4 min ·
[2602.14010] A Deployment-Friendly Foundational Framework for Efficient Computational Pathology
Llms

[2602.14010] A Deployment-Friendly Foundational Framework for Efficient Computational Pathology

This paper presents LitePath, a foundational framework for computational pathology that significantly reduces computational costs while m...

arXiv - AI · 4 min ·
[2602.13977] WoVR: World Models as Reliable Simulators for Post-Training VLA Policies with RL
Machine Learning

[2602.13977] WoVR: World Models as Reliable Simulators for Post-Training VLA Policies with RL

The paper presents WoVR, a novel reinforcement learning framework that enhances the reliability of world models for Vision-Language-Actio...

arXiv - AI · 4 min ·
[2602.13515] SpargeAttention2: Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning
Machine Learning

[2602.13515] SpargeAttention2: Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning

The paper presents SpargeAttention2, a novel trainable sparse attention method that enhances the efficiency of diffusion models by combin...

arXiv - Machine Learning · 4 min ·
[2602.13476] AsyncVLA: An Asynchronous VLA for Fast and Robust Navigation on the Edge
Llms

[2602.13476] AsyncVLA: An Asynchronous VLA for Fast and Robust Navigation on the Edge

AsyncVLA introduces an asynchronous control framework for robotic navigation, enhancing real-time performance by decoupling semantic reas...

arXiv - Machine Learning · 3 min ·
[2602.13817] What happens when reviewers receive AI feedback in their reviews?
Ai Infrastructure

[2602.13817] What happens when reviewers receive AI feedback in their reviews?

This article examines the impact of AI feedback on peer reviews, revealing both benefits and challenges faced by reviewers when using an ...

arXiv - AI · 3 min ·
[2602.13334] Ask the Expert: Collaborative Inference for Vision Transformers with Near-Edge Accelerators
Machine Learning

[2602.13334] Ask the Expert: Collaborative Inference for Vision Transformers with Near-Edge Accelerators

This article presents a collaborative inference framework for deploying Vision Transformers on edge devices, addressing computational cha...

arXiv - Machine Learning · 3 min ·
[2602.13718] HybridFlow: A Two-Step Generative Policy for Robotic Manipulation
Machine Learning

[2602.13718] HybridFlow: A Two-Step Generative Policy for Robotic Manipulation

The paper presents HybridFlow, a two-step generative policy designed to improve robotic manipulation by enhancing real-time interaction c...

arXiv - AI · 3 min ·
[2602.13704] Pailitao-VL: Unified Embedding and Reranker for Real-Time Multi-Modal Industrial Search
Nlp

[2602.13704] Pailitao-VL: Unified Embedding and Reranker for Real-Time Multi-Modal Industrial Search

The paper presents Pailitao-VL, a multi-modal retrieval system designed for real-time industrial search, addressing key challenges in ret...

arXiv - AI · 4 min ·
[2602.13671] MAS-on-the-Fly: Dynamic Adaptation of LLM-based Multi-Agent Systems at Test Time
Llms

[2602.13671] MAS-on-the-Fly: Dynamic Adaptation of LLM-based Multi-Agent Systems at Test Time

The paper presents MASFly, a novel framework for dynamic adaptation of LLM-based multi-agent systems at test time, enhancing task perform...

arXiv - AI · 3 min ·
[2602.13606] Multi-Modal Sensing and Fusion in mmWave Beamforming for Connected Vehicles: A Transformer Based Framework
Machine Learning

[2602.13606] Multi-Modal Sensing and Fusion in mmWave Beamforming for Connected Vehicles: A Transformer Based Framework

This article presents a novel multi-modal sensing and fusion framework for mmWave beamforming in connected vehicles, enhancing communicat...

arXiv - Machine Learning · 4 min ·
[2602.13547] AISA: Awakening Intrinsic Safety Awareness in Large Language Models against Jailbreak Attacks
Llms

[2602.13547] AISA: Awakening Intrinsic Safety Awareness in Large Language Models against Jailbreak Attacks

The paper presents AISA, a novel defense mechanism for large language models (LLMs) that enhances safety against jailbreak attacks by act...

arXiv - AI · 4 min ·
[2602.13540] On Calibration of Large Language Models: From Response To Capability
Llms

[2602.13540] On Calibration of Large Language Models: From Response To Capability

This paper introduces the concept of capability calibration for large language models (LLMs), emphasizing the importance of accurate conf...

arXiv - Machine Learning · 4 min ·
[2602.14972] Use What You Know: Causal Foundation Models with Partial Graphs
Llms

[2602.14972] Use What You Know: Causal Foundation Models with Partial Graphs

This paper introduces a method for enhancing Causal Foundation Models (CFMs) by incorporating partial causal graph information, improving...

arXiv - Machine Learning · 4 min ·
[2602.13496] Future of Edge AI in biodiversity monitoring
Machine Learning

[2602.13496] Future of Edge AI in biodiversity monitoring

This article explores the role of Edge AI in biodiversity monitoring, analyzing 82 studies to assess system types, architectural trade-of...

arXiv - AI · 4 min ·
[2602.14896] Algorithmic Simplification of Neural Networks with Mosaic-of-Motifs
Machine Learning

[2602.14896] Algorithmic Simplification of Neural Networks with Mosaic-of-Motifs

This paper explores the algorithmic simplification of neural networks through a method called Mosaic-of-Motifs, demonstrating how structu...

arXiv - Machine Learning · 4 min ·
[2602.13446] End-to-End NOMA with Perfect and Quantized CSI Over Rayleigh Fading Channels
Machine Learning

[2602.13446] End-to-End NOMA with Perfect and Quantized CSI Over Rayleigh Fading Channels

This paper presents an end-to-end autoencoder framework for downlink non-orthogonal multiple access (NOMA) over Rayleigh fading channels,...

arXiv - AI · 3 min ·
[2602.13452] LLM-Powered Automatic Translation and Urgency in Crisis Scenarios
Llms

[2602.13452] LLM-Powered Automatic Translation and Urgency in Crisis Scenarios

This article examines the effectiveness of large language models (LLMs) in crisis communication, particularly focusing on multilingual tr...

arXiv - AI · 3 min ·
[2602.13376] An Online Reference-Free Evaluation Framework for Flowchart Image-to-Code Generation
Llms

[2602.13376] An Online Reference-Free Evaluation Framework for Flowchart Image-to-Code Generation

This article presents a novel reference-free evaluation framework for assessing the quality of flowchart image-to-code generation, utiliz...

arXiv - AI · 3 min ·
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