Search: “research”

How Wrong Can a Good Predictor Be? Diverging Updates with Vanishing Predictive KL

arXiv:2609.11132v1 Announce Type: new Abstract: Accurate posterior prediction need not require accurate approximation of Bayesian updates. We prove that an unbounded gap between the update maps can co

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Identifiability of Nonnegative Tensor Decompositions via Positive Scattering

DGX agent

arXiv:2609.11606v1 Announce Type: cross Abstract: Identifiability of tensor decompositions is often established through linear-algebraic conditions on the factor families. For nonnegative decompositio

researcharxiv-cs-lg

11 Sept 2026

InstantHDR: Single-forward Gaussian Splatting Initialization for HDR 3D Reconstruction

arXiv:2603.11298v3 Announce Type: replace Abstract: High dynamic range (HDR) novel view synthesis (NVS) aims to reconstruct HDR scenes from multi-exposure low dynamic range (LDR) images. Existing HDR

Learning Intrusion Response Strategies for OT Systems

arXiv:2609.10298v1 Announce Type: cross Abstract: Cyberattacks against Operational Technology (OT) systems, which monitor and control industrial processes, pose an increasing threat to essential socie

researcharxiv-cs-ai

Learnware and AI Model Management System

arXiv:2609.11656v1 Announce Type: new Abstract: The transition from file storage to database management systems transformed stored data into managed resources. AI now faces an analogous transition fro

Legible Failures: Detecting and Repairing In-Context Binding Errors

arXiv:2609.11216v1 Announce Type: new Abstract: A wrong answer does not show whether the model lacked the needed information or held it and failed to use it. On an entity-obligation binding task, a la

Leveraging LLMs for Context-Aware Implicit Textual and Multimodal Hate Speech Detection

arXiv:2510.15685v2 Announce Type: replace Abstract: This paper investigates the use of an LLM to generate auxiliary background context for social media posts, and explores four methods to incorporate

Lie-Algebraic Bell Recurrences for Arbitrary-Order Twist Jets and Parallel-Mechanism Closure

arXiv:2609.10748v1 Announce Type: new Abstract: This paper develops an arbitrary-order kinematic construction that links serial propagation, parallel-mechanism closure, and rigid-platform point fields

LoaDiff: Conditional Generation of Electricity Consumption Time Series for Energy Analytics

arXiv:2609.11639v1 Announce Type: new Abstract: The energy transition is reshaping residential electricity consumption through the increasing adoption of distributed generation, electrified appliances

Longitudinal Risk Prediction in Mammography with Privileged History Distillation

arXiv:2603.15814v2 Announce Type: replace Abstract: Longitudinal mammography screening has become an important source of information for improving future breast cancer risk prediction. However, the pe

Measuring the Value of World-Model Updates: A Counterfactual Utility Protocol for Continual Adaptation

arXiv:2609.10954v1 Announce Type: new Abstract: Continual world models must decide whether new data justify changing the model. Fixed replay schedules and prediction-error triggers specify when to upd

Meta-Learning for Classifier Selection in Image Datasets: A Feature-Driven Framework for Accuracy Prediction

arXiv:2609.11041v1 Announce Type: new Abstract: No Free Lunch theorem implies that any performance gains achieved by a classifier on a particular image distribution are necessarily offset by a loss of

Meta-Learning for Data-Efficient Plant Growth Estimation via Vision Transformers and Fuzzy Clustering

arXiv:2609.10749v1 Announce Type: new Abstract: Accurate plant growth estimation is essential for greenhouse monitoring, yet obtaining labeled data remains costly and time-consuming. To address this,

MHE-Former: Multi-Hypothesis Transformers via Entropy Maximization for 3D Mesh Recovery

arXiv:2609.10743v1 Announce Type: new Abstract: Monocular 3D hand and body mesh recovery often suffers from severe occlusion and ambiguity. Traditional deterministic methods typically regress a single

Mi-Ripple: Restoring Images Degraded by Iterative AI Editing

arXiv:2609.11317v1 Announce Type: new Abstract: Iterative reference-conditioned image editing can introduce grid-like and granular textures, commonly described as digital ripple. We present Mi-Ripple,

