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Using machine learning to identify individuals at risk for intimate partner violence
Machine Learning

Using machine learning to identify individuals at risk for intimate partner violence

Researchers at Mass General Brigham have developed a series of artificial intelligence (AI) tools that uses machine learning to identify ...

AI News - General · 7 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 ·
Accelerating science with AI and simulations
Machine Learning

Accelerating science with AI and simulations

MIT Professor Rafael Gómez-Bombarelli discusses the transformative potential of AI in scientific research, emphasizing its role in materi...

AI News - General · 10 min ·

All Content

[2603.24639] Experiential Reflective Learning for Self-Improving LLM Agents
Llms

[2603.24639] Experiential Reflective Learning for Self-Improving LLM Agents

Abstract page for arXiv paper 2603.24639: Experiential Reflective Learning for Self-Improving LLM Agents

arXiv - AI · 3 min ·
[2603.25284] SliderQuant: Accurate Post-Training Quantization for LLMs
Llms

[2603.25284] SliderQuant: Accurate Post-Training Quantization for LLMs

Abstract page for arXiv paper 2603.25284: SliderQuant: Accurate Post-Training Quantization for LLMs

arXiv - AI · 4 min ·
[2603.25283] A Gait Foundation Model Predicts Multi-System Health Phenotypes from 3D Skeletal Motion
Llms

[2603.25283] A Gait Foundation Model Predicts Multi-System Health Phenotypes from 3D Skeletal Motion

Abstract page for arXiv paper 2603.25283: A Gait Foundation Model Predicts Multi-System Health Phenotypes from 3D Skeletal Motion

arXiv - AI · 3 min ·
[2603.24638] How unconstrained machine-learning models learn physical symmetries
Machine Learning

[2603.24638] How unconstrained machine-learning models learn physical symmetries

Abstract page for arXiv paper 2603.24638: How unconstrained machine-learning models learn physical symmetries

arXiv - Machine Learning · 4 min ·
[2603.25273] Distribution and Clusters Approximations as Abstract Domains in Probabilistic Abstract Interpretation to Neural Network Analysis
Machine Learning

[2603.25273] Distribution and Clusters Approximations as Abstract Domains in Probabilistic Abstract Interpretation to Neural Network Analysis

Abstract page for arXiv paper 2603.25273: Distribution and Clusters Approximations as Abstract Domains in Probabilistic Abstract Interpre...

arXiv - AI · 3 min ·
[2603.25266] Probabilistic Abstract Interpretation on Neural Networks via Grids Approximation
Machine Learning

[2603.25266] Probabilistic Abstract Interpretation on Neural Networks via Grids Approximation

Abstract page for arXiv paper 2603.25266: Probabilistic Abstract Interpretation on Neural Networks via Grids Approximation

arXiv - AI · 3 min ·
[2603.25158] Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills
Llms

[2603.25158] Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills

Abstract page for arXiv paper 2603.25158: Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills

arXiv - AI · 4 min ·
[2603.25133] RubricEval: A Rubric-Level Meta-Evaluation Benchmark for LLM Judges in Instruction Following
Llms

[2603.25133] RubricEval: A Rubric-Level Meta-Evaluation Benchmark for LLM Judges in Instruction Following

Abstract page for arXiv paper 2603.25133: RubricEval: A Rubric-Level Meta-Evaluation Benchmark for LLM Judges in Instruction Following

arXiv - AI · 3 min ·
[2603.25097] ElephantBroker: A Knowledge-Grounded Cognitive Runtime for Trustworthy AI Agents
Llms

[2603.25097] ElephantBroker: A Knowledge-Grounded Cognitive Runtime for Trustworthy AI Agents

Abstract page for arXiv paper 2603.25097: ElephantBroker: A Knowledge-Grounded Cognitive Runtime for Trustworthy AI Agents

arXiv - AI · 4 min ·
[2603.25075] Sparse Visual Thought Circuits in Vision-Language Models
Llms

