research

Image Denoising via the Adaptive Rank-Cluster Filter

arXiv:2608.15298v1 Announce Type: new Abstract: A spatial-local image-denoising filter is proposed, and its performance metrics are evaluated in comparison with baseline filtering algorithms, includin

Implementation of a Metacognition Framework for Self-Awareness and Self-Regulation in Ensembles of LLMs

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DGX agent

arXiv:2608.15400v1 Announce Type: new Abstract: Large Language Models (LLMs) are notorious for struggling with assessing their own uncertainty, detecting knowledge conflicts, or recognizing when probl

researcharxiv-cs-ai

18 Aug 2026

Improved Regret Analysis for Parallel Gaussian Process Bandit Optimization

arXiv:2608.16492v1 Announce Type: cross Abstract: This paper studies the regret analysis for parallel Gaussian process (GP) bandit optimization. The known regret upper bounds for the widely used GP ba

Improving the matrix multiplication exponent with modern optimization and AlphaEvolve

arXiv:2608.16884v1 Announce Type: cross Abstract: The current best bounds on the matrix multiplication exponent omega are obtained through a refinement of the laser method called combination loss anal

In-Context Learning to Assess Built Environment Impacts on Perceived Neighborhood Walkability Among Mobility-impaired Older Adults

arXiv:2608.14663v1 Announce Type: new Abstract: As global populations age, enhancing neighborhood walkability through inclusive urban design is important for mitigating built environment (BE) barriers

In-Context Source and Channel Coding

arXiv:2601.10267v2 Announce Type: replace Abstract: Separate Source-Channel Coding (SSCC) remains attractive for text transmission due to its modularity and compatibility with mature entropy coders an

In Defense of OCTA: The Reconstruction-Utility Gap in OCT-to-OCTA Synthesis

arXiv:2608.15626v1 Announce Type: new Abstract: Optical coherence tomography angiography (OCTA) images retinal blood flow, giving capillary-perfusion and foveal-avascular-zone biomarkers that grade di

Incision trajectory tracing for electrosurgical navigation by CNN-based knife contacting frames extraction method

arXiv:2608.14749v1 Announce Type: cross Abstract: Background and Objective: Image-guided surgical navigation has been actively studied because of its advantage of identifying subsurface targets and cr

Information-Theoretic Causal Modelling of Semiconductor Process Dynamics

arXiv:2608.14678v1 Announce Type: cross Abstract: With the progress of the semiconductor industry toward increasingly complex compute devices and tighter process tolerances, advanced process control h

Integrating Persuasion Theory into the Epidemiological Modelling of Health Misinformation Spread on Social Media

arXiv:2608.15689v1 Announce Type: cross Abstract: This study presents a hybrid epidemiological and behavioural framework to simulate the spread of health misinformation on social media. We extend the

Intent-Driven Situation Tracking for User-Centric Multi-Turn Agents

arXiv:2608.15755v1 Announce Type: new Abstract: User-centric multi-turn agents must act on an evolving task situation shaped by changing user intents, accumulated tool-grounded facts, missing informat

Invariant Pretraining for Robust Code Representations

arXiv:2608.15412v1 Announce Type: cross Abstract: Encoder-based code representation models remain widely deployed for discriminative tasks such as clone detection and code classification, where their

IP Protection in the Era of Visual Generative AI: A Survey

arXiv:2608.14730v1 Announce Type: new Abstract: The rapid evolution of visual generative AI has introduced a wide range of intellectual property risks, spanning the unauthorized learning, reproduction

Is Grokking a Loss of Normal Hyperbolicity of the Interpolation Manifold?

arXiv:2608.14803v1 Announce Type: new Abstract: A recent line of work recasts the post-memorization phase of grokking as constrained optimization: once a network interpolates the training set, weight

Iterative Self-Learning for Expressive Text-to-Speech Synthesis

arXiv:2608.15910v1 Announce Type: cross Abstract: Expressive text-to-speech (TTS) systems that use explicit conditioning labels provide direct and interpretable control over expressive attributes, in

researcharxiv-cs-cl

Joint Flow Matching Enables Continuous Dose-Conditioned Cell Morphing

arXiv:2608.16424v1 Announce Type: new Abstract: Generative modeling has shown increasing promise for predicting cellular perturbation effects under chemical compound treatments. Existing approaches ei

