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Artificial Intelligence
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The newest 5,000 papers, from 11 October 2026 to 5 November 2026: 4,998 arXiv preprints and 2 OpenAlex records.
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Newest papers, page 148
A Head Camera Is (Almost) All You Need: An Electronics-Free UMI Glove Labelled and Observed by One Moving Camera
Handheld demonstration devices decouple data collection from the robot, but conventional designs burden the hand with a wrist camera, cables and a pose tracker (SLAM, an IMU, a VR controller, or a…TriGeoBench: A Multimodal Mathematical Geometry Benchmark with Figures and TikZ
Multimodal Large Language Models show strong vision-language capabilities, yet their geometry-centric reasoning remains insufficiently understood.When Does Feedback Help? Auditing Learned Voltage-Clamp Experimental Design
A learned scientific controller can outperform a misspecified planner without benefiting from feedback.SCODEL: Shared Canonical Ontology Definitions for Food Entity Linking and Ontology-Grounded Recipe Knowledge Graphs
Identifying recipe entities and linking them to ontology concepts is fundamental for semantic recipe understanding.BCT: Bayes-Consistent Tempering for Flow Language Models
Temperature scaling is typically applied as a post-hoc transformation of model probabilities.CUA-Recovery: Benchmarking Error Recovery in Long-Horizon Computer-Use Agents
As computer-use agents (CUAs) move to long-horizon workflows spanning multiple applications, undetected errors can silently corrupt persistent state and cause cascading failures in subsequent actions.Corpus Quality Improves, Retrieval Utility Does Not: An Ablation of Preprocessing and Refinement in a Speech-to-QA Pipeline
Practitioners building training corpora with a pipeline of language models keep a preprocessing or refinement (post-process) stage when switching it on raises the corpus quality.A Unified Attack Framework against Statistical Generative Watermarks for Large Language Models
Watermarking has emerged as a key tool for identifying text generated by large language models (LLMs), with current schemes embedding statistical signals into the generation process to enable later…Does Multi-Agent Collaboration Pay When Agents Serve Users? Testing Agent Scaling in Dual-Control Settings
Multi-agent systems (MAS) built from language models are deployed on the premise that collaboration beats a single-agent system (SAS), yet when it pays is unclear.When Can LLM Reasoning Reliably Reuse Intermediate Results?
Sampling complete solutions gives large language models more chances to solve a problem, but each attempt starts again.Inferring continuous cognitive traits from limited neuroimaging data using pairwise convolutional neural networks
Individual differences in cognitive abilities vary widely, yet the structural brain features supporting these differences remain poorly understood.Pairwise Learning Increases Data Efficiency in Deep Neural Networks
Deep neural networks often fail at small-sample regression, collapsing to low-variance predictions that miss individual differences.Reusing Multimodal Agents: Efficient Evaluation of Sound Designs in Games
This paper introduces a novel framework for efficiently evaluating in-game sound designs using multimodal learning and reinforcement learning.CovNav: Conformal Prediction-Guided Adaptive Inference for Object Goal Navigation
In object goal navigation (ObjectNav), an embodied agent must find a target object (e.g., "find a bed") in a previously unseen environment, relying on spatial commonsense such as object co-occurrence.Temporal Evidence Allocation For Longitudinal Clinical Retrieval: A Position And Technical Report
Electronic health records are written to support care, not retrieval.Pattern Intelligence: Unsupervised, LLM-Interpreted Discovery of Systematic Underpayment and Denial Patterns in Healthcare Revenue Cycle Management
Healthcare providers lose substantial revenue to systematic payer underpayments and claim denials, yet identifying the recurring, correctable patterns behind them remains largely manual and does not…EASformer: Environment-Action-State Alignment for Industrial Generative Ranking
Modern industrial ranking systems increasingly adopt generative recommendation (GR) paradigms, in which user behavior sequences and non-sequential (NS) features are tokenized and jointly modeled by…VLA-Retain: Benchmarking Cross-Dimension Effects of Vision Tuning in VLAs
Vision-language-action (VLA) models transfer knowledge from large-scale pretraining into robot control, but their manipulation performance remains sensitive to changes in observation conditions…E8-QAT: Efficient 2-Bit Quantization-Aware Training with Implicit Lattice Codebooks
Low-bit quantization reduces the memory footprint of large language models, but preserving accuracy with efficient training remains challenging.Beyond Calibration: Temporal LLM Confidence Assessment Across Languages and Local Settings
Large language models are expected to estimate their own uncertainty, with confidence signals used to guide retrieval, adaptive compute allocation, routing, and selective abstention.