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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 ·
[2603.16629] MLLM-based Textual Explanations for Face Comparison
Llms

[2603.16629] MLLM-based Textual Explanations for Face Comparison

Abstract page for arXiv paper 2603.16629: MLLM-based Textual Explanations for Face Comparison

arXiv - AI · 4 min ·
[2603.14267] DiFlowDubber: Discrete Flow Matching for Automated Video Dubbing via Cross-Modal Alignment and Synchronization
Machine Learning

[2603.14267] DiFlowDubber: Discrete Flow Matching for Automated Video Dubbing via Cross-Modal Alignment and Synchronization

Abstract page for arXiv paper 2603.14267: DiFlowDubber: Discrete Flow Matching for Automated Video Dubbing via Cross-Modal Alignment and ...

arXiv - AI · 4 min ·

All Content

[2603.01863] Tide: A Customisable Dataset Generator for Anti-Money Laundering Research
Machine Learning

[2603.01863] Tide: A Customisable Dataset Generator for Anti-Money Laundering Research

Abstract page for arXiv paper 2603.01863: Tide: A Customisable Dataset Generator for Anti-Money Laundering Research

arXiv - Machine Learning · 4 min ·
[2603.01195] VisNec: Measuring and Leveraging Visual Necessity for Multimodal Instruction Tuning
Machine Learning

[2603.01195] VisNec: Measuring and Leveraging Visual Necessity for Multimodal Instruction Tuning

Abstract page for arXiv paper 2603.01195: VisNec: Measuring and Leveraging Visual Necessity for Multimodal Instruction Tuning

arXiv - AI · 4 min ·
[2603.01185] Token-level Data Selection for Safe LLM Fine-tuning
Llms

[2603.01185] Token-level Data Selection for Safe LLM Fine-tuning

Abstract page for arXiv paper 2603.01185: Token-level Data Selection for Safe LLM Fine-tuning

arXiv - AI · 3 min ·
[2603.01353] Constructing Synthetic Instruction Datasets for Improving Reasoning in Domain-Specific LLMs: A Case Study in the Japanese Financial Domain
Llms

[2603.01353] Constructing Synthetic Instruction Datasets for Improving Reasoning in Domain-Specific LLMs: A Case Study in the Japanese Financial Domain

Abstract page for arXiv paper 2603.01353: Constructing Synthetic Instruction Datasets for Improving Reasoning in Domain-Specific LLMs: A ...

arXiv - Machine Learning · 3 min ·
[2603.01293] Theoretical Perspectives on Data Quality and Synergistic Effects in Pre- and Post-Training Reasoning Models
Llms

[2603.01293] Theoretical Perspectives on Data Quality and Synergistic Effects in Pre- and Post-Training Reasoning Models

Abstract page for arXiv paper 2603.01293: Theoretical Perspectives on Data Quality and Synergistic Effects in Pre- and Post-Training Reas...

arXiv - Machine Learning · 4 min ·
[2603.01053] Turning Black Box into White Box: Dataset Distillation Leaks
Machine Learning

[2603.01053] Turning Black Box into White Box: Dataset Distillation Leaks

Abstract page for arXiv paper 2603.01053: Turning Black Box into White Box: Dataset Distillation Leaks

arXiv - Machine Learning · 3 min ·
[2603.01264] S2O: Enhancing Adversarial Training with Second-Order Statistics of Weights
Machine Learning

[2603.01264] S2O: Enhancing Adversarial Training with Second-Order Statistics of Weights

Abstract page for arXiv paper 2603.01264: S2O: Enhancing Adversarial Training with Second-Order Statistics of Weights

arXiv - Machine Learning · 3 min ·
[2603.01162] Demystifying Group Relative Policy Optimization: Its Policy Gradient is a U-Statistic
Llms

[2603.01162] Demystifying Group Relative Policy Optimization: Its Policy Gradient is a U-Statistic

Abstract page for arXiv paper 2603.01162: Demystifying Group Relative Policy Optimization: Its Policy Gradient is a U-Statistic

arXiv - Machine Learning · 4 min ·
[2603.00917] Prompt Sensitivity and Answer Consistency of Small Open-Source Large Language Models on Clinical Question Answering: Implications for Low-Resource Healthcare Deployment
Llms

[2603.00917] Prompt Sensitivity and Answer Consistency of Small Open-Source Large Language Models on Clinical Question Answering: Implications for Low-Resource Healthcare Deployment

Abstract page for arXiv paper 2603.00917: Prompt Sensitivity and Answer Consistency of Small Open-Source Large Language Models on Clinica...

arXiv - AI · 4 min ·
[2603.00889] CHIMERA: Compact Synthetic Data for Generalizable LLM Reasoning
Llms