Joint MDPs and Reinforcement Learning in Coupled-Dynamics Environments

arXiv:2603.06946v2 Announce Type: replace Abstract: Many distributional quantities in reinforcement learning are intrinsically joint across actions, including distributions of gaps and probabilities o

JoLT: Joint Latent Trajectories for Context-Guided High-Resolution Tiled Generation

arXiv:2608.15395v1 Announce Type: new Abstract: Although text-to-image generative models produce impressive results, they struggle to generate densely detailed, high-resolution (HR) images. Current li

KHiM-Mamba: Injecting Pathology Knowledge into Mamba via Hidden-State Modulation for Whole Slide Image Analysis

arXiv:2608.14757v1 Announce Type: cross Abstract: Whole slide image analysis is commonly formulated as multiple instance learning (MIL), where instance features are contextually updated and aggregated

KOALA: Koopman Operator Learning for WiFi-Based Anticipatory Hum

arXiv:2608.15815v1 Announce Type: new Abstract: WiFi Channel State Information (CSI) has emerged as a privacy-preserving alternative to cameras for human pose estimation. However, existing approaches

Koopman early warning signals for bifurcation and rate-induced tipping

arXiv:2608.14716v1 Announce Type: cross Abstract: Abrupt transitions in complex systems are often preceded by early warning signals. However, most indicators rely on the notion of critical slowing dow

KV-Rescue: Recovering Reasoning Language Model KV Eviction Loss via Stepwise Interleaving

arXiv:2608.15797v1 Announce Type: new Abstract: KV-cache eviction caps the memory cost of long reasoning traces but is inherently lossy because the model decodes from a partial view of its history. Un

Large Discovery Models: Empirically-grounded Model-Based Open-Ended Search

arXiv:2608.15669v1 Announce Type: new Abstract: Scientific discovery often involves optimising expensive-to-evaluate objectives over vast, structured, and open-ended hypothesis spaces, such as molecul

Large language model-assisted discovery of cohorts from scientific literature

arXiv:2608.15909v1 Announce Type: cross Abstract: Background: Planning multi-study analyses requires identifying cohorts with the relevant participants, phenotypes, and data modalities. This process c

researcharxiv-cs-cl

Large Language Model Assisted Operational Monitoring for Battery Energy Storage System Integrated Power Distribution Networks

arXiv:2608.15396v1 Announce Type: new Abstract: Battery energy storage systems (BESS) are increasingly used in distribution networks for voltage regulation and demand response, which increases the vol

Large Language Models as Implicit Sociological Models: Reconstructing Voting Behaviour from Sociodemographic Profiles

arXiv:2608.15871v1 Announce Type: cross Abstract: Large language models (LLMs) trained on large-scale internet corpora encode extensive statistical regularities about social identities, attitudes, and

researcharxiv-cs-cl

Large language models as synthetic clinical experts to inform longitudinal rare-disease modeling

arXiv:2608.16507v1 Announce Type: new Abstract: Due to the limited amount of information, modeling longitudinal rare-disease data can benefit from integrating clinical knowledge. Yet, elicitation of e

Learning Auditable Classifier Models: Source-Disjoint Tree Ensembles

arXiv:2608.15725v1 Announce Type: new Abstract: Predictive models in clinical and regulated settings must be accurate and fully auditable. Tree ensembles deliver strong accuracy on tabular data, but t

Learning Discrete Riemannian Metrics for Physical Fields with Cochain-Frame Equivarianc

arXiv:2608.14556v1 Announce Type: new Abstract: Physical fields on meshes require a separation between topology and geometry: conservation laws are topological and should be exact, while geometry, mat

Learning Generalizable Reconstruction of High-Dimensional Neural Dynamics

arXiv:2608.16569v1 Announce Type: new Abstract: Accurate reconstruction of long-duration neural recordings is challenging because local field potentials (LFPs) are high-resolution, multichannel, trans

Learning to Price with Persuasion

arXiv:2608.16699v1 Announce Type: cross Abstract: Motivated by modern marketplaces, where the platform or the seller routinely gathers detailed user profiles, we study a novel learning theoretic model

LightLoc++: Sensor-Robust Representation Learning for Efficient Outdoor LiDAR Localization

arXiv:2608.15317v1 Announce Type: new Abstract: Scene coordinate regression (SCR) achieves strong performance in outdoor LiDAR localization, but it usually requires scene-specific training that can ta

