Search: “research”

Conformal Calibration for Multi-Modal Regression with Missing Modalities

arXiv:2608.07795v1 Announce Type: cross Abstract: Prediction intervals for multi-modal regression with tabular variables, text, images, or other input sources are difficult to calibrate when those sou

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Constrained Learning with Universally Learnable Concept Classes

DGX agent

arXiv:2608.08414v1 Announce Type: new Abstract: We study constrained statistical learning over infinite-dimensional hypothesis classes in the fully nonconvex setting, and establish universal PACC lear

researcharxiv-cs-lg

11 Aug 2026

Constraining ontology mappings using metaphysical choices

arXiv:2608.08122v1 Announce Type: new Abstract: In this paper we discuss the foundations behind a novel methodology for the validation of semantic mappings between different data sources based upon di

Continued development of the model based on the SSN [D]

researchr-machinelearning

Back after ~6 months — rebuilding my spiking language model around CPU-first inference Hey everyone. It’s been around six months since I last posted anything about this project here. Some of you might

Contraction Analysis of Holomorphic Dynamical Systems via the Intrinsic Kobayashi Metric

arXiv:2608.07551v1 Announce Type: cross Abstract: This paper studies incremental stability of holomorphic dynamical systems through the infinitesimal Kobayashi metric, an intrinsic pseudometric on com

researcharxiv-cs-ro

Contrastive Mask Fidelity: Reference-Free Auditing of Ground-Truth Masks in Remote Sensing Semantic Segmentation

arXiv:2608.09101v1 Announce Type: new Abstract: Semantic segmentation models are trained and evaluated against human-drawn masks, yet remote-sensing annotations are often coarse, incomplete, or misali

Coordinate-Residual Physics-Driven Neural Network for Electromagnetic Inverse Scattering

arXiv:2608.09382v1 Announce Type: cross Abstract: Electromagnetic inverse scattering is a nonlinear and ill-posed problem, where accurate reconstruction is challenging due to measurement limitations,

CoRe-UIE: Rethinking Coexisting and Region-wise Degradation for Underwater Image Enhancement

arXiv:2608.08965v1 Announce Type: new Abstract: Underwater images often suffer from diverse and coexisting degradations, including color distortion, scattering haze, texture attenuation, and uneven il

Cost Accounting for Reactive Computational Graphs: Exhaustive Sweeps, Sequential Mutation, and the Backward-Locality Gap

arXiv:2607.18323v2 Announce Type: replace-cross Abstract: Exhaustive site-by-site interventions on a neural network's computational graph -- activation-patching sweeps, circuit-discovery searches, sys

CuteTTS: Efficient and High-Quality Speech Synthesis via Autoregressive Modeling of Continuous Latents

arXiv:2608.08638v1 Announce Type: cross Abstract: Zero-shot text-to-speech (TTS) now supports interactive assistants, personalized media, and accessibility tools. All TTS systems require faithful ling

Damage Classification for 3D Point Cloud Data via 3D Data Analysis and Vision Foundation Model-based 2D Projections

arXiv:2608.08955v1 Announce Type: new Abstract: Fine-grained damage classification of 3D point cloud data (PCD) remains a persistent challenge, constrained by high computational demands and limited la

Dancing Points: Synthesizing Ballroom Dancing with Three-Point Inputs

arXiv:2601.02096v2 Announce Type: replace-cross Abstract: Ballroom dancing is a structured yet expressive motion category. Its highly diverse movement and complex interactions between leader and follo

Data collection from highways: a geometric, class-agnostic approach to embedded vehicle counting

arXiv:2608.07643v1 Announce Type: new Abstract: Traffic data collection is dominated today by deep object detectors followed by tracking-by-detection, a pipeline that presupposes what is often missing

Data-Driven Fire-Zone Segmentation for Improved Short-Term Wildfire Prediction

arXiv:2608.07472v1 Announce Type: new Abstract: Wildfire prediction models typically discretize study areas into uniform grids, ignoring the heterogeneous spatial distribution of ignitions. We challen

Data Repetition Beats Data Scaling in Long-CoT Supervised Fine-Tuning

arXiv:2602.11149v2 Announce Type: replace Abstract: Supervised fine-tuning (SFT) on chain-of-thought data is an essential post-training step for reasoning language models. Standard machine learning in

DeCo: Zero-Shot Industrial Anomaly Generation through Decoupling and Recoupling

arXiv:2608.07904v1 Announce Type: new Abstract: Industrial anomaly inspection is severely hindered by the scarcity of real anomalous data.Zero-shot industrial anomaly generation addresses this by gene

