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Newest papers, page 113
Multi-view Semantic-aware Resource Allocation for Edge AI
Semantic communication is emerging as a pivotal paradigm to overcome wireless resource scarcity in 6G networks.Joint Independence Testing for Latent Position Random Graphs
Kernel techniques are among the most powerful methods in data science and statistics.MOFjson: An Explicit Topological Representation of Metal-Organic Frameworks for Language Models
Language models for metal-organic frameworks (MOFs) rely on formats that separate atomic geometry from structural topology, forcing models to choose between unstructured coordinate lists and…HIFI: A Highly Efficient Framework for Statistical Inference with Foundation Models
Foundation models provide powerful representations for unstructured data, such as text and images, and parameter-efficient fine-tuning (PEFT) makes their adaptation to downstream tasks increasingly…Error Diffusion Replaces Latent Weights: Training Binary-Weight Language Models on a Few Bits of Dithered State
Binary-weight language models store one bit per weight, but training them keeps a full-precision latent copy of each weight plus Adam state, about 96 extra bits per weight, so a deployed binary…Conditional Diffusion Generation of DVL and Inertial Signals for Underwater Navigation
Autonomous underwater vehicles (AUVs) navigate without satellite positioning and rely on Doppler velocity log (DVL) and inertial sensors for motion estimation.Cumulative Marginal Matching for One-Step Diffusion
The sampling procedures of diffusion and flow-matching models involve hundreds of denoising steps incurring substantial inference time, which has motivated a growing body of work on training schemes…Large Language Models: A Plain-Language Overview for Engineers
Large language models (LLMs) are neural networks trained on huge text collections to generate text by predicting what comes next.HARP-LoRA: Hierarchy-Conditioned Rank Projection for Low-Rank Adaptation in Scientific Table Understanding
Tabular data is widely used in scientific applications, where complex layouts, including multi-level headers, merged cells, captions, and footnotes, make information extraction difficult.Sparse Sum-of-Squares Layers for Certified Learning
A central limitation of modern machine learning systems is the lack of formal certificates guaranteeing their behavior beyond empirical, sample-based evaluation.An Agentic AI Workflow for Liver Lesion Segmentation and Structured Radiology Reporting
Despite advances in automated liver lesion segmentation, a gap remains between image-derived predictions and clinically interpretable radiology reports.How Much Graph Is Too Much? Graph Construction and Exposure in Spatio-Temporal Forecasting
Spatio-temporal graph neural networks combine a node's history with information from graph neighbors.A Battery for AI Propensity Measurement: Rubrics, Synthetic Item Banks, and Annotations
We release a battery of 28 propensities for AI research, with expert-written rubrics, synthetic datasets, and annotated demand intervals, built with the method of Romero-Alvarado et al. (2026).Valid Early Detection of Memorization in Diffusion Models
Diffusion models can sometimes reproduce examples from their training data, a phenomenon known as memorization.One Mean Log-Mel Vector per Phoneme: Simple and Fast Text Injection for Speech Recognition
Text injection trains speech recognition models on unpaired text alongside paired audio.Intrinsic Goals for Autonomous Agents: Hierarchical Exploration Captures Future Volitional Action in Drosophila
Animals have a remarkable capacity for autonomy---driven by intrinsic motivation---without external sensory cues or extrinsic objectives, yet the computational mechanisms behind this ability largely…Cross-Loop Query Handoff: How Later Loops Redirect Two-Hop Retrieval in the Ouro Looped Language Models
How do later loops in a pretrained looped language model repair two-hop retrieval?ResCom: Activation Residual Compensation for Large Language Model Quantization
Low-bit weight--activation quantization reduces the memory and computation needed to deploy large language models, but activation rounding can still degrade accuracy after calibration.Distributed LLM Inference via Communication-Efficient Speculative Decoding
Distributed speculative decoding has emerged as a promising approach for device--server collaborative large language model (LLM) inference, but its decoding speedup is often limited by the…Exponential Wake-Up Overshoot in Explicit Gaussian Point-Process Filters
When events resume after a long silence, explicit Gaussian point-process filters amplify the first update exponentially in the silence duration.