· ai
[Paper] Open Polymer Challenge: Post-Competition Report
Machine learning (ML) offers a powerful path toward discovering sustainable polymer materials, but progress has been limited by the lack of large, high-quality,...
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- · ai
[Paper] Unsupervised Learning of Density Estimates with Topological Optimization
Kernel density estimation is a key component of a wide variety of algorithms in machine learning, Bayesian inference, stochastic dynamics and signal processing....
- · ai
[Paper] Revisiting the Scaling Properties of Downstream Metrics in Large Language Model Training
While scaling laws for Large Language Models (LLMs) traditionally focus on proxy metrics like pretraining loss, predicting downstream task performance has been ...
- · ai
[Paper] Toward Faithful Retrieval-Augmented Generation with Sparse Autoencoders
Retrieval-Augmented Generation (RAG) improves the factuality of large language models (LLMs) by grounding outputs in retrieved evidence, but faithfulness failur...
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[Paper] No Labels, No Problem: Training Visual Reasoners with Multimodal Verifiers
Visual reasoning is challenging, requiring both precise object grounding and understanding complex spatial relationships. Existing methods fall into two camps: ...
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[Paper] Accelerated Rotation-Invariant Convolution for UAV Image Segmentation
Rotation invariance is essential for precise, object-level segmentation in UAV aerial imagery, where targets can have arbitrary orientations and exhibit fine-sc...
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[Paper] Explainable Anomaly Detection for Industrial IoT Data Streams
Industrial maintenance is being transformed by the Internet of Things and edge computing, generating continuous data streams that demand real-time, adaptive dec...
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[Paper] Decentralized Trust for Space AI: Blockchain-Based Federated Learning Across Multi-Vendor LEO Satellite Networks
The rise of space AI is reshaping government and industry through applications such as disaster detection, border surveillance, and climate monitoring, powered ...
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[Paper] SATGround: A Spatially-Aware Approach for Visual Grounding in Remote Sensing
Vision-language models (VLMs) are emerging as powerful generalist tools for remote sensing, capable of integrating information across diverse tasks and enabling...
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[Paper] DAO-GP Drift Aware Online Non-Linear Regression Gaussian-Process
Real-world datasets often exhibit temporal dynamics characterized by evolving data distributions. Disregarding this phenomenon, commonly referred to as concept ...
- · ai
[Paper] When Tables Leak: Attacking String Memorization in LLM-Based Tabular Data Generation
Large Language Models (LLMs) have recently demonstrated remarkable performance in generating high-quality tabular synthetic data. In practice, two primary appro...
- · ai
[Paper] Siamese-Driven Optimization for Low-Resolution Image Latent Embedding in Image Captioning
Image captioning is essential in many fields including assisting visually impaired individuals, improving content management systems, and enhancing human-comput...