Decoding Phenotypes: A Framework for Fusing Genomic Language Models and Neuroimaging

arXiv:2608.08926v1 Announce Type: new Abstract: Neuroimaging and genetic testing are two important clinical references for nervous system diseases, offering complementary diagnostic information. Howev

Deep Learning Imputation of Missing Radius of Maximum Winds (Rmax) Values in Tropical Cyclone Best-Track Data

arXiv:2608.09683v1 Announce Type: new Abstract: Probabilistic coastal hazard assessments require accurate characterization of tropical cyclone (TC) parameters, yet datasets often contain missing recor

Deep Residual Echo State Networks: exploring residual orthogonal connections in untrained Recurrent Neural Networks

arXiv:2508.21172v3 Announce Type: replace-cross Abstract: Echo State Networks (ESNs) are a particular type of untrained Recurrent Neural Networks (RNNs) within the Reservoir Computing (RC) framework,

Degraded Infrared Small Object Detection via Degradation-Adapted Physics-Guided Restoration

arXiv:2608.09311v1 Announce Type: new Abstract: Infrared small object detection has made significant progress in recent years. However, degradations such as fog and nonuniformity can suppress target-b

Detection of Self-Introductions in Legislative Testimony

arXiv:2608.07891v1 Announce Type: new Abstract: Self-introductions are common in legislative committee testimonies. Successfully detecting them and extracting the speaker's name is enormously helpful

Different Feedback, Different Updates: Selective Self-Learning from User Interactions for Large Language Models

arXiv:2608.09109v1 Announce Type: new Abstract: User feedback offers natural supervision for persistent LLM improvement, but a single message may support multiple behavioral changes with different sco

DiffSafeMerge: Mitigating Backdoor Inheritance in Diffusion Model Merging

arXiv:2608.09445v1 Announce Type: cross Abstract: Unconditional diffusion checkpoint merging assumes benign sources, yet a compromised public checkpoint can transfer a dormant backdoor while clean gen

DINO-3DRA: Leveraging 2D Foundation Model Semantics for 3D Cerebral Aneurysm Segmentation

arXiv:2608.07767v1 Announce Type: new Abstract: Accurate aneurysm segmentation in 3D rotational angiography (3DRA) is hindered by extreme class imbalance, morphological similarity to vessels, and abse

Directed Neuro-Symbolic Stochastic Execution for Verification of Distributed Parallel AI Programs

arXiv:2608.07947v1 Announce Type: new Abstract: Distributed parallel Artificial Intelligence (AI) programs expose reliability gaps that conventional testing cannot close: parallel executions are non-d

Distilling CT Foundation Models into Editable Concept Bottlenecks for Lung Nodule Malignancy Prediction

arXiv:2608.07857v1 Announce Type: cross Abstract: Foundation models provide transferable CT representations, but predictions based directly on these embeddings are difficult to interpret. We developed

Diversity Matters: Distributional Feature Coverage Sample Selection for Data-Efficient Backdoor Attacks

arXiv:2608.09047v1 Announce Type: cross Abstract: Backdoor attacks compromise training data so that a model retains clean accuracy but predicts an attacker-chosen target on triggered inputs. At very l

Do AI Forecast Ensembles Sample the Correct Conditional Distribution?

arXiv:2608.08954v1 Announce Type: cross Abstract: Ensemble forecasting aims to sample the conditional distribution of outcomes; whether AI forecast ensembles do this correctly in a joint sense remains

Do Evaluation Metrics Detect Errors in Classical Chinese to English Translations?

arXiv:2608.08283v1 Announce Type: cross Abstract: Although large language models can translate some historical languages surprisingly well, their usefulness in digital humanities workflows is limited

DocPure: Prompt-Free Unified Document Restoration via Degradation-Aware Structure-Guided Wavelet Modulation

arXiv:2608.09536v1 Announce Type: new Abstract: High-quality document images are pivotal for information archiving and downstream automatic processing. However, they are frequently compromised by dive

Doubly Adaptive Channel and Spatial Attention for Semantic Image Communication by IoT Devices

arXiv:2602.22794v2 Announce Type: replace Abstract: Internet of Things (IoT) networks face significant challenges such as limited communication bandwidth, constrained computational and energy resource

DS@GT ARC at Touche: Large Language Models for Retrieval-Augmented Debate

arXiv:2608.08143v1 Announce Type: cross Abstract: We extend the DS@GT ARC working-note submission to the Touche 2025 Retrieval-Augmented Debate task. The task has two subtasks: generating the next utt

