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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 ·
[2603.15159] To See is Not to Master: Teaching LLMs to Use Private Libraries for Code Generation
Llms

[2603.15159] To See is Not to Master: Teaching LLMs to Use Private Libraries for Code Generation

Abstract page for arXiv paper 2603.15159: To See is Not to Master: Teaching LLMs to Use Private Libraries for Code Generation

arXiv - AI · 4 min ·
[2602.07374] TernaryLM: Memory-Efficient Language Modeling via Native 1.5-Bit Quantization with Adaptive Layer-wise Scaling
Llms

[2602.07374] TernaryLM: Memory-Efficient Language Modeling via Native 1.5-Bit Quantization with Adaptive Layer-wise Scaling

Abstract page for arXiv paper 2602.07374: TernaryLM: Memory-Efficient Language Modeling via Native 1.5-Bit Quantization with Adaptive Lay...

arXiv - AI · 4 min ·

All Content

[2603.20821] Compass: Optimizing Compound AI Workflows for Dynamic Adaptation
Machine Learning

[2603.20821] Compass: Optimizing Compound AI Workflows for Dynamic Adaptation

Abstract page for arXiv paper 2603.20821: Compass: Optimizing Compound AI Workflows for Dynamic Adaptation

arXiv - Machine Learning · 4 min ·
[2603.20755] Memory-Efficient Fine-Tuning Diffusion Transformers via Dynamic Patch Sampling and Block Skipping
Machine Learning

[2603.20755] Memory-Efficient Fine-Tuning Diffusion Transformers via Dynamic Patch Sampling and Block Skipping

Abstract page for arXiv paper 2603.20755: Memory-Efficient Fine-Tuning Diffusion Transformers via Dynamic Patch Sampling and Block Skipping

arXiv - AI · 4 min ·
[2603.20673] PAVE: Premise-Aware Validation and Editing for Retrieval-Augmented LLMs
Llms

[2603.20673] PAVE: Premise-Aware Validation and Editing for Retrieval-Augmented LLMs

Abstract page for arXiv paper 2603.20673: PAVE: Premise-Aware Validation and Editing for Retrieval-Augmented LLMs

arXiv - AI · 3 min ·
[2603.20648] A Multihead Continual Learning Framework for Fine-Grained Fashion Image Retrieval with Contrastive Learning and Exponential Moving Average Distillation
Machine Learning

[2603.20648] A Multihead Continual Learning Framework for Fine-Grained Fashion Image Retrieval with Contrastive Learning and Exponential Moving Average Distillation

Abstract page for arXiv paper 2603.20648: A Multihead Continual Learning Framework for Fine-Grained Fashion Image Retrieval with Contrast...

arXiv - AI · 4 min ·
[2603.20586] MKA: Memory-Keyed Attention for Efficient Long-Context Reasoning
Llms

[2603.20586] MKA: Memory-Keyed Attention for Efficient Long-Context Reasoning

Abstract page for arXiv paper 2603.20586: MKA: Memory-Keyed Attention for Efficient Long-Context Reasoning

arXiv - AI · 3 min ·
[2603.20562] Permutation-Consensus Listwise Judging for Robust Factuality Evaluation
Llms

[2603.20562] Permutation-Consensus Listwise Judging for Robust Factuality Evaluation

Abstract page for arXiv paper 2603.20562: Permutation-Consensus Listwise Judging for Robust Factuality Evaluation

arXiv - AI · 3 min ·
[2603.20508] Measuring Reasoning Trace Legibility: Can Those Who Understand Teach?
Llms

[2603.20508] Measuring Reasoning Trace Legibility: Can Those Who Understand Teach?

Abstract page for arXiv paper 2603.20508: Measuring Reasoning Trace Legibility: Can Those Who Understand Teach?

arXiv - AI · 4 min ·
[2603.20504] Meeting in the Middle: A Co-Design Paradigm for FHE and AI Inference
Machine Learning

[2603.20504] Meeting in the Middle: A Co-Design Paradigm for FHE and AI Inference

Abstract page for arXiv paper 2603.20504: Meeting in the Middle: A Co-Design Paradigm for FHE and AI Inference

arXiv - AI · 3 min ·
[2603.20442] Detecting Neurovascular Instability from Multimodal Physiological Signals Using Wearable-Compatible Edge AI: A Responsible Computational Framework
Machine Learning

[2603.20442] Detecting Neurovascular Instability from Multimodal Physiological Signals Using Wearable-Compatible Edge AI: A Responsible Computational Framework

