Search: “research”

Asymmetric Classifier-Free Guidance for Target-Speaker ASR

arXiv:2609.30476v1 Announce Type: cross Abstract: Target-speaker automatic speech recognition (TS-ASR) must identify and transcribe a desired speaker under varying overlap and noise conditions. These

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Audit Before You Commit: Locating Belief Failures in Active Identification for One-Shot Manipulation

DGX agent

arXiv:2609.30608v1 Announce Type: new Abstract: A robot that probes a few times before one irreversible action, such as tapping a surface before inserting a peg, must decide when the evidence is enoug

researcharxiv-cs-ro

28 Sept 2026

Auditing System-1 Models on Biosecurity-Relevant Benchmarks: Calibration, Selective Prediction, and Permutation Instability in a Non-Generative Model

arXiv:2609.30454v1 Announce Type: new Abstract: Non-generative 'System-1' models return structured probabilistic decisions in a single forward pass, without autoregressive decoding, at a small fractio

Augmented Reality Interfaces for Human-Robot Collaboration: Development of a ROS 2-Based Sensor Streaming Framework and Validation via SLAM Algorithms

arXiv:2609.31396v1 Announce Type: new Abstract: In recent years, Human-Robot Collaboration (HRC) has taken on a central role in Industry 4.0 and collaborative robotics, demanding communication channel

AUWave: A Data-Driven Model for Reconstructing Significant Wave Heights Using Sparse Observations

arXiv:2509.19384v2 Announce Type: replace-cross Abstract: Reconstructing high-resolution regional significant wave height (SWH) fields from sparse buoy observations is a critical challenge for ocean m

AYLA: Amplifying Gradient Sensitivity via Loss Transformation in Non-Convex Optimization

arXiv:2504.01875v3 Announce Type: replace Abstract: Stochastic Gradient Descent (SGD) and its variants, such as ADAM, are foundational to deep learning optimization, adjusting model parameters through

Bayesian Optimization with Fisher Information Geometry: Gradient Bounds and Trust-Region Methods

arXiv:2609.31107v1 Announce Type: cross Abstract: We study Bayesian optimization (BO) through the lens of information geometry. Pulling back the Fisher information metric through the surrogate posteri

Beyond Bag-of-Words: Diagnosing Compositional Binding Failures in Vision-Language Models

arXiv:2602.02043v2 Announce Type: replace-cross Abstract: Modern vision-language models struggle with basic compositional reasoning, failing to bind attributes to objects or relations to their referen

Beyond Empirical Support: Structured Outlier Generation via Sinkhorn Optimal Transport

arXiv:2609.31470v1 Announce Type: cross Abstract: Outliers are essential for evaluating and improving the robustness of machine learning systems, especially when future distributions may differ signif

Beyond the Last Truffula Tree: SustainAI - A Water-Aware, Closed-Loop Framework for Environmentally Accountable AI

arXiv:2609.30747v1 Announce Type: cross Abstract: As artificial intelligence (AI) becomes embedded in everyday life, its environmental footprint, particularly water consumption remains largely invisib

Block Sparse Attention with Log-Linear Complexity

arXiv:2609.31093v1 Announce Type: new Abstract: Scaling language models to long contexts is limited by the quadratic cost of self-attention. Block sparse attention offers an efficient alternative, but

Breaking Homogeneity: Diversifying Persona Sets for Creative LLM Outputs

arXiv:2609.30492v1 Announce Type: cross Abstract: Language models often produce homogeneous responses to open-ended tasks; such homogeneity can spawn groupthink-the convergence of ideas toward a singu

Brenier Meets Adversarial Training: Optimal Transport Geometry for Robust Learning

arXiv:2609.31363v1 Announce Type: new Abstract: Distributionally robust optimization (DRO) provides a principled framework for learning under distribution shift, but its practical use is hindered by t

CacheReforge: Bounded Recovery for Stale KV Caches under Evolving Adapters

arXiv:2609.30884v1 Announce Type: new Abstract: Large language models rely on KV caching to reduce repeated prefill computation in long context and interactive applications. As lightweight adapters ev

ClearGS: Reliability-Aware Gaussian Splatting from Handheld Videos

arXiv:2609.31509v1 Announce Type: cross Abstract: We present ClearGS for 3D Gaussian Splatting (3DGS) from handheld videos with uneven viewpoint coverage and mixed frame quality. Rather than selecting

