Search: “research”

What Breaks in Multi-Image Schema Application? Factorial Oracle Interventions Reveal an Instance-Information Bottleneck

arXiv:2610.19611v1 Announce Type: new Abstract: Modern vision-language models can accept multi-image contexts, but aggregate accuracy rarely reveals where a multi-image reasoning pipeline fails. We st

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What Does Disagreement Mean? A Semantic Identifiability Frontier for Pairwise Preference Learning

DGX agent

arXiv:2610.20450v1 Announce Type: cross Abstract: Pairwise comparison data are a standard supervision signal in preference learning, but disagreement in such data can reflect stable latent heterogenei

researcharxiv-cs-lg

15 Oct 2026

What Is a Clarification? Estimating Model-Dependent Input Ambiguity

arXiv:2610.20052v1 Announce Type: new Abstract: Ambiguous inputs can admit multiple interpretations, each potentially yielding a different answer. Existing work largely treats this ambiguity as a prop

researcharxiv-cs-cl

What the Machine Invented: Mining New Mathematical Instruments from OpenAI's October 2026 Release of AI-Generated Mathematics

arXiv:2610.17090v1 Announce Type: cross Abstract: On 6 October 2026 OpenAI published an initial 722 AI-written mathematical manuscripts, organized into 372 problem families, in the public repository g

When a Conceptor Complement Becomes Gain: Operator Geometry and Behavioral Attribution in Language Models

arXiv:2610.16325v1 Announce Type: new Abstract: When a steering intervention changes a language model's behavior, which part of the intervention deserves the credit? We test this question for a target

When Do Discrete Actions Make Good Continuous Controllers?

arXiv:2610.20429v1 Announce Type: new Abstract: Though modern AI models like LLMs predict discrete tokens, today's robotic foundation models represent actions as continuous vectors. In this paper, we

researcharxiv-cs-ro

When Does Task-Aware Imputation Matter? An Analysis of Robustness Under Train-Test Mismatch

arXiv:2610.20342v1 Announce Type: new Abstract: Missing data is a pervasive challenge in machine learning, often degrading predictive performance and complicating model deployment. Most existing appro

When Does the Dependency Graph Help Code-to-Architecture Mapping?

arXiv:2610.19769v1 Announce Type: cross Abstract: Architectural technical debt arises when a system's implementation drifts from its inten ded modular decomposition, while the mapping between source f

Where Do LLM Ensemble Gains Come From? Decomposing Candidate Value, Diversity, and Aggregation

arXiv:2610.18786v1 Announce Type: cross Abstract: LLM ensemble gains are often measured against a single baseline, but the value attributed to additional candidates can change with the comparison used

Where Polanyi Meets Galois: Tacit Knowing as an Algebro-Deterministic Operation, Toward Re-rooting AI-Generated Science

arXiv:2610.16102v1 Announce Type: cross Abstract: We argue that tacit knowing is better modelled as an operating regime of one memory substrate than as a kind of content. The substrate is VaCoAl, an a

Which Knowledge Should LLMs Trust? Uncovering a Generalizable Steering Direction Across Knowledge Conflicts

arXiv:2610.20067v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently encounter conflicts between internal parametric knowledge and external contextual knowledge, yet the mechanisms

researcharxiv-cs-cl

Why Generate a Click? Plug-in Decision Heads for Web Agents

arXiv:2610.20107v1 Announce Type: new Abstract: Web agents built on vision language models decide every action by generating text such as click(12), although most of that text encodes a choice among a

researcharxiv-cs-cl

Why Software Engineering Is Indispensable in the Age of Coding Agents

arXiv:2610.10226v2 Announce Type: replace-cross Abstract: Can AI make Software Engineering (SE) -- the discipline -- obsolete? And can it make software engineers -- the professionals -- redundant? Thi

WinARDet: Compressed Window Auto-Regression for Long-Horizon Vision-Language Grounding

arXiv:2610.19419v1 Announce Type: new Abstract: MLLM-based detectors formulate vision-language grounding as autoregressive coordinate generation, yet in dense scenes, they often collapse into a box re

3D Gaussian Splatting for Fine-grained Urban Scene Reconstruction via Semantic-guided Density Control and Loss Design

arXiv:2610.16292v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has been becoming a promising 3D reconstruction technique because of its advantage of high-fidelity rendering effect with h

3DXTalker: Unifying Identity, Lip Sync, Emotion, and Spatial Dynamics in Expressive 3D Talking Avatars

arXiv:2602.10516v4 Announce Type: replace Abstract: Audio-driven 3D talking avatar generation is increasingly important in virtual communication, digital humans, and interactive media, where avatars m

