Search: “research”

Using OCR Heads to Verbalize Image Semantics

arXiv:2609.18823v1 Announce Type: cross Abstract: How do VLMs map from pixels to semantics? To understand this general question, we focus on a narrow one: studying how VLMs perform optical character r

UWA360CAM: A 360^{irc} 24/7 Real-Time Streaming Camera System for Underwater Applications

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DGX agent

arXiv:2309.12668v3 Announce Type: replace Abstract: Omnidirectional camera is a cost-effective and information-rich sensor highly suitable for many marine applications and the ocean scientific communi

researcharxiv-cs-ro

17 Sept 2026

VCTP: Vehicle-Conditioned Terrain Planning for Off-Road Navigation

arXiv:2609.17834v1 Announce Type: new Abstract: A vehicle's heading affects both the surfaces beneath its tires and its pitch and roll. We present Vehicle-Conditioned Terrain Planning (VCTP), which re

Visual Input and Its Framing Affect Attribute-based Descriptions Produced by Large Vision-Language Models

arXiv:2609.18345v1 Announce Type: new Abstract: Large vision-language models (LVLMs) are commonly used with only a single text prompt as the input, or plus an image. In this paper, we demonstrate that

Voice of Reason: Reinforcement Learning for Spoken Math

arXiv:2609.18677v1 Announce Type: new Abstract: Speech language models enable richer spoken interactions between humans and machines than cascaded systems, allowing access to paralinguistic informatio

WAVE-Go: World-Model Navigation with Adaptive Execution for Wheel-Legged Robots

arXiv:2609.18193v1 Announce Type: new Abstract: World models can anticipate the consequences of navigation actions, but predicted action sequences may become invalid during execution, especially when

Weakening Neurons: An Input-Output Functionality in Transformers with Outsize Influence

arXiv:2609.18612v1 Announce Type: cross Abstract: We analyze the learned input-output behavior of GLU-based neurons in large language models (LLMs). We propose a simple analysis method: For each neuro

When Edit Flows are Edit Jumps: replicating Edit Flows and EvoFlows

arXiv:2609.18745v1 Announce Type: new Abstract: Antibody lead optimization calls for a small, bounded set of edits to an existing candidate: substitutions, but also insertions and deletions. Edit-base

When Is Graph Structure Worth Its Cost? The Case for Structure Pricing in Retrieval-Augmented Generation

arXiv:2609.18099v1 Announce Type: new Abstract: Graph-based retrieval-augmented generation (RAG) can help answer questions that require information from many documents. However, building a graph often

'You are an expert annotator': Automatic Best-Worst-Scaling Annotations for Emotion Intensity Modeling

arXiv:2403.17612v3 Announce Type: replace Abstract: Labeling corpora constitutes a bottleneck to create models for new tasks or domains. Large language models mitigate the issue with automatic corpus

3D Field Data Reduction with Adaptive Sample-Based Gaussian-Encoded Reconstruction

arXiv:2609.16024v1 Announce Type: cross Abstract: In scientific simulation, regular grids, unstructured meshes, and particle-based formats are chosen to represent field data for computational efficien

A multimodal large language model for evidence-based autism spectrum disorder screening

arXiv:2609.16464v1 Announce Type: new Abstract: The clinical management of autism spectrum disorder (ASD) faces a bottleneck in early screening, mainly because trained specialists are scarce and conve

A panoramic aerodynamic performance prediction method for turbomachinery cascades using transformer-enhanced neural operator

arXiv:2609.16066v1 Announce Type: new Abstract: To enable flexible and rapid aerodynamic performance evaluation in turbomachinery design, this paper proposes a panoramic performance prediction framewo

A Spectral Decomposition Framework for Multiscale Nonlinear Dimensionality Reduction

arXiv:2604.02535v2 Announce Type: replace Abstract: Dimensionality reduction (DR) involves two longstanding trade-offs. First, preserving local neighborhoods can come at the cost of global structure.