Abstract page for arXiv paper 2603.20442: Detecting Neurovascular Instability from Multimodal Physiological Signals Using Wearable-Compat...

arXiv - Machine Learning · 4 min ·
[2603.20406] Thinking in Different Spaces: Domain-Specific Latent Geometry Survives Cross-Architecture Translation
Llms

[2603.20406] Thinking in Different Spaces: Domain-Specific Latent Geometry Survives Cross-Architecture Translation

Abstract page for arXiv paper 2603.20406: Thinking in Different Spaces: Domain-Specific Latent Geometry Survives Cross-Architecture Trans...

arXiv - Machine Learning · 4 min ·
[2603.20397] KV Cache Optimization Strategies for Scalable and Efficient LLM Inference
Llms

[2603.20397] KV Cache Optimization Strategies for Scalable and Efficient LLM Inference

Abstract page for arXiv paper 2603.20397: KV Cache Optimization Strategies for Scalable and Efficient LLM Inference

arXiv - Machine Learning · 4 min ·
[2603.20392] SymCircuit: Bayesian Structure Inference for Tractable Probabilistic Circuits via Entropy-Regularized Reinforcement Learning
Machine Learning

[2603.20392] SymCircuit: Bayesian Structure Inference for Tractable Probabilistic Circuits via Entropy-Regularized Reinforcement Learning

Abstract page for arXiv paper 2603.20392: SymCircuit: Bayesian Structure Inference for Tractable Probabilistic Circuits via Entropy-Regul...

arXiv - Machine Learning · 3 min ·
[2603.20357] Memory poisoning and secure multi-agent systems
Llms

[2603.20357] Memory poisoning and secure multi-agent systems

Abstract page for arXiv paper 2603.20357: Memory poisoning and secure multi-agent systems

arXiv - AI · 4 min ·
[2603.20324] When Agents Disagree: The Selection Bottleneck in Multi-Agent LLM Pipelines
Llms

[2603.20324] When Agents Disagree: The Selection Bottleneck in Multi-Agent LLM Pipelines

Abstract page for arXiv paper 2603.20324: When Agents Disagree: The Selection Bottleneck in Multi-Agent LLM Pipelines

arXiv - AI · 4 min ·
[2603.20296] Collaborative Adaptive Curriculum for Progressive Knowledge Distillation
Ai Infrastructure

[2603.20296] Collaborative Adaptive Curriculum for Progressive Knowledge Distillation

Abstract page for arXiv paper 2603.20296: Collaborative Adaptive Curriculum for Progressive Knowledge Distillation

arXiv - Machine Learning · 3 min ·
[2603.20281] On the Fragility of AI Agent Collusion
Llms

[2603.20281] On the Fragility of AI Agent Collusion

Abstract page for arXiv paper 2603.20281: On the Fragility of AI Agent Collusion

arXiv - AI · 3 min ·
[2603.20256] SciNav: A General Agent Framework for Scientific Coding Tasks
Llms

[2603.20256] SciNav: A General Agent Framework for Scientific Coding Tasks

Abstract page for arXiv paper 2603.20256: SciNav: A General Agent Framework for Scientific Coding Tasks

arXiv - Machine Learning · 4 min ·
[2603.20250] Developing Machine Learning-Based Watch-to-Warning Severe Weather Guidance from the Warn-on-Forecast System
Machine Learning

[2603.20250] Developing Machine Learning-Based Watch-to-Warning Severe Weather Guidance from the Warn-on-Forecast System

Abstract page for arXiv paper 2603.20250: Developing Machine Learning-Based Watch-to-Warning Severe Weather Guidance from the Warn-on-For...

arXiv - Machine Learning · 4 min ·
[2603.20246] Decoding the decoder: Contextual sequence-to-sequence modeling for intracortical speech decoding
Llms

[2603.20246] Decoding the decoder: Contextual sequence-to-sequence modeling for intracortical speech decoding

Abstract page for arXiv paper 2603.20246: Decoding the decoder: Contextual sequence-to-sequence modeling for intracortical speech decoding

arXiv - AI · 4 min ·
[2603.20235] Writing literature reviews with AI: principles, hurdles and some lessons learned
Llms

[2603.20235] Writing literature reviews with AI: principles, hurdles and some lessons learned

Abstract page for arXiv paper 2603.20235: Writing literature reviews with AI: principles, hurdles and some lessons learned

arXiv - AI · 4 min ·
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Machine Learning Large Language Models Generative AI Natural Language Processing Computer Vision Robotics & Embodied AI

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