Lightweight Deep Learning-Based Channel Estimation for RIS-Aided Extremely Large-Scale MIMO Systems on Resource-Limited Edge Devices

arXiv:2507.09627v3 Announce Type: replace-cross Abstract: Next-generation wireless technologies such as 6G aim to meet demanding requirements such as ultra-high data rates, low latency, and enhanced c

Lipschitz Bandits with Arbitrary Feedback Delays

arXiv:2608.15036v1 Announce Type: new Abstract: The Lipschitz bandit problem extends the traditional multi-armed bandit framework to continuous action spaces by assuming that the reward functions sati

Local Gains and Fixed-Assignment Set Losses in Shared Set Decoders

arXiv:2608.14717v1 Announce Type: new Abstract: A query-relation deletion can improve the edited slot while reducing the utility of the prediction set that contains it. We study this tension in two re

Logical Embeddings for Argument Analysis

arXiv:2608.15325v1 Announce Type: cross Abstract: We propose a new framework for machine-learning-oriented argument analysis tasks. Our proposal involves replacing traditional contextualized word embe

Longitudinal and Graph-Augmented Prediction of Adolescent Substance Use Onset in the ABCD Study

arXiv:2608.14578v1 Announce Type: new Abstract: Early identification of adolescent substance-use risk is an important prevention challenge, yet the relative value of baseline characteristics, longitud

Look Before You Lift: Visual and Quantitative Diagnostics for Topological Deep Learning

arXiv:2608.15388v1 Announce Type: new Abstract: Topological deep learning (TDL) methods rely on lifting raw data into higher-order discrete domains such as simplicial complexes, cell complexes, and hy

Looks Can be Deceiving: Annotator and Reviewer Performance Across Imagery Sources in Crowd-Sourced Aerial Damage Assessment

arXiv:2608.14942v1 Announce Type: cross Abstract: This paper presents the first known empirical investigation of annotator and reviewer performance across multi-source remotely sensed imagery, evaluat

M-LINKX: Multiview Graph Learning for Brain Cognitive Disease Detection

arXiv:2608.14847v1 Announce Type: new Abstract: Electroencephalogram (EEG) is a non-invasive and relatively low-cost procedure that measures brain electricity for the detection of cognitive diseases.

Machine Learning Approaches to Decoding Topological Quantum Codes

arXiv:2608.15760v1 Announce Type: cross Abstract: Decoding is an essential component of quantum error correction (QEC), translating stabilizer measurement outcomes into corrective actions that suppres

MegaParts: Scaling Part-Aware 3D Object Generation to 300 Parts via Token-Efficient Autoregressive Modeling

arXiv:2608.14783v1 Announce Type: new Abstract: Part-aware 3D object generation is essential for graphics applications such as controllable modeling, editing, and articulation, where objects are repre

Memory-Bounded Continuation of Greedy Sampling for Continual Anomaly Detection

arXiv:2608.15277v1 Announce Type: new Abstract: Greedy sampling produces a compact yet representative summary of normal data, which is essential for reliable anomaly detection that relies on measuring

Mental Model Management: An Operator-Based Framework for LLM Memory

arXiv:2608.15451v1 Announce Type: new Abstract: Large language models process large amounts of information but usually lack an explicit mechanism for maintaining compact and evolving conceptual repres

MIRROR: Multimodal Intelligent Radiology Reasoning and Observation Reporter

arXiv:2608.16709v1 Announce Type: cross Abstract: A radiologist reading a model's output faces two problems. The model returns a number and no reason, and any system that turns that number into readab

MISTac: A Vision-Based Tactile Sensor for Minimally Invasive Surgery

arXiv:2608.14772v1 Announce Type: new Abstract: Minimally invasive and robot-assisted surgery offer many advantages over traditional open surgery, but deprive surgeons of tactile feedback and the abil

researcharxiv-cs-ro

Mitigating Error Accumulation in Co-Speech Motion Generation via Global Rotation Diffusion and Multi-Level Constraints

arXiv:2511.10076v3 Announce Type: replace Abstract: Reliable long-horizon co-speech gesture generation requires precise motion representation and consistent structural priors across all joints. Existi

Mixture of experts architectures for machine learning interatomic potentials

arXiv:2603.07977v3 Announce Type: replace-cross Abstract: Machine Learning Interatomic Potentials (MLIPs) enable accurate large-scale atomistic simulations, yet improving their expressive capacity eff