Compact Force Sensor for Dual-UAV Cable-Suspended Payload Transport with Tension-Aware Outer-Loop Control

arXiv:2609.31035v1 Announce Type: new Abstract: Cooperative payload transportation using multiple extit{Unmanned Aerial Vehicles} (UAVs) poses challenges in stability, coordination, and robustness, es

Conditional Predictive Sufficient Statistics for Visual Representation Learning

arXiv:2609.30647v1 Announce Type: new Abstract: A useful visual representation is a statistic of the observed past that retains the latent factors shared with the future and discards patch-private noi

Containing Behavioral Cascades from Manipulated Claims in LLM-Powered Multi-Robot Systems

arXiv:2609.30523v1 Announce Type: new Abstract: Large language model (LLM)-powered multi-robot systems are vulnerable to semantic manipulation: an accepted false world-state claim can trigger a fleet-

ContraFM-S2O: Flow Matching-Based One-step SAR-to-Optical Image Translation Model with Contrastive Learning

arXiv:2609.31378v1 Announce Type: new Abstract: In recent years, diffusion models and GAN-based models have become the mainstream approaches for SAR-to-optical image translation, owing to their advant

CoralPlan: Observation Skill Selection and Execution for Underwater Robotic Inspection

arXiv:2609.31211v1 Announce Type: new Abstract: Underwater robotic inspection depends on acquiring views that reveal task-relevant structure. For a structurally complex coral colony, recognising the t

Coupled Usage-Sense Processes: Temporal and Attributable Lexical Semantic Change

arXiv:2609.30974v1 Announce Type: new Abstract: Lexical semantic change is usually summarized by a scalar distance between independently sampled period distributions. This measures how much a word cha

CRNDiff: Count-Native Diffusion Framework via Chemical Reaction Networks

arXiv:2609.31149v1 Announce Type: new Abstract: Scientific measurements such as single-cell RNA (scRNA) sequencing often take the form of nonnegative integer counts, whereas continuous-state diffusion

Decodable In-Context State and Model Output Across Training

arXiv:2609.31401v1 Announce Type: new Abstract: Prior work established that a probe can decode an in-context binding on model errors and that probe-guided steering can repair some of them. We follow p

Deep-Learning Solvers and Surrogates for Infinity and p-Laplace Problems

arXiv:2609.30809v1 Announce Type: cross Abstract: We investigate the use of neural network solvers for infinity and p-Laplace problems, which are fundamental in nonlinear analysis and have practical a

Design and Characterization of a Variable-Length Continuum Mechanism with Force Locking

arXiv:2609.30759v1 Announce Type: new Abstract: The utility of flexible continuum mechanisms for dexterous navigation is often impaired by their low stiffness, making them ineffective at manipulation

DGT-Map: Directional Global Traversability Mapping Utilizing Multi-Task Learning for Heterogeneous Vehicles

arXiv:2609.30461v1 Announce Type: new Abstract: Off-road traversability is direction-dependent and vehicle specific, yet most global maps assign a single isotropic cost to each location. Existing lear

Diagnosing the Sources of Compositional Failure in Vision-Language Models: A Controlled Analysis

arXiv:2609.31456v1 Announce Type: new Abstract: Vision-language models (VLMs) often struggle with compositional reasoning tasks, but the reasons for this underperformance remain unclear. A common hypo

Different Corruptions, Different Signals: Uncertainty and Loss in Federated Data Quality

arXiv:2609.31454v1 Announce Type: cross Abstract: Federated learning (FL) data corruption can affect either inputs or labels, but it remains unclear whether input-conditional uncertainty and predictio

Differentiable RNA Secondary Structure Extraction for Deep Learning

arXiv:2609.30752v1 Announce Type: new Abstract: Many deep learning approaches to RNA secondary structure prediction have recently been proposed. They typically output a weight matrix W where W_{ij} is

Differential Attention Unlocks Complementary EEG and Speech Fusion for Emotion Recognition

arXiv:2609.31399v1 Announce Type: new Abstract: Multimodal emotion recognition (MER) increasingly pairs EEG with speech, treating internal neural signals and external vocal expression as informative v

Differentially-Private Decision Trees and Provable Robustness to Data Poisoning

arXiv:2305.15394v3 Announce Type: replace Abstract: Decision trees are interpretable models that are well-suited to non-linear learning problems. Much work has been done on extending decision tree lea

