Search: “research”

Continual Learning for Reliable In-Sequence Molecular Communication

arXiv:2610.20426v1 Announce Type: new Abstract: This paper considers reliable in-sequence molecular communication, where bio-nanomachines exchange molecule-encoded information in a specified order, an

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DGX agent

arXiv:2610.19247v1 Announce Type: new Abstract: Transformers are intuitively considered to be efficient at copying from their inputs. We actually show that the ability of LLMs to copy in context can b

researcharxiv-cs-cl

15 Oct 2026

CORE: Contrast-and-Reflect for Self-Supervised Prompt Optimization in Anomaly Synthesis

arXiv:2610.19610v1 Announce Type: new Abstract: Industrial anomaly detection (AD) is bottlenecked by the scarcity of anomalous samples, making high-fidelity anomaly synthesis crucial for improving dow

Correlation-Aware Contextual Bandits with Surrogate Rewards for LLM Routing

arXiv:2607.09015v2 Announce Type: replace Abstract: We study contextual bandit problems with correlated arms and access to surrogate reward signals produced by a machine learning model, motivated by a

Cortex: Consolidating Context into Parametric Memory

arXiv:2610.20399v1 Announce Type: new Abstract: Context can improve large language model performance, but these gains may be lost after context removal. Inspired by biological systems consolidation, w

Counterfactual Gate-Support Decomposition: Separating Selection from Redistribution in Training-Data Filtering

arXiv:2610.19343v1 Announce Type: cross Abstract: A training-data quality gate changes both which examples survive within regions of the input space and how training mass is distributed across those r

CoWear: Towards Collaborative Wearable Inertial Localization with Multiple Smart Devices

arXiv:2610.20596v1 Announce Type: new Abstract: Consumer smart devices observe the same human motion from different body locations, yet existing inertial-localization benchmarks rarely provide synchro

researcharxiv-cs-ro

Cross-Protocol Personality Assessment with LLMs: Aligning Behavioral Evidence with Human Ratings

arXiv:2610.16050v1 Announce Type: new Abstract: Personality assessment from asynchronous video interviews (AVIs) plays a crucial role in recruitment by enabling standardized and behaviorally grounded

Crossing the Gender Binary: Modelling Gendered Reference in Science Fiction and General Fiction

arXiv:2610.19028v1 Announce Type: new Abstract: Science fiction is widely credited with unsettling gender. This article asks whether that holds at the linguistic level, in how readily gendered referen

DAGFormer: Global Topology Prediction for Transformer Cross-Layer Connections

arXiv:2610.19625v1 Announce Type: new Abstract: We propose DAGFormer, a Transformer language model whose cross-layer connections are planned by a jointly trained topology predictor. Beyond the residua

Data Density Scaling Laws for Image Self-Distillation

arXiv:2610.19013v1 Announce Type: new Abstract: Current scaling law formulations suggest that increasing the number of unique samples in a dataset improves model performance, while repeated exposure t

Dataset-Level Regularization for Joint-Embedding Self-Supervised Learning

arXiv:2610.20158v1 Announce Type: new Abstract: Self-supervised joint embedding learning aligns representations of augmented views while regularizing their distribution to prevent collapse. Regulariza

Decidable Reasoning About Time in Finite-Domain Situation Calculus Theories

arXiv:2402.03164v3 Announce Type: replace Abstract: Representing time is crucial for cyber-physical systems and has been studied extensively in the situation calculus. The most commonly used approach

Deep Generative Models for Phylogenetic Inference with Complex Evolutionary Processes

arXiv:2610.19053v1 Announce Type: new Abstract: Inference of phylogenetic trees from sequences plays a central role in understanding evolutionary relationships, with applications ranging from tracking

Deep Learning for Atmospheric Turbulence Mitigation: A Comparison Between GANs and Transformers

arXiv:2610.19274v1 Announce Type: cross Abstract: Atmospheric turbulence creates complex spatial and temporal distortions that significantly reduce image quality. This work compares two deep learning

Deep Time-series Forecasting Needs Kernelized Moment Balancing

arXiv:2602.00717v2 Announce Type: replace Abstract: Deep time-series forecasting can be formulated as a distribution balancing problem aimed at aligning the distribution of the forecasts and ground tr

