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Detecting Chain-of-Thought Hijacking in Backdoored Multimodal Large Reasoning Models

arXiv:2610.16598v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning enables multimodal large reasoning models (MLRMs) to solve complex visual problems, but also exposes them to CoT hijack

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Detecting Unreliable Classifications from Quantized Models

DGX agent

arXiv:2610.18575v1 Announce Type: new Abstract: Post-training INT8 quantization is typically validated by checking accuracy retention, which requires ground-truth labels often unavailable in low-resou

researcharxiv-cs-cv

14 Oct 2026

Deterministic denoising of long-duration gravitational-wave signal candidates with alpha-(de)blending

arXiv:2609.15308v1 Announce Type: cross Abstract: We present a deterministic machine-learning method for denoising candidate signals from all-sky searches for continuous gravitational waves from rotat

DGSfM: Depth-Guided Scale-Aware Global Structure-from-Motion

arXiv:2607.09507v2 Announce Type: replace Abstract: Global Structure-from-Motion (SfM) is an efficient paradigm for recovering camera poses and sparse 3D structure from unordered images. However, its

Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model

arXiv:2502.05505v4 Announce Type: replace-cross Abstract: Differentially private (DP) synthetic data enables the use of sensitive datasets while providing strong privacy guarantees. Recently, Private

DiffGA: Steering Frozen Diffusion Models for Materials Design via Evolutionary Search

arXiv:2610.14999v1 Announce Type: cross Abstract: Steering candidate generation toward user-defined objectives is central to inverse materials design, yet remains difficult when objectives are black-b

DIME: Scaling Facial Representation Learning via Differential Masked Autoencoding

arXiv:2610.17015v1 Announce Type: new Abstract: Scaling up data and model capacity has driven substantial progress in visual representation learning. However, conventional pretext tasks exhibit dimini

DisCo Algebra: Why Disintegration and Combination Are Not Inverses

arXiv:2610.15006v1 Announce Type: cross Abstract: We present DisCo algebra---a compositional framework for joint probability built from a symmetric cooperad (disintegration) and a symmetric operad (co

Disease-level drug approval forecasting from trial-agnostic public data

arXiv:2610.14013v1 Announce Type: cross Abstract: Drug development is an expensive and lengthy process requiring developers to select drugs for human trials and diseases to target. Computational tools

Disentangling Marginal Capacity from Geometry in Optimal-Transport Label Transfer

arXiv:2610.14853v1 Announce Type: new Abstract: Optimal transport (OT) is widely used to align distributions and transfer labels between unpaired source and target data, but source-target composition

Dissociating Answerability from Extraction in LLM Question Answering over Radiology Reports

arXiv:2610.17576v1 Announce Type: cross Abstract: Answering questions from radiology reports involves two decisions: whether the report contains an answer and which span gives it. A false answer prese

Distance Prediction for Quantum Codes

arXiv:2610.18130v1 Announce Type: cross Abstract: The distance of a quantum code is a fundamental metric that dictates its error-correction capability. While quantum low-density parity-check (qLDPC) f

Distributed area coverage path planning subject to the inclusion of a headland path

arXiv:2610.15739v1 Announce Type: new Abstract: A deterministic method for the problem of distributed area coverage path planning subject to the inclusion of a headland path is presented. Given a, in

Distributional Regression for Arbitrary Response Variables Using ReLU Neural Networks

arXiv:2610.16142v1 Announce Type: cross Abstract: This paper develops a unified framework for distributional regression with arbitrary response variables. Rather than relying on scalar thresholds or E

dMRI-F: A Foundation Model for Generalizable Diffusion MRI Analysis from Sparse Acquisitions

arXiv:2610.17968v1 Announce Type: new Abstract: Diffusion MRI (dMRI) probes water diffusion within the brain, providing unique information about tissue microstructure and white matter connectivity. Hi

Does Seeing More Mean Knowing More? Mono-Anchored Advantage Normalization for Multi-Source Visual Reasoning

arXiv:2605.25437v2 Announce Type: replace Abstract: Visual reasoning through reinforcement learning with verifiable rewards (RLVR) has achieved remarkable progress. However, when dealing with multi-so

DPAL: A Test-Time Adaptation Loss for Financial Time Series Forecasting

arXiv:2610.14376v1 Announce Type: new Abstract: Test-time adaptation (TTA) enables time series forecasters to update after deployment as new observations become available. However, adaptation objectiv

DShuttleNet: A Badminton Doubles Dataset for Evaluating Team Coordination

arXiv:2610.14016v1 Announce Type: new Abstract: Most existing sports datasets are individual-centric or ball-centric, focusing on individual player actions while ignoring interactions among teammates.