4LC: 4D Latent Cache for Efficient Conditioning in Dynamic World Modeling

arXiv:2610.17625v1 Announce Type: new Abstract: For video generation in dynamic world modeling, observed static and dynamic content should be efficiently reused to provide conditions for repeated gene

A 4-Qubit Variational Quantum Classifier for Sequence-Specific Classification of DNMT3A and DNMT3B Flanking Methylation Preferences

arXiv:2610.15998v1 Announce Type: new Abstract: DNA methylation is a critical epigenetic modification that regulates gene expression and genome stability, primarily catalyzed by the DNA methyltransfer

A Behavior-first approach to Multi-Intention Inverse Reinforcement Learning

arXiv:2602.07496v2 Announce Type: replace Abstract: Inverse Reinforcement Learning (IRL) seeks to infer reward functions from expert demonstrations. When demonstrations originate from multiple experts

A Bethe-Ansatz Source of Early Token Correlations: A marginal-preserving construction for parallel proposals

arXiv:2610.16781v1 Announce Type: cross Abstract: Parallel token proposals in language-model decoding need a joint law, not merely accurate token marginals. We construct a family of coordinate-Bethe-a

A Controlled Evaluation of Curvature Inspired Scalar Feature Scaling for Domain Generalization

arXiv:2610.18227v1 Announce Type: cross Abstract: Domain-specific curvature is an appealing idea for domain generalization (DG), but curvature learning can denote substantially different computations.

A Differentiable 3D Scene Graph Metric via Contextual Hellinger Triplet Geometry

arXiv:2610.17705v1 Announce Type: new Abstract: 3D scene graph prediction is commonly supervised with local object and predicate classification losses. Although effective for slot-wise label predictio

A Generalized McDiarmid Inequality: Sample Reuse and Non-Uniform Unbounded Differences

arXiv:2610.17159v1 Announce Type: cross Abstract: We develop a novel generalization of McDiarmid's concentration inequality and use it to obtain a uniform law of large numbers result and error bounds

A Geometrical Approach to Constructing Neural Networks for Perfect Training-set Classification

arXiv:2610.17312v1 Announce Type: new Abstract: This paper proposes a method for constructing a neural network that achieves perfect classification of all samples in a given training set, without taki

A Hybrid Kinematic GCN and Elastic Transformer for Efficient Indian Sign Language Recognition

arXiv:2610.14680v1 Announce Type: cross Abstract: Sign Language Recognition (SLR) presents complex challenges due to variable signing speeds and spatial intricacies. Specifically, Indian Sign Language

A Method for Exact Enforcement of Boundary Conditions on General Curved Triangular Domains: Algorithm and Application to Scientific Machine Learning

arXiv:2610.17392v1 Announce Type: cross Abstract: We present a method for enforcing exactly Dirichlet, Neumann, and Robin conditions on general triangular domains with arbitrarily curved boundaries. T

A Note on Graphon-Signal Analysis of Graph Neural Networks

arXiv:2508.18564v2 Announce Type: replace Abstract: A recent paper, ``A Graphon-Signal Analysis of Graph Neural Networks'', by Levie, analyzed message passing graph neural networks (MPNNs) by embeddin

A Novel GPT-Based Framework for Anomaly Detection in System Logs

arXiv:2510.16044v2 Announce Type: replace-cross Abstract: Identification of anomalous events within system logs constitutes a pivotal element within the frame- work of cybersecurity defense strategies

A physics-coupled graph neural operator for mid-plane six-component stress tensor field prediction in concrete penetration

arXiv:2610.16996v1 Announce Type: new Abstract: The penetration-resistant design of concrete structures requires the spatiotemporal evolution of the stress field within the target, whereas in design o

A Rate Transfer Method: Convergence Rates in Stochastic Gradient Descent via Stochastic Calculus

arXiv:2610.18739v1 Announce Type: new Abstract: We develop a rate-transfer method that converts finite-time Lyapunov estimates for an associated stochastic differential equation (SDE) into finite-time

A Refresh Interval Does Not Fully Specify a Refresh Schedule: Learning-Rate-Dependent Placement in Kronecker-Preconditioned Language Model Training

arXiv:2610.18695v1 Announce Type: new Abstract: Kronecker-preconditioned optimizers recompute a cached curvature eigendecomposition only periodically, and implementations and adaptive methods control