Diagnosing Low-Confidence Patient Profiles via Localized Harmful Covariate Shift Detection

arXiv:2610.19178v1 Announce Type: new Abstract: Before deploying clinical prediction models, their reliability must be assessed to ensure safe use. Errors may arise from distribution shifts between tr

Digital Self-Interference Cancellation for In-Band Full-Duplex Systems Based on Transformer Neural Operators

arXiv:2610.19490v1 Announce Type: cross Abstract: Digital-domain self-interference cancellation is essential in in-band full-duplex radios after passive suppression and analog cancellation. It is part

Dimension-Free Scaling Laws for Size Generalization: An Exponential Separation

arXiv:2610.19279v1 Announce Type: new Abstract: Modern machine learning models increasingly operate on variable-size structured data, such as sets and graphs. A central requirement is size generalizat

Dimension-Optimal Dynamic Regret in Exp-Concave Online Learning

arXiv:2610.20187v1 Announce Type: new Abstract: Tracking changing comparators is a central problem in online learning. For exp-concave losses, previous work established the T^{1/3}P_T^{2/3} dependence

Discriminative Score Function: Turning Pretrained Models into Functional Generative Priors

arXiv:2610.19743v1 Announce Type: new Abstract: Discriminative models are trained with task-specific objectives such as classification, detection, or representation learning, yet their practical utili

Do Syntax Heads Influence Model Behavior?

arXiv:2610.19231v1 Announce Type: new Abstract: Transformer language models develop attention heads that specialize in syntactic relations, for example, attending from verbs to their subjects. Do thes

Does the Explanation Drift Before the Guarantee? Label-Free Early Warning on Evolving Graphs

arXiv:2610.16534v1 Announce Type: new Abstract: Deployed models can fail silently as the world they describe evolves. Attribution drift has served as an early warning in tabular data; we ask whether,

DoReMe: Dual optimization of Reconstruction and Motion estimation for self-navigated free-breathing abdominal MRI using Gaussian Splatting

arXiv:2610.19120v1 Announce Type: cross Abstract: Purpose: Free-breathing abdominal MRI is limited by respiratory motion, which introduces image artifacts and k-space inconsistencies. Existing reconst

Dual-arm Cooperation for Tabletop Wiping with Temporal Object Removal

arXiv:2610.19527v1 Announce Type: new Abstract: We devise a dual-arm cooperative planning framework for wiping table surface in the presence of scattered objects. Unlike conventional surface-cleaning

researcharxiv-cs-ro

Dynamic Graph World Modelling: Learning Future Dynamics from Temporal Context

arXiv:2610.19364v1 Announce Type: new Abstract: Dynamic graph learning models how entities and their relations evolve from historical observations to predict future graph states. Existing methods do n

Edgewise Envelopes Between Balanced Forman and Ollivier-Ricci Curvature

arXiv:2603.13535v5 Announce Type: cross Abstract: Evaluating Ollivier-Ricci (OR) curvature on large-scale graphs is computationally prohibitive due to the necessity of solving an optimal transport pro

Embedding Geometry Shapes LLM Routing: Tracing Failure Modes and Improving Generalization

arXiv:2610.19198v1 Announce Type: cross Abstract: With the growing number of LLMs available, selecting which one to use for a prompt has become a key question. A large part of the routing literature r

EmoXpt: Analyzing Emotional Variances in Human Comments and LLM-Generated Responses

arXiv:2501.06597v1 Announce Type: cross Abstract: The widespread adoption of generative AI has generated diverse opinions, with individuals expressing both support and criticism of its applications. T

Empirical Boundaries of Reservoir Computing for Few-Shot Sequence Pattern Tasks

arXiv:2610.19997v1 Announce Type: new Abstract: Efficient sequence modeling remains a fundamental challenge in machine learning. Despite the success of Transformers, recurrent neural networks (RNNs) h

Enabling Tidying Tasks in Robotic Vacuum Cleaners via a Geometry-Induced Self-Locking Deployable Linkage

arXiv:2610.20150v1 Announce Type: new Abstract: Robotic vacuum cleaners must extend their functionality within tight limits on size, cost, and durability. Deployable linkages with few actuators meet t

researcharxiv-cs-ro

Enabling Validation for Robust Few-Shot Recognition

arXiv:2506.04713v4 Announce Type: replace Abstract: A key challenge in Few-Shot Recognition (FSR) is the scarcity of labeled task-specific data for training. Contemporary methods mitigate this challen