[2603.25075] Sparse Visual Thought Circuits in Vision-Language Models

Abstract page for arXiv paper 2603.25075: Sparse Visual Thought Circuits in Vision-Language Models

arXiv - AI · 3 min ·
[2603.25046] MP-MoE: Matrix Profile-Guided Mixture of Experts for Precipitation Forecasting
Machine Learning

[2603.25046] MP-MoE: Matrix Profile-Guided Mixture of Experts for Precipitation Forecasting

Abstract page for arXiv paper 2603.25046: MP-MoE: Matrix Profile-Guided Mixture of Experts for Precipitation Forecasting

arXiv - Machine Learning · 4 min ·
[2603.25035] Mechanistically Interpreting Compression in Vision-Language Models
Llms

[2603.25035] Mechanistically Interpreting Compression in Vision-Language Models

Abstract page for arXiv paper 2603.25035: Mechanistically Interpreting Compression in Vision-Language Models

arXiv - AI · 3 min ·
[2603.25031] From Stateless to Situated: Building a Psychological World for LLM-Based Emotional Support
Llms

[2603.25031] From Stateless to Situated: Building a Psychological World for LLM-Based Emotional Support

Abstract page for arXiv paper 2603.25031: From Stateless to Situated: Building a Psychological World for LLM-Based Emotional Support

arXiv - AI · 4 min ·
[2603.25022] A Public Theory of Distillation Resistance via Constraint-Coupled Reasoning Architectures
Machine Learning

[2603.25022] A Public Theory of Distillation Resistance via Constraint-Coupled Reasoning Architectures

Abstract page for arXiv paper 2603.25022: A Public Theory of Distillation Resistance via Constraint-Coupled Reasoning Architectures

arXiv - Machine Learning · 3 min ·
[2603.24967] The Anatomy of Uncertainty in LLMs
Llms

[2603.24967] The Anatomy of Uncertainty in LLMs

Abstract page for arXiv paper 2603.24967: The Anatomy of Uncertainty in LLMs

arXiv - AI · 3 min ·
[2603.24963] Design Once, Deploy at Scale: Template-Driven ML Development for Large Model Ecosystems
Machine Learning

[2603.24963] Design Once, Deploy at Scale: Template-Driven ML Development for Large Model Ecosystems

Abstract page for arXiv paper 2603.24963: Design Once, Deploy at Scale: Template-Driven ML Development for Large Model Ecosystems

arXiv - Machine Learning · 4 min ·
[2603.24961] Can MLLMs Read Students' Minds? Unpacking Multimodal Error Analysis in Handwritten Math
Llms

[2603.24961] Can MLLMs Read Students' Minds? Unpacking Multimodal Error Analysis in Handwritten Math

Abstract page for arXiv paper 2603.24961: Can MLLMs Read Students' Minds? Unpacking Multimodal Error Analysis in Handwritten Math

arXiv - AI · 4 min ·
[2603.24943] FinMCP-Bench: Benchmarking LLM Agents for Real-World Financial Tool Use under the Model Context Protocol
Llms

[2603.24943] FinMCP-Bench: Benchmarking LLM Agents for Real-World Financial Tool Use under the Model Context Protocol

Abstract page for arXiv paper 2603.24943: FinMCP-Bench: Benchmarking LLM Agents for Real-World Financial Tool Use under the Model Context...

arXiv - AI · 3 min ·
[2603.24933] Decoding Market Emotions in Cryptocurrency Tweets via Predictive Statement Classification with Machine Learning and Transformers
Machine Learning

[2603.24933] Decoding Market Emotions in Cryptocurrency Tweets via Predictive Statement Classification with Machine Learning and Transformers

Abstract page for arXiv paper 2603.24933: Decoding Market Emotions in Cryptocurrency Tweets via Predictive Statement Classification with ...

arXiv - AI · 4 min ·
[2603.24929] LogitScope: A Framework for Analyzing LLM Uncertainty Through Information Metrics
Llms

[2603.24929] LogitScope: A Framework for Analyzing LLM Uncertainty Through Information Metrics

Abstract page for arXiv paper 2603.24929: LogitScope: A Framework for Analyzing LLM Uncertainty Through Information Metrics

arXiv - AI · 3 min ·
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