AI for Games in the Foundation Model Era

arXiv:2609.16679v1 Announce Type: new Abstract: Foundation models, alongside advances in learned game-world models, are reshaping AI across the game lifecycle. Beyond playing games, recent systems mod

AI Policies: Help or Hindrance? A Software Developer's Perspective

arXiv:2609.16496v1 Announce Type: cross Abstract: AI policies introduced by software organisations to mitigate LLM-related risks such as sensitive information leaks and unauthorised usage are not usef

Amortized Probabilistic Retrieval of Atmospheric CO2 from OCO-2 Spectra Using Deep Learning with Laplace Approximations and Normalizing Flows

arXiv:2606.17413v2 Announce Type: replace Abstract: Space-based monitoring of atmospheric carbon dioxide (CO_2) constrains the global carbon budget. NASA's Orbiting Carbon Observatory-2 (OCO-2) estima

Anatomy-Change-Aware Bidirectional Selective State-Space Memory for Clinically Deployed Thoracic Radiotherapy Auto-Contouring

arXiv:2609.16036v1 Announce Type: cross Abstract: We developed DAMM-Net++, a 2.5D architecture for thoracic OAR and target volume segmentation that addresses three persistent challenges in radiotherap

ANIMASK: What the Model Contributes to Role Play in Simulated Story Worlds

arXiv:2609.16667v1 Announce Type: new Abstract: When a language model plays a character, the observed behavior reflects both the assigned persona and the default dispositions of the actor model itself

AntennaFlow: A Generative Flow Model for Offset Correction in Phaseless Antenna Testing

arXiv:2609.16948v1 Announce Type: new Abstract: Near-field to far-field transformation is central to large-aperture antenna testing, yet two coupled challenges remain: costly phase acquisition at mill

Safety

Artificial intelligence and biosecurity: capabilities, threat pathways, and defense-in-depth governance

arXiv:2609.16213v1 Announce Type: new Abstract: Artificial intelligence is reshaping biological research across an increasingly connected digital-to-physical workflow. General-purpose large language m

safetyarxiv-cs-ai

Attention Mean Fields Predict Average Representation Dynamics and Reveal Context-Specific Computation

arXiv:2609.16382v1 Announce Type: cross Abstract: A language model's representation geometry is not predetermined; it evolves as the model runs. A faithful account of that geometry must capture that d

Autoformalizing Argumentative Material Inferences

arXiv:2609.16991v1 Announce Type: new Abstract: Natural language arguments are compelling before they are formally explicit. A premise supports a claim through defeasible warrants, background commitme

Automated Distinction of Intimal and Medial Intracranial Arterial Calcification from CT Head

arXiv:2609.16035v1 Announce Type: cross Abstract: Intracranial arterial calcifications (IACs) are a common finding on clinical non-contrast enhanced head CT scans and are associated with neurovascular

Beyond Episodic AI: Cognitive Field Networks for Biologically Inspired Persistent Cognition

arXiv:2609.16752v1 Announce Type: new Abstract: Cognitive Field Theory (CFT) proposes that cognition arises from memory-dressed collective dynamics that generate a persistent macroscopic cognitive fie

Beyond Gestures: Estimating Full Hand Pose and Contact Forces from Wrist-Worn Pressure Sensor Array

arXiv:2609.16518v1 Announce Type: cross Abstract: Capturing hand motion and interaction forces is critical for interactive computing, VR, and high-fidelity tactile demonstrations for robot learning. W

Beyond In-Distribution Metrics: A Systematic Out-of-Distribution Evaluation of Congenital Heart Disease Segmentation

arXiv:2609.17068v1 Announce Type: cross Abstract: Congenital heart disease (CHD) diagnosis and surgical planning often require patient-specific 3D anatomical models, but manual segmentation is labor-i

Bio-Inspired Palette Evolution in Indirectly Encoded Substrates: Timescale Compatibility Shapes Activation Function Discovery

arXiv:2609.17067v1 Announce Type: cross Abstract: Indirectly encoded neural networks can assign different activation functions to individual nodes, but the right functions are rarely known in advance.

Bounded Adjustment with Reliability-Guided Embedding for Imbalanced Learning with Noisy Labels

arXiv:2609.16380v1 Announce Type: new Abstract: Class-balanced learning and label noise create a coupled failure mode: frequency correction prevents majority classes from dominating the decision rule,

Bridging Learned Visual Perception and Symbolic Belief-Space Planning

arXiv:2609.16884v1 Announce Type: new Abstract: In partially observable settings, agents must act without full knowledge of the world state and rely on uncertain state-estimation pipelines. Obtaining

Bridging the Confidence Gap: Temperature Scaling for Calibrating Test-Time Prompt Tuning

arXiv:2609.17386v1 Announce Type: new Abstract: Test-time prompt tuning (TPT) enables adaptation on a single test instance, achieving improved accuracy but often sacrificing calibration performance. M

Bridging the Gap Between Homogeneous and Heterogeneous Asynchronous Optimization Is Surprisingly Difficult

arXiv:2609.17483v1 Announce Type: cross Abstract: Modern large-scale machine learning tasks often require multiple workers, devices, CPUs, or GPUs to compute stochastic gradients in parallel and async