A Stochastic Analysis Perspective on Diffusion Models

arXiv:2610.14133v1 Announce Type: cross Abstract: Generative modelling involves two complementary tasks: learning a probabilistic approximation of an unknown data distribution from observations, and d

A temporal graph dissimilarity measure capturing epidemic spreading behavior

arXiv:2610.16456v1 Announce Type: cross Abstract: Comparing temporal networks is a challenging problem in network analysis. Commonly adopted methods compare structural properties of temporal graphs an

A Time-Synchronous Prequential Evaluation Framework for Next-Week Student Disengagement Prediction from Moodle LMS Logs

arXiv:2610.17490v1 Announce Type: new Abstract: Retrospective evaluation of early-warning models may not reflect information available when predictions are issued and outcomes become observable. We de

Accelerating Cross-Model LLM Inference via Attention Map Reuse

arXiv:2610.14688v1 Announce Type: new Abstract: LLM-augmented data workflows often involve multiple heterogeneous models operating over substantial shared context, such as schemas, tool specifications

Accounting for model error in ensemble variational data assimilation through learned generative dynamics

arXiv:2610.17333v1 Announce Type: cross Abstract: Many approaches have recently been proposed to combine data assimilation with machine learning for improved forecasts with geophysical models. Here, w

ACED: Reference-Anchored Aggregation of Natural-Language and Executable Evidence for Mathematical Reasoning

arXiv:2610.16635v1 Announce Type: new Abstract: Natural-language self-consistency and executable programs provide complementary test-time evidence for mathematical reasoning, yet either channel may su

Active Neural Matter: A Finite-Window Response Framework for Physical Systems and Distributed AI Workflows

arXiv:2610.14549v1 Announce Type: new Abstract: Physical systems and distributed AI workflows can retain past information, receive delayed feedback and combine conflicting signals. These features pose

AD-GS: Anatomical Density-guided 3D Gaussian Splatting for Sparse-View Dental CBCT Reconstruction

arXiv:2610.14963v1 Announce Type: new Abstract: Sparse-view Cone-Beam Computed Tomography (CBCT) reconstruction is essential for reducing radiation dose and scan effort, but remains underconstrained d

Adaptive-Depth Is a Finishing Stage

arXiv:2610.14252v1 Announce Type: new Abstract: Looped transformers reuse the same layer multiple times, allowing inference compute to be adjusted without changing the model. Recent adaptive-depth met

Adaptive Interaction Network for Human Motion Prediction During Human-Robot Collaboration

arXiv:2610.16624v1 Announce Type: new Abstract: Human motion prediction during human-robot collaboration is critical for achieving safe and efficient interactions in shared environments. Unlike previo

Adaptive Look, Flexible Thought: Learning How and How Long to Think in Multimodal Reasoning

arXiv:2610.15810v1 Announce Type: new Abstract: The introduction of long chain-of-thought (CoT) reasoning and external tools has substantially improved the performance of multimodal large language mod

Adaptive Robust Confidence Sets in High Dimensions

arXiv:2610.15723v1 Announce Type: cross Abstract: We study adaptive confidence sets for mean vectors of multivariate Gaussians with identity covariance under Huber contamination when the contamination

Aerodynamic Promptness of Tilting-Propeller Multirotors

arXiv:2610.16532v1 Announce Type: cross Abstract: This work develops a geometric theory of aerodynamic promptness for multirotor platforms whose propeller directions depend on a smooth orientation-mec

researcharxiv-cs-ro

AERR-Nav: Adaptive Exploration-Recovery-Reminiscing Strategy for Zero-Shot Object Navigation

arXiv:2603.17712v1 Announce Type: cross Abstract: Zero-Shot Object Navigation (ZSON) in unknown multi-floor environments presents a significant challenge. Recent methods, mostly based on semantic valu

Agreement versus Softmax under Spatial Disambiguation

arXiv:2610.14210v1 Announce Type: cross Abstract: ScanRefer Multiple queries require spatial disambiguation: several instances of the target class are present, and the referencer must pick one. When p

AI-Assisted Tumor-Growth Law Discovery from Sparse Data: Refitting and LLM-Based Ranking

arXiv:2610.16891v1 Announce Type: new Abstract: Inferring tumor-growth laws from sparse, noisy observations requires more than accurate curve fitting. We study an AI-assisted workflow involving symbol

AI-Enhanced Hyperspectral Imaging for Intraoperative Detection of Low-Grade Glioma: A Clinical Study

arXiv:2610.17944v1 Announce Type: new Abstract: Current image-guided neuronavigation techniques, such as intraoperative MRI and ultrasound, are limited by high costs, limited sensitivity and operation