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[2511.18151] AVERY: Intent-Driven Adaptive VLM Split Computing via Embodied Self-Awareness for Efficient Disaster Response Systems
Llms

[2511.18151] AVERY: Intent-Driven Adaptive VLM Split Computing via Embodied Self-Awareness for Efficient Disaster Response Systems

Abstract page for arXiv paper 2511.18151: AVERY: Intent-Driven Adaptive VLM Split Computing via Embodied Self-Awareness for Efficient Disaster Response Systems

arXiv - Machine Learning · 4 min ·
[2511.13719] Scaling Spatial Intelligence with Multimodal Foundation Models
Llms

[2511.13719] Scaling Spatial Intelligence with Multimodal Foundation Models

Abstract page for arXiv paper 2511.13719: Scaling Spatial Intelligence with Multimodal Foundation Models

arXiv - Machine Learning · 4 min ·
[2511.07732] ViPRA: Video Prediction for Robot Actions
Machine Learning

[2511.07732] ViPRA: Video Prediction for Robot Actions

Abstract page for arXiv paper 2511.07732: ViPRA: Video Prediction for Robot Actions

arXiv - Machine Learning · 4 min ·
[2510.26307] A Survey of Heterogeneous Graph Neural Networks for Cybersecurity Anomaly Detection
Machine Learning

[2510.26307] A Survey of Heterogeneous Graph Neural Networks for Cybersecurity Anomaly Detection

Abstract page for arXiv paper 2510.26307: A Survey of Heterogeneous Graph Neural Networks for Cybersecurity Anomaly Detection

arXiv - Machine Learning · 4 min ·
[2510.25974] Who Leads? Comparing Human-Centric and Model-Centric Strategies for Defining ML Target Variables
Machine Learning

[2510.25974] Who Leads? Comparing Human-Centric and Model-Centric Strategies for Defining ML Target Variables

Abstract page for arXiv paper 2510.25974: Who Leads? Comparing Human-Centric and Model-Centric Strategies for Defining ML Target Variables

arXiv - Machine Learning · 4 min ·
[2510.19372] On the Hardness of Reinforcement Learning with Transition Look-Ahead

[2510.19372] On the Hardness of Reinforcement Learning with Transition Look-Ahead

Abstract page for arXiv paper 2510.19372: On the Hardness of Reinforcement Learning with Transition Look-Ahead

arXiv - Machine Learning · 3 min ·
[2510.17211] Temporally Detailed Hypergraph Neural ODEs for Disease Progression Modeling
Machine Learning

[2510.17211] Temporally Detailed Hypergraph Neural ODEs for Disease Progression Modeling

Abstract page for arXiv paper 2510.17211: Temporally Detailed Hypergraph Neural ODEs for Disease Progression Modeling

arXiv - Machine Learning · 4 min ·
[2510.16082] BIOGEN: Evidence-Grounded Multi-Agent Reasoning Framework for Transcriptomic Interpretation in Antimicrobial Resistance
Ai Agents

[2510.16082] BIOGEN: Evidence-Grounded Multi-Agent Reasoning Framework for Transcriptomic Interpretation in Antimicrobial Resistance

Abstract page for arXiv paper 2510.16082: BIOGEN: Evidence-Grounded Multi-Agent Reasoning Framework for Transcriptomic Interpretation in ...

arXiv - Machine Learning · 4 min ·
[2510.13521] Narrow Operator Models of Stellarator Equilibria in Fourier Zernike Basis
Machine Learning

[2510.13521] Narrow Operator Models of Stellarator Equilibria in Fourier Zernike Basis

Abstract page for arXiv paper 2510.13521: Narrow Operator Models of Stellarator Equilibria in Fourier Zernike Basis

arXiv - Machine Learning · 3 min ·
[2510.12901] SimULi: Real-Time LiDAR and Camera Simulation with Unscented Transforms
Machine Learning

[2510.12901] SimULi: Real-Time LiDAR and Camera Simulation with Unscented Transforms