CAD-Based Relation Learning and Geometric-Symbolic Planning for Robotic Assembly

arXiv:2609.17263v1 Announce Type: new Abstract: Assembly Sequence Planning (ASP) remains a challenging problem due to its combinatorial nature, making exhaustive planning approaches impractical for co

Can Deep Learning Achieve Cross-Physics Mapping?

arXiv:2609.16853v1 Announce Type: new Abstract: Can deep learning translate physical fields governed by fundamentally different equations? We address this question by introducing Cross-Physics Mapping

CareMirror: Bringing Caregiver Wellbeing into the Dementia Care Ecosystem

arXiv:2609.17434v1 Announce Type: cross Abstract: Family caregivers of people living with dementia shoulder emotional and practical responsibilities, yet their own wellbeing often remains peripheral t

Cascade: Hierarchical Recoverability Control for Large Language Model Unlearning

arXiv:2609.16890v1 Announce Type: new Abstract: Large Language Model (LLM) unlearning is essential for removing sensitive or copyrighted knowledge while preserving general utility. Existing methods of

Causal Discovery via Transformed Low-Rank Quantile Surfaces

arXiv:2609.16931v1 Announce Type: cross Abstract: We propose Low-Rank Quantile Surfaces (LRQS), a bivariate causal model in which, in the causal direction, an unknown monotone transformation of the co

Causal neural set filtering for online multi-target tracking

arXiv:2609.16054v1 Announce Type: cross Abstract: Transformer-based multi-target tracking (MTT) jointly learns data association and state estimation, but MT3/Track-MT3-style trackers repeatedly re-enc

Challenges of Auditing: Variability in Outputs of Large Language Models for Health

arXiv:2609.16590v1 Announce Type: new Abstract: People increasingly use frontier AI models for health advice, but via different access modes (e.g., ChatGPT, ChatGPT Health, APIs) with varying settings

Channel-Informed Neural Network for Physical Layer Key Generation

arXiv:2609.16341v1 Announce Type: new Abstract: Physical-layer key generation (PKG) enables wireless devices to establish shared keys from reciprocal channel observations without directly exchanging t

Channel-Wise and Token-Aware Post-Training Quantization for Visual State Space Duality

arXiv:2609.16656v1 Announce Type: new Abstract: State space models (SSMs), particularly Mamba, have emerged as efficient alternatives to attention-based architectures and have been extended to vision

CineScale: Tuning-Free High-Resolution Video Generation

arXiv:2508.15774v2 Announce Type: replace Abstract: Visual diffusion models achieve remarkable progress, yet they are typically trained at limited resolutions due to the lack of high-resolution data a

CLASH: Counterfactual Auditing of Lexical and Prosodic Reliance in Spoken Sarcasm Detection

arXiv:2609.16582v1 Announce Type: cross Abstract: Spoken sarcasm detectors may exploit lexical content, prosody, or their interaction, yet conventional evaluation cannot reveal which cues drive their

Closing the Loop: Branch-and-Bound for Scalable Verification of Nonlinear Neural Feedback Systems

arXiv:2609.16298v1 Announce Type: new Abstract: Despite recent advances in the verification of nonlinear neural feedback systems, scalability remains the central obstacle, as state-of-the-art solvers

Collision-Aware Humanoid Whole-Body Control under Imperfect Tracking Targets

arXiv:2609.16405v1 Announce Type: new Abstract: Humanoid robots often execute motion commands through whole-body controllers (WBCs) that track targets while maintaining balance and stability. However,

Comparative Characterization of KV Cache Management Strategies for LLM Inference

arXiv:2604.05012v2 Announce Type: replace-cross Abstract: Efficient inference with Large Language Models (LLMs) increasingly relies on Key-Value (KV) caches to store previously computed key and value

Compute-Optimal Pretrain--Fine-tune in Ridge Gradient Descent

arXiv:2609.16262v1 Announce Type: cross Abstract: Pretraining followed by fine-tuning introduces a compute-allocation problem: under a fixed training budget, compute spent improving the upstream objec

Conditioning noise is a free regularizer for LoRA fine-tuning: no pathology encoder required for diffusion-based artifact detection in histopathology

arXiv:2609.16032v1 Announce Type: cross Abstract: Diffusion-based artifact detectors score whole-slide image patches by reconstruction error under a model fine-tuned on clean tissue. We show that cond