DUET: A Diversity-Quality Duet of Distillation Experts for Two-Step Video Generation

arXiv:2608.09637v1 Announce Type: cross Abstract: Diffusion models have enabled high-quality video generation in recent years, but the high cost of iterative sampling hinders their practical deploymen

Dynamic gain neuromodulation attenuates the stability gap under joint training

arXiv:2507.14056v3 Announce Type: replace-cross Abstract: Recent work in continual learning has highlighted the stability gap -- a temporary performance drop on previously learned tasks when new ones

eBIRD: Event-based Intensity Image Reconstruction Using Controllable Diffusion Models

arXiv:2608.08519v1 Announce Type: new Abstract: Intensity-image reconstruction from event streams remains a challenging problem due to the binary, sparse, and asynchronous nature of event data. This w

Efficient identification of critical regions via Flow Matching-based Monte Carlo initialization

arXiv:2508.15318v5 Announce Type: replace-cross Abstract: Markov chain Monte Carlo (MCMC) is a standard tool for studying many-body systems, but its practical cost can become substantial, especially w

EgoBrain: Synergizing Minds and Eyes For Human Action Understanding

arXiv:2506.01353v3 Announce Type: replace Abstract: The integration of brain-computer interfaces (BCIs), in particular electroencephalography (EEG), with artificial intelligence (AI) has shown tremend

EMMR: Emotion-Mediated Multimodal Reasoning for Personality Assessment in Asynchronous Video Interviews

arXiv:2608.07512v1 Announce Type: cross Abstract: Asynchronous Video Interviews (AVIs) have become increasingly popular for personality assessment. Recent large language models (LLMs) have shown poten

Emotion in an active inference model of human driving

arXiv:2608.07480v1 Announce Type: new Abstract: Active inference has emerged as a principled framework for modeling adaptive behavior by balancing goal-directed action with uncertainty reduction. It h

End-to-End Neural Decomposition with Koopman Operators for Time-Series Forecasting

arXiv:2608.08788v1 Announce Type: cross Abstract: Koopman theory offers a linear-operator view of nonlinear sequence dynamics by lifting observations into a space where evolution is governed by a line

Enhanced Real-Time 6-DOF Extended Reality Catheter Tracking for Evaluating Potential Improvement in Efficiency, Precision, and Depth Perception for Cardiac Interventions

arXiv:2608.07606v1 Announce Type: cross Abstract: Despite advances in 3D ultrasound, most percutaneous cardiac interventions still rely on 2D visualization, limiting depth perception and spatial under

Enhancing Knowledge Tracing through Leakage-Free and Recency-Aware Embeddings

arXiv:2508.17092v2 Announce Type: replace-cross Abstract: Knowledge Tracing (KT) aims to predict a student's future performance based on their sequence of interactions with learning content. Many KT m

Entanglement-Free Trajectory Planning for Tethered Mobile Robots with a Slack Tether

arXiv:2608.09860v1 Announce Type: new Abstract: In motion planning algorithms for tethered mobile robots, the entanglement state of the tether is a critical aspect to consider during the planning phas

researcharxiv-cs-ro

Epistemic Transfer in AI-Assisted Verification: A Framework and Evaluation Protocol

arXiv:2608.08882v1 Announce Type: cross Abstract: AI tools that help people judge online claims are usually evaluated while the tool is present. This paper asks a different question: after using such

Error Bound Analysis for the Regularized Loss of Deep Linear Neural Networks

arXiv:2502.11152v4 Announce Type: replace-cross Abstract: The optimization foundations of deep linear networks have recently received significant attention. However, due to their inherent non-convexit

Estimating Uncertainty in Galaxy Morphology Classification

arXiv:2608.08398v1 Announce Type: new Abstract: Astronomers classify galaxy morphology to investigate cosmic evolution. While deep foundation models are increasingly utilized in Galaxy Morphology Clas

Estimation of Spacecraft Inertia Tensor Using Attitude-Only Data from Torque-Free Motion

arXiv:2608.08886v1 Announce Type: new Abstract: We present an attitude-only framework for estimating a spacecraft's normalized inertia tensor from torque-free rotational motion. Our method supports bo

researcharxiv-cs-ro

EvalConvoLearn: An Open-Source Framework for Evaluating Grounded Learner Simulations in Tutoring Conversations

arXiv:2608.07497v1 Announce Type: cross Abstract: Conversational learner simulations are valuable tools for testing learning theories, evaluating instructional materials and automated tutors, or power