All Articles
16056 articles total
Harnessing X-ray Absorption Spectroscopy Data through Multimodal Mining of Battery Literature
A multimodal mining pipeline that converts X-ray absorption spectroscopy data from battery literature into a structured, AI-ready open dataset.
Towards simultaneous decoding of kinetic and kinematic movement parameters during grasp and lift task by noninvasive brain imaging
Comparison of regression models for brain-machine interfaces, showing that attention-based regressors excel at simultaneous multi-parameter movement decoding from EEG signals.
Exact Symmetry as Algebra: A Machine-Verified Tensor Calculus that Enforces Physical Selection Rules
Researchers introduce a machine-verified tensor calculus in Lean 4 that enforces exact physical symmetry in ML models, eliminating equivariance errors.
VistaHop: Benchmarking Long-Horizon Visual DeepSearch
VistaHop and VistaArena are introduced as benchmarks to evaluate multimodal LLMs' ability to perform long-horizon visual search and iterative reasoning.
An Empirical Audit of Input Encoders for Multi-Channel Signal Transformers
An empirical study of input encoders for multi-channel signal Transformers suggests that standard per-channel linear projections are practically equivalent to more complex alternatives.
Minimax-Optimal Generalization Bounds for Smooth Deep Neural Networks Trained by (Stochastic) Gradient Descent
This paper provides minimax-optimal generalization bounds for smooth deep neural networks trained via GD and SGD, linking them to kernel methods.
SafeECGMatch: Calibration-Aware Joint Frequency and Time Space Semi-Supervised Learning for Open-Set ECG Classification
SafeECGMatch is a semi-supervised learning framework for ECG classification that uses calibration-aware techniques to handle out-of-distribution anomalies.
Ouroboros-Spatial: Closing the Data-Model Loop for Spatial Reasoning
Ouroboros-Spatial is a self-evolving training framework for MLLMs that closes the data-model loop to improve spatial reasoning efficiency.
Functional Cache Grafting: Robust and Rapid Code-Policy Synthesis for Embodied Agents
FCGraft reduces latency and improves robustness in embodied agent policies by grafting validated function-level KV caches instead of full re-computation.
Keyless Attention: Value-Space Routing and Value-Only Caching for Efficient Transformers
Keyless Attention proposes a value-space routing mechanism that eliminates key representations, reducing KV-cache memory and access overhead by 50%.
Revealing Hidden Model Behaviors with Task-Specific Self-Reports
SAR is a lightweight LoRA adapter designed to audit fine-tuned models by making them report their own hidden behaviors in plain language.
G2VD: Generalizable AI-Generated Video Detection via Counterfactual Intervention and Causal Disentanglement
G2VD is a generalizable AI-generated video detection framework using counterfactual intervention and causal disentanglement to avoid shortcut learning.
The First Transatlantic Telegraph Cable Was a Bold, Beautiful Failure
A historical account of the first transatlantic telegraph cable and its initial failure.
Adaptively Robust LLM Monitoring via Activation Watermarking
Proposed Activation Watermarking (AWM) to prevent adaptive attackers from evading LLM monitoring via hidden state randomization.
GroupRAG: Cognitively Inspired Group-Aware Retrieval and Reasoning via Knowledge-Driven Problem Structuring
Introduces GroupRAG, a framework that uses knowledge-driven keypoint grouping to improve LLM retrieval and reasoning based on cognitive science.
REAP: Automatic Curation of Coding Agent Benchmarks from Interactive Production Usage
Presents REAP, an automated pipeline for curating production-derived benchmarks for AI coding agents, resulting in the Harvest benchmark.
Shot-based quantum encoding: a data-loading paradigm for quantum neural networks
Introduces shot-based quantum encoding (SBQE) to efficiently load classical data into quantum neural networks without data-encoding gates.
The Fast Lane Hypothesis: Von Economo Neurons Implement a Biological Speed-Accuracy Tradeoff
Develops the Fast Lane Hypothesis and a computational model for von Economo neurons to explain biological speed-accuracy tradeoffs in social cognition.
Facial-Expression-Aware Prompting for Empathetic LLM Tutoring
Explores the use of facial-expression-aware prompting to increase empathy and responsiveness in LLM-based tutoring systems.
BioHiCL: Hierarchical Multi-Label Contrastive Learning for Biomedical Retrieval with MeSH Labels
Introduces BioHiCL, a hierarchical multi-label contrastive learning approach for improving biomedical information retrieval using MeSH labels.