[2603.00889] CHIMERA: Compact Synthetic Data for Generalizable LLM Reasoning

Abstract page for arXiv paper 2603.00889: CHIMERA: Compact Synthetic Data for Generalizable LLM Reasoning

arXiv - AI · 4 min ·
[2603.00951] When Does Margin Clamping Affect Training Variance? Dataset-Dependent Effects in Contrastive Forward-Forward Learning
Machine Learning

[2603.00951] When Does Margin Clamping Affect Training Variance? Dataset-Dependent Effects in Contrastive Forward-Forward Learning

Abstract page for arXiv paper 2603.00951: When Does Margin Clamping Affect Training Variance? Dataset-Dependent Effects in Contrastive Fo...

arXiv - Machine Learning · 4 min ·
[2603.00857] MultiPUFFIN: A Multimodal Domain-Constrained Foundation Model for Molecular Property Prediction of Small Molecules
Llms

[2603.00857] MultiPUFFIN: A Multimodal Domain-Constrained Foundation Model for Molecular Property Prediction of Small Molecules

Abstract page for arXiv paper 2603.00857: MultiPUFFIN: A Multimodal Domain-Constrained Foundation Model for Molecular Property Prediction...

arXiv - Machine Learning · 4 min ·
[2603.00560] Geometry OR Tracker: Universal Geometric Operating Room Tracking
Ai Infrastructure

[2603.00560] Geometry OR Tracker: Universal Geometric Operating Room Tracking

Abstract page for arXiv paper 2603.00560: Geometry OR Tracker: Universal Geometric Operating Room Tracking

arXiv - AI · 4 min ·
[2603.00529] CaptionFool: Universal Image Captioning Model Attacks
Machine Learning

[2603.00529] CaptionFool: Universal Image Captioning Model Attacks

Abstract page for arXiv paper 2603.00529: CaptionFool: Universal Image Captioning Model Attacks

arXiv - AI · 3 min ·
[2603.00502] Trinity: A Scenario-Aware Recommendation Framework for Large-Scale Cold-Start Users
Machine Learning

[2603.00502] Trinity: A Scenario-Aware Recommendation Framework for Large-Scale Cold-Start Users

Abstract page for arXiv paper 2603.00502: Trinity: A Scenario-Aware Recommendation Framework for Large-Scale Cold-Start Users

arXiv - Machine Learning · 3 min ·
[2603.00498] Antibody: Strengthening Defense Against Harmful Fine-Tuning for Large Language Models via Attenuating Harmful Gradient Influence
Llms

[2603.00498] Antibody: Strengthening Defense Against Harmful Fine-Tuning for Large Language Models via Attenuating Harmful Gradient Influence

Abstract page for arXiv paper 2603.00498: Antibody: Strengthening Defense Against Harmful Fine-Tuning for Large Language Models via Atten...

arXiv - Machine Learning · 4 min ·
[2603.00483] RAISE: Requirement-Adaptive Evolutionary Refinement for Training-Free Text-to-Image Alignment
Machine Learning

[2603.00483] RAISE: Requirement-Adaptive Evolutionary Refinement for Training-Free Text-to-Image Alignment

Abstract page for arXiv paper 2603.00483: RAISE: Requirement-Adaptive Evolutionary Refinement for Training-Free Text-to-Image Alignment

arXiv - AI · 4 min ·
[2603.00478] Benchmarking Few-shot Transferability of Pre-trained Models with Improved Evaluation Protocols
Machine Learning

[2603.00478] Benchmarking Few-shot Transferability of Pre-trained Models with Improved Evaluation Protocols

Abstract page for arXiv paper 2603.00478: Benchmarking Few-shot Transferability of Pre-trained Models with Improved Evaluation Protocols

arXiv - Machine Learning · 4 min ·
[2603.00377] Improving Full Waveform Inversion in Large Model Era
Machine Learning

[2603.00377] Improving Full Waveform Inversion in Large Model Era

Abstract page for arXiv paper 2603.00377: Improving Full Waveform Inversion in Large Model Era

arXiv - Machine Learning · 4 min ·
[2603.00363] Quantifying Catastrophic Forgetting in IoT Intrusion Detection Systems
Data Science

[2603.00363] Quantifying Catastrophic Forgetting in IoT Intrusion Detection Systems

Abstract page for arXiv paper 2603.00363: Quantifying Catastrophic Forgetting in IoT Intrusion Detection Systems

arXiv - Machine Learning · 3 min ·
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Machine Learning Large Language Models Generative AI Natural Language Processing Computer Vision Robotics & Embodied AI

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