'Mirror' Large Language Model Evaluations of Depression are Criterion Contaminated

arXiv:2508.05830v3 Announce Type: replace Abstract: Large Language Model (LLM) studies that use language responses elicited from depression assessments to predict scores on those same assessments ofte

Model-Aware Schedules Improve Generation via Fiberwise Optimal Transport

arXiv:2609.11842v1 Announce Type: new Abstract: Diffusion and flow-matching schedules control the signal and noise coefficients that mix data and noise along affine probability paths. Minimizing a kin

Modular Kinematic Reduction of Closed-Chain Mechanisms Using Path Assembly and Defect Homotopy

arXiv:2609.11338v1 Announce Type: new Abstract: Closed kinematic chains complicate modular modeling by coupling active and passive coordinates through nonlinear closure constraints. This paper present

More than half of recent astronomy papers are written with language-model assistance

arXiv:2609.10664v1 Announce Type: cross Abstract: Language models leave a distinctive vocabulary in the prose they help write, and we measure how much of the astronomy literature now carries it. From

MUC-FL: Block-Wise Marginal Utility Contribution for Communication-Efficient Federated Learning

arXiv:2609.10545v1 Announce Type: cross Abstract: Federated Learning (FL) enables distributed model training without centralizing data but suffers from high communication overhead. To address this, we

Musec: MomentUm SpEctral Clipping for Stable Muon-type Training

arXiv:2609.11655v1 Announce Type: new Abstract: Muon has emerged as a highly effective optimizer for large language model training, often achieving superior convergence and performance compared with t

No Screening is More Efficient with Multiple Objects

arXiv:2408.10077v4 Announce Type: replace-cross Abstract: We study the welfare-maximizing allocation of heterogeneous objects when screening uses costly effort rather than monetary transfers. No-scree

OmniKVQuant: KV Cache Quantization for Omni-LLMs

arXiv:2609.11582v1 Announce Type: new Abstract: As Omni-modal large language models (Omni-LLMs) take in audio, video and text together, their KV cache memory cost grows. KV cache quantization is the d

On the Impact of Anonymization on the Performance of Large Language Models

arXiv:2609.11335v1 Announce Type: new Abstract: As large language models are increasingly deployed in sensitive domains, anonymizing input data to protect personally identifiable information has becom

On the Relation between Code Quality and Machine Learning Performance: A Large-scale Empirical Study

arXiv:2609.10610v1 Announce Type: cross Abstract: Context: Computational notebooks are the standard environment for machine learning (ML) development. Within the ML community, model performance is oft

Output Embedding Centering for Stable LLM Pretraining

arXiv:2601.02031v3 Announce Type: replace-cross Abstract: Pretraining of large language models is not only expensive but also prone to certain training instabilities. A specific instability that often

Overpainting: Localized Context-aware Diffusion Image Editing

arXiv:2609.10811v1 Announce Type: new Abstract: We present 'overpainting', an image editing operation which offers both control over the location of the edit and awareness of the previous content in t

Partial GFlowNet: Accelerating Convergence in Large State Spaces via Strategic Partitioning

arXiv:2602.11498v2 Announce Type: replace Abstract: Generative Flow Networks (GFlowNets) have shown promising potential to generate high-scoring candidates with probability proportional to their rewar

Particle GFlowNets: Rethinking Generative Marginalization Models

arXiv:2609.11538v1 Announce Type: new Abstract: Generative Marginalization Models (MaMs) have been recently introduced as efficient neural sampling models for any-order autoregressive modelling of dis

PathoHR: Breast Cancer Survival Prediction on High-Resolution Pathological Images

arXiv:2503.17970v2 Announce Type: replace-cross Abstract: Breast cancer survival prediction in computational pathology presents a remarkable challenge due to tumor heterogeneity. For instance, differe

Periodic robust robotic rock chop via virtual model control

arXiv:2508.02604v4 Announce Type: replace Abstract: Robotic cutting is a challenging, contact-rich manipulation task where the robot must simultaneously negotiate unknown object mechanics, large conta

Perturbation: A simple and efficient adversarial tracer for representation learning in language models

arXiv:2603.23821v2 Announce Type: replace Abstract: Linguistic representation learning in deep neural language models (LMs) has been studied for decades, but finding representations in LMs remains an