Encounter-Driven City-Scale Human Mobility Generation with Large Language Models

arXiv:2610.17672v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for human mobility generation by modeling individual routines, activities, and mobility prefere

Energy-Based Models For Speech Synthesis

arXiv:2310.12765v2 Announce Type: replace-cross Abstract: Recently there has been a lot of interest in non-autoregressive (non-AR) models for speech synthesis, such as FastSpeech 2 and diffusion model

Energy Ring: Stabilizing Feature Energy for Reliable Test-Time Discovery

arXiv:2610.14525v1 Announce Type: new Abstract: Test-Time Discovery (TTD) aims to recognize known classes and detect novel ones while the model is already deployed, operating directly on a continual u

Enhancing Latent World Models with Associative Memory

arXiv:2610.19683v1 Announce Type: cross Abstract: World models trained via latent dynamics offer a scalable path for embodied planning, yet existing methods suffer from representational collapse, comp

EPOCH: Coverage-Aware Evolution with Experiential Preference Optimization for LLM-based Automated Heuristic Design

arXiv:2610.17379v1 Announce Type: new Abstract: LLM-based automated heuristic design (AHD) discovers heuristics for combinatorial optimization problems (COPs), where an LLM generates candidates in an

Equal-information evaluation of credit assignment in modular financial reinforcement learning

arXiv:2610.14750v1 Announce Type: new Abstract: Credit assignment in modular financial reinforcement learning is difficult to evaluate because an attributed signal may improve a component loss without

Evaluating Compressed Memory: Dependence, Utility, and Content Benefit

arXiv:2610.19373v1 Announce Type: new Abstract: Does a language model answer better because its compressed memory contains useful document information? Replacing memory vectors with zeros can lower a

Event Cameras versus Frame Cameras for Synthetic-Aperture Imaging: A Simulation Study

arXiv:2610.20309v1 Announce Type: new Abstract: Synthetic-aperture imaging (SAI) removes occluders such as foliage by integrating many views of a scene along a camera path. It has so far been used mai

Event-Centric Earthquake Monitoring with a Multi-Station Transformer

arXiv:2610.17404v1 Announce Type: cross Abstract: Earthquake catalogs underpin studies such as fault structure, earthquake processes and seismic hazard, and their value depends on being both complete

Evidence-Anchored Overdose Death Prediction from Death Investigation Reports

arXiv:2610.19556v1 Announce Type: new Abstract: Confirmation of overdose deaths in the United States is often delayed due to the complexities of certifying drug-involved deaths. Death investigation re

Exact Scaling Laws for a Random-Features Bigram Model

arXiv:2610.19281v1 Announce Type: new Abstract: Understanding neural scaling laws is increasingly important for theory and practice, yet first-principles explanations remain limited even in simple set

Exploring Interpretability in Deep Learning-Based Forest Classification - Separating Similar Forest Classes using Sentinel-2 Time Series

arXiv:2610.19270v1 Announce Type: new Abstract: The ecological insurance theory posits that diverse forests are more resilient and better able to adapt to changing environmental conditions. Increasing

Exposing AI Inference as a Telco Network API over the 5G User Plane

arXiv:2610.15062v1 Announce Type: new Abstract: Supporting edge Artificial Intelligence (AI) inference as a network service is challenging because current mobile systems can transport tensors but do n

Falsification-proof non-market allocation mechanisms

arXiv:2610.18625v1 Announce Type: cross Abstract: Relying on manipulable characteristics to target the allocation of resources is fraught with difficulties. Naively optimal rules lead to falsification

Fan Out or Relay? Ownership-Aware Routing for LLM Agents Querying Siloed Tables

arXiv:2610.18157v1 Announce Type: cross Abstract: Inside organizations, a question's data often sit with several owners, who query their own tables but never hand them over. An LLM coordinator can fan

Fast Diffusion-GAN Model for Generating Symbolic Music with Emotions

arXiv:2310.14040v2 Announce Type: replace-cross Abstract: Diffusion models have shown promising results for a wide range of generative tasks with continuous data, such as image and audio synthesis. Ho