DTA-GT: Direction- and Topology-Aware Graph Transformer for Neural Network Representation Learning

arXiv:2610.16822v1 Announce Type: new Abstract: Architecture attribute predictors reduce the cost of neural architecture search by estimating accuracy or latency from a small set of evaluated candidat

Dual-Domain Sparse-View 4D CBCT Reconstruction with Spatial-Temporal Consistency Learning

arXiv:2610.18518v1 Announce Type: new Abstract: Four-dimensional cone-beam computed tomography (4D CBCT) provides phase-resolved volumetric images for image-guided radiotherapy. Yet good reconstructio

DVTR-KD: Distilling Vision-Language Models via Intermediate Visual Token Reconstruction

arXiv:2610.17853v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved strong performance on diverse vision-language tasks, but their computational demands limit deploy

E8 Lattice Key Quantization for Low-Bit KV-Cache Compression

arXiv:2610.15384v1 Announce Type: new Abstract: Compressing the key-value (KV) cache is essential for serving long-context large language models (LLMs) under memory constraints. While current scalar q

Early Detection of Pension-Sponsor Distress from Public Filings: A Sponsor Vulnerability Index, Stress-Augmented VaR, and Dynamic Self-Investment Caps

arXiv:2610.14120v1 Announce Type: cross Abstract: A defined-benefit pension is only as safe as its sponsor, yet sponsor distress is under-instrumented relative to plan-side modelling. We present a tra

Edge-Native Temporal--Graph Dual-Expert Inference for Dexterous Grasp Classification

arXiv:2610.14926v1 Announce Type: new Abstract: Multi-finger hands contact objects at different times, so a global close command can overload early-contact fingers while others are still moving. Dense

Efficient Preconditioned Optimization Methods with Frequent Directions

arXiv:2610.16792v1 Announce Type: new Abstract: Adaptive optimization methods have received considerable attention in recent years due to their strong empirical performance. However, they generally re

EgoCPT: Learning Dexterous Manipulation from a Single Ego-Centric Video with Contact-Aware Optimization

arXiv:2610.17572v1 Announce Type: new Abstract: While expert demonstrations on real robots are difficult to collect, human ego-centric videos are easy to collect and abundant on the internet. However,

EgoExplorer: A Vision-Motion-Touch Observatory for Human Loco-Manipulation In Situ

arXiv:2610.18872v1 Announce Type: cross Abstract: Learning humanoid loco-manipulation from human demonstrations rests on observing how locomotion, posture, and object interaction evolve together as ta

ELVIS: Enhance Low-Light for Video Instance Segmentation in the Dark

arXiv:2512.01495v3 Announce Type: replace Abstract: Video instance segmentation (VIS) for low-light content remains highly challenging for both humans and machines alike, due to noise, blur and other

Emergent Loop Geometry in Gauge-Equivariant Graph Neural Networks

arXiv:2610.18742v1 Announce Type: cross Abstract: Gauge-equivariant graph neural networks generate ordered products of gauge links through local message passing, but the geometry of these internal str

Encoding Context into LLM Weights: What Makes It Context?

arXiv:2610.17686v1 Announce Type: cross Abstract: Longer contexts allow large language models (LLMs) to condition their predictions on more information, but inference costs grow prohibitively with con

Equilibrium Learning in Unbounded Stochastic Games with Gaussian Transitions

arXiv:2610.16149v1 Announce Type: cross Abstract: Learning equilibria from data is difficult when several decision makers interact indefinitely and the system state has no prescribed bounds. We examin

Euclidean Distance-Based Flow Matching

arXiv:2610.18534v1 Announce Type: new Abstract: Flow Matching has recently become popular as a technique for generative modeling with applications in many domains. In the standard Flow Matching formul