PitchFlower: A flow-based neural audio codec with pitch controllability

arXiv:2510.25566v2 Announce Type: replace-cross Abstract: We present PitchFlower, a flow-based neural audio codec with explicit pitch controllability. Our approach promotes pitch disentanglement throu

Planning along Differentiable Charts of Constraint Manifolds with General-Purpose IK Solvers

arXiv:2609.10905v1 Announce Type: new Abstract: Planning trajectories for robot manipulators under kinematic equality constraints restricts feasible motions to a measure-zero submanifold of the config

Polyhedral Geometry of Time-to-First-Spike Neural Networks

arXiv:2609.11227v1 Announce Type: new Abstract: We study the expressivity of spiking neural networks, which provide a natural framework for asynchronous, event-driven computation complementary to conv

Predicting Privacy Leakage from Weight Spectral Density

arXiv:2609.11780v1 Announce Type: new Abstract: Membership inference attacks (MIAs) are widely used to audit the privacy disclosure risk of machine learning models, however current state-of-the-art at

Predicting Train Delays in Finland Using Machine Learning and Weather Data

arXiv:2609.11277v1 Announce Type: cross Abstract: Reliable railway operations depend increasingly on real-time environmental intelligence delivered through wireless sensor infrastructures, a capabilit

Predictive Multi-Landmark OCT Tracking for Increased Motion Robustness

arXiv:2609.11330v1 Announce Type: new Abstract: Optical coherence tomography is a promising modality for markerless motion tracking due to its high spatial resolution and inherent depth perception. Ho

Prevalence Determines Precision:Silent Contamination in Detector-Defined Datasets

arXiv:2609.11449v1 Announce Type: new Abstract: Many ML datasets are constructed by running a detector, heuristic, or model over candidate pools; accepted items become labels. Dataset precision is the

Prototype Matters: Modality-unified Prototype Self-distillation for Unsupervised Visible-infrared Person Re-identification

arXiv:2609.11514v1 Announce Type: new Abstract: Estimating reliable cross-modality association is crucial to unsupervised visible-infrared person re-ID. While optimal transport is shown to be a practi

Quantifying the Memorization-to-Generalization Transition: Scaling Laws and Phase Structure in Grokking

arXiv:2609.10657v1 Announce Type: cross Abstract: Neural networks trained past memorization frequently undergo a delayed transition to generalization, a phenomenon known as grokking. Despite theoretic

Quantum State Preparation with the QNN-based SRBB Algorithm

arXiv:2503.13647v2 Announce Type: replace-cross Abstract: In this work, a novel algorithm structured on Lie algebras for the approximate quantum state preparation problem is proposed, addressing a cha

Quasi-static analysis of passive stability in a novel underactuated multi-finger hand

arXiv:2609.11579v1 Announce Type: new Abstract: Underactuated robotic hands achieve adaptive and robust grasping with a reduced number of actuators, but predicting the stable equilibrium pose of the g

Rebalancing Token Importance in Language Models with TF-IDF Weighted Cross-Entropy Loss

arXiv:2609.11029v1 Announce Type: new Abstract: Large language models are typically trained under uniform token weighting, which allows frequent and low-information tokens to dominate learning and can

ReGround: Grounding Reviewer Comments in Multimodal Evidence

arXiv:2609.11460v1 Announce Type: new Abstract: Reviewer comments naturally relate to specific parts of the reviewed paper, yet grounding these comments to the underlying evidence is difficult due to

Relatively Smart II: Tractable or Semi-Supervised Instance-Optimal Learning

arXiv:2609.10886v1 Announce Type: new Abstract: We continue the study of relatively smart learning, introduced by Dughmi and Pour (2026), which asks a supervised learner to compete, marginal by margin

Rethinking Verbalized Confidence for LLM-as-a-Judge: A Compatibility Shift on Post-2025 Proprietary Models

arXiv:2609.10996v1 Announce Type: new Abstract: Verbalized confidence, long dismissed as overconfident, coarse, and prone to round-number clustering, is now the more robust soft-scoring mechanism for

REVA: Reusable Evidence View Aggregation for Context-Efficient RAG Serving

arXiv:2609.11209v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves knowledge-intensive large language model (LLM) applications by conditioning generation on retrieved docu