DiffusionShadow: Diffusion-based Shadow Caching for Neural Volume Rendering

arXiv:2609.30658v1 Announce Type: cross Abstract: Implicit neural representations (INRs) have gained momentum in scientific visualization due to their compactness and scalability to large datasets, ma

Distribution-Conditioned Transport

arXiv:2603.04736v2 Announce Type: replace Abstract: Learning a transport model that maps a source distribution to a target distribution is a canonical problem in machine learning, but scientific appli

Distribution of hitting times for dissipative random dynamical systems on R^d, with application to stochastic gradient descent

arXiv:2609.30274v1 Announce Type: cross Abstract: Machine Learning and more specifically Deep Learning involves solving large scale nonconvex optimization problems. Several algorithms have been propos

Do LLMs Understand Context? A Knowledge Graph-Based Evaluation Framework

arXiv:2609.30484v1 Announce Type: new Abstract: While large language models (LLMs) have achieved remarkable linguistic capabilities, a profound question lingers at their core: do these models truly co

Does Understanding Inform Generation in Unified Multimodal Models? From Analysis to Path Forward

arXiv:2511.20561v3 Announce Type: replace-cross Abstract: Recent years have witnessed significant progress in Unified Multimodal Models, yet a fundamental question remains: Does understanding truly in

Does Uniform Discrete Diffusion Need Time?

arXiv:2609.30977v1 Announce Type: cross Abstract: Uniform discrete diffusion models (UDMs) commonly use explicit time conditioning, but we find that it can often be unnecessary in practice. In this pa

Don't CLAP: Are Music-Text Models Bag-of-Words?

arXiv:2609.30540v1 Announce Type: cross Abstract: Text-to-music systems are assessed on audio quality and on how faithfully the music follows its prompt, and the CLAP score, the cosine similarity betw

Double-stream registration with pyramid fusion for HDR video with alternating exposures

arXiv:2609.31108v1 Announce Type: new Abstract: High dynamic range (HDR) video reconstruction from al-ter-na-ting-exposure sequences remains challenging, especially in regions with extreme luminance v

dRVG: Quadtree-Guided, Resolution-Complete Online Motion Planning for Polygonal Robots in Unknown Environments

arXiv:2609.31412v1 Announce Type: new Abstract: We present the dynamic rotation-stacked visibility graph (dRVG), an online motion planner that guides polygonal robots to specified goals in initially u

Dynamic Regret in Online Convex Optimization with Indicator Switching Costs

arXiv:2609.30556v1 Announce Type: new Abstract: We study dynamic regret in online convex optimization with an indicator switching cost: a fixed penalty incurred whenever two consecutive decisions diff

Effects of Transcript Compression on LLM-based Medical Misinformation Detection in Japanese YouTube Videos

arXiv:2609.30882v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to assess long-form medical videos, but their effectiveness may depend on whether transcripts are pro

Efficient Constrained Graph Search for Post-hoc Error Correction in Binary Classifiers

arXiv:2401.04282v2 Announce Type: replace Abstract: We introduce a model-agnostic framework for constrained post-hoc error correction in binary classifiers. Given a frozen base classifier, the method

Encryptability As a Coordinate Choice: Depth-One Homomorphic Federated Learning of Quantum Neural Networks

arXiv:2609.30581v1 Announce Type: cross Abstract: Encrypted training relies on keeping server-side updates low-degree. This constraint traditionally excludes models whose weights inhabit a compact Lie

Energy-efficient operation of neural operators for virtual sensing

arXiv:2609.30580v1 Announce Type: new Abstract: Virtual sensing repeatedly reconstructs physical fields from changing observations, often on a fixed geometry. We investigate how shared spatial computa

Enhancing Assessment of Self-Consistency in LLM Explanations using Perturbation Strength

arXiv:2609.30849v1 Announce Type: new Abstract: Prior work has examined the self-consistency of LLM-generated explanations using surface-level perturbation methods. However, the strength of these pert

Enhancing Photogrammetric Digital Surface Models with Pretrained Diffusion Models and Multimodal Conditioning

arXiv:2609.31199v1 Announce Type: cross Abstract: Large-scale Digital Surface Models (DSMs) can be produced cost-effectively from satellite images via stereo-photogrammetry. However, the resulting 3D

EPOC: Endpoint-Preserving Online Correction With Compressed Residual State for Multi-Horizon Time Series Forecasting

arXiv:2609.30929v1 Announce Type: new Abstract: Completed multi-horizon forecasts provide residual feedback for a fixed forecaster, but retaining full residual blocks increases auxiliary state. We pro