Evaluating the Causal Faithfulness of SHAP as a Candidate Attribution Method for SAE Features

arXiv:2610.17898v1 Announce Type: new Abstract: Sparse autoencoders decompose language model representations into interpretable features, but feature interpretation in this literature remains predomin

Exact Phase-Type Point Processes for Certified Measurement and Prediction of Event Streams

arXiv:2610.14948v1 Announce Type: new Abstract: Temporal point processes are used both to measure market mechanisms, for example how fast prices absorb news and how much of the reaction is the market

Exact power indices for plurality-voting ensembles

arXiv:2610.17980v1 Announce Type: new Abstract: Plurality-voting ensembles aggregate the predictions of multiple base classifiers and output the most voted class, with ties typically broken at random.

Exact Topological Compliance: Generating Persistence-Equivalent Graphs

arXiv:2610.18856v1 Announce Type: new Abstract: Persistent homology summarizes the topological evolution of a graph as persistence diagrams (PDs). Generating graphs whose topology matches a target des

Explainable Visual Anomaly Detection via Concept Bottleneck Models

arXiv:2511.20088v3 Announce Type: replace Abstract: In recent years, VAD (Visual Anomaly Detection) has attracted significant attention due to its high interpretability, as it provides visual explanat

Explaining Heterogeneous Treatment Effects with Causal Forests and the Hoeffding Functional Decomposition

arXiv:2610.16447v1 Announce Type: cross Abstract: The estimation of heterogeneous treatment effects is a central objective of causal inference. However, state-of-the-art algorithms to solve this task

Explicit Bounds on Hoffman Constants for Sparse Polyhedral Regularizers

arXiv:2610.15241v1 Announce Type: cross Abstract: Hoffman constants quantify the distance to the solution set of a polyhedral system in terms of its residual; they control error bounds, geometric cond

Exploration strategies for Gaussian process bandit optimization with inference regret guarantees

arXiv:2610.16187v1 Announce Type: cross Abstract: Existing cumulative regret guarantees for Bayesian optimization (BO) do not necessarily characterize the quality of the algorithm's final output. This

Explore This! Beat and Downbeat Tracking From a Learned Tatum Grid

arXiv:2610.14817v1 Announce Type: cross Abstract: State-of-the-art beat tracking is based on neural networks that model beats and downbeats as individual events, often followed by a separate Dynamic B

Extending Wire-Driven Parallel Robots to Multi-Floating-Link Systems with an Inter-Body Wire

arXiv:2610.16173v1 Announce Type: new Abstract: Parallel wire-driven systems are a framework in which multiple wires are connected to an end effector, and the end effector is driven by the tensions of

exttt{NFDiag}: High-dimensional MCMC Convergence Diagnosis with Normalizing Flows

arXiv:2610.16574v1 Announce Type: cross Abstract: Accurately assessing the convergence of Monte Carlo Markov Chains is crucial for ensuring their validity in Bayesian inference problems. However, conv

Fast Quantized Johnson-Lindenstrauss Transforms

arXiv:2610.16289v1 Announce Type: new Abstract: Quantization has emerged as one of the primary techniques for reducing the memory footprint of large language models during inference. A prominent examp

FETALFusion: Resolution-Aware State-Space Modeling for Multi-Domain Fetal Head Segmentation

arXiv:2610.17951v1 Announce Type: new Abstract: Head circumference (HC) measured from 2D ultrasound is a routine marker of fetal growth, and automating it needs segmentations whose boundaries hold up

Fisher information and the geometry of memorization in neural networks

arXiv:2610.16161v1 Announce Type: new Abstract: A fruitful approach towards understanding generalization in machine learning involves characterizing how models separate generalizable structure from id

FOCUS: A Subspecialty Foundation Model for Intraoperative Central Nervous System Pathology

arXiv:2610.16914v1 Announce Type: new Abstract: Intraoperative frozen-section diagnosis of central nervous system (CNS) lesions guides surgical decisions but is challenged by artefacts, diagnostic com

Follow the Perturbed Leader for Linear Bandits: sqrt{T} Regret over General Convex Sets

arXiv:2610.17818v1 Announce Type: new Abstract: We give the first adversarial linear bandit algorithm based on Follow-the-Perturbed-Leader (FTPL) that achieves sqrt{T} regret over general convex actio