Abstract page for arXiv paper 2510.12901: SimULi: Real-Time LiDAR and Camera Simulation with Unscented Transforms

arXiv - Machine Learning · 4 min ·
[2510.10324] On some practical challenges of conformal prediction
Machine Learning

[2510.10324] On some practical challenges of conformal prediction

Abstract page for arXiv paper 2510.10324: On some practical challenges of conformal prediction

arXiv - Machine Learning · 3 min ·
[2510.03721] Person-Centric Annotations of LAION-400M: Auditing Bias and Its Transfer to Models
Llms

[2510.03721] Person-Centric Annotations of LAION-400M: Auditing Bias and Its Transfer to Models

Abstract page for arXiv paper 2510.03721: Person-Centric Annotations of LAION-400M: Auditing Bias and Its Transfer to Models

arXiv - Machine Learning · 4 min ·
[2509.25311] Aspects of holographic entanglement using physics-informed-neural-networks

[2509.25311] Aspects of holographic entanglement using physics-informed-neural-networks

Abstract page for arXiv paper 2509.25311: Aspects of holographic entanglement using physics-informed-neural-networks

arXiv - Machine Learning · 3 min ·
[2509.19315] Advancing Few-Shot Pediatric Arrhythmia Classification with a Novel Contrastive Loss and Multimodal Learning

[2509.19315] Advancing Few-Shot Pediatric Arrhythmia Classification with a Novel Contrastive Loss and Multimodal Learning

Abstract page for arXiv paper 2509.19315: Advancing Few-Shot Pediatric Arrhythmia Classification with a Novel Contrastive Loss and Multim...

arXiv - Machine Learning · 4 min ·
[2508.01277] Foundation Models for Bioacoustics -- a Comparative Review
Llms

[2508.01277] Foundation Models for Bioacoustics -- a Comparative Review

Abstract page for arXiv paper 2508.01277: Foundation Models for Bioacoustics -- a Comparative Review

arXiv - Machine Learning · 4 min ·
[2506.23836] Proving the Limited Scalability of Centralized Distributed Optimization via a New Lower Bound Construction
Ai Safety

[2506.23836] Proving the Limited Scalability of Centralized Distributed Optimization via a New Lower Bound Construction

Abstract page for arXiv paper 2506.23836: Proving the Limited Scalability of Centralized Distributed Optimization via a New Lower Bound C...

arXiv - Machine Learning · 4 min ·
[2508.01321] Flow IV: Counterfactual Inference In Nonseparable Outcome Models Using Instrumental Variables
Machine Learning

[2508.01321] Flow IV: Counterfactual Inference In Nonseparable Outcome Models Using Instrumental Variables

Abstract page for arXiv paper 2508.01321: Flow IV: Counterfactual Inference In Nonseparable Outcome Models Using Instrumental Variables

arXiv - Machine Learning · 3 min ·
[2506.04450] Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification
Llms

[2506.04450] Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification

Abstract page for arXiv paper 2506.04450: Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification

arXiv - Machine Learning · 4 min ·
[2505.17288] Learning to Choose or Choosing to Learn: Best-of-N vs. Supervised Fine-Tuning for Bit String Generation
Llms

[2505.17288] Learning to Choose or Choosing to Learn: Best-of-N vs. Supervised Fine-Tuning for Bit String Generation

Abstract page for arXiv paper 2505.17288: Learning to Choose or Choosing to Learn: Best-of-N vs. Supervised Fine-Tuning for Bit String Ge...

arXiv - Machine Learning · 3 min ·
[2505.13213] Diffusion Models with Double Guidance: Generate with aggregated datasets
Machine Learning

[2505.13213] Diffusion Models with Double Guidance: Generate with aggregated datasets

Abstract page for arXiv paper 2505.13213: Diffusion Models with Double Guidance: Generate with aggregated datasets

arXiv - Machine Learning · 3 min ·