Search: “applications”

PhysHanDI: Physics-Based Reconstruction of Hand-Deformable Object Interactions

arXiv:2605.09538v1 Announce Type: cross Abstract: While existing methods for reconstructing hand-object interactions have made impressive progress, they either focus on rigid or part-wise rigid object

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Applications

PixelFlowCast: Latent-Free Precipitation Nowcasting via Pixel Mean Flows

DGX agent

arXiv:2605.10046v1 Announce Type: new Abstract: Precipitation nowcasting aims to forecast short-term radar echo sequences for extreme weather warning, where both prediction fidelity and inference effi

applicationsarxiv-cs-cv

12 May 2026

Position: Avoid Overstretching LLMs for every Enterprise Task

arXiv:2605.09365v1 Announce Type: new Abstract: Enterprise workloads are dominated by deterministic, structured, and knowledge-dependent tasks operating under strict cost, latency, and reliability con

Prospective Compression in Human Abstraction Learning

arXiv:2605.09985v1 Announce Type: new Abstract: A core challenge in program synthesis is online library learning: the incremental acquisition of reusable abstractions under uncertainty about future ta

Rethinking Evaluation of Multiple Sclerosis (MS) Lesion Segmentation Models

arXiv:2605.09666v1 Announce Type: cross Abstract: Multiple Sclerosis (MS) is a chronic autoimmune disease that can significantly reduce the quality of life of a patient. Existing treatment options can

RIR-Former: Coordinate-Guided Transformer for Continuous Reconstruction of Room Impulse Responses

arXiv:2602.01861v3 Announce Type: replace-cross Abstract: Room impulse responses (RIRs) are essential for many acoustic signal processing tasks, yet measuring them densely across space is often imprac

Root Cause Analysis of Measurement and Mechanistic Anomalies

arXiv:2601.23026v2 Announce Type: replace Abstract: Root cause analysis of anomalies aims to identify how and why a sample deviates from the normal process. Existing methods primarily focus on telling

RubiConv -- Efficient Boundary-Respecting Convolutions

arXiv:2605.08451v1 Announce Type: new Abstract: Convolutional architectures have emerged as powerful alternatives to Transformers for sequence modeling. The primary advantage is that they offer improv

SABER: A Scalable Action-Based Embodied Dataset for Real-World VLA Adaptation

arXiv:2605.09613v1 Announce Type: cross Abstract: Robotic deployment in real-world environments depends on rich, domain-specific action data as much as on strong model architecture. General-purpose ro

Scalable and Efficient Continual Learning from Demonstration via a Hypernetwork-generated Stable Dynamics Model

arXiv:2311.03600v3 Announce Type: replace Abstract: Robots capable of learning from demonstration (LfD) must exhibit stability while executing learned motion skills. To be effective in the real world,

applicationsarxiv-cs-ro

Shapley Regression for Rare Disease Diagnosis Support: a case study on APDS

arXiv:2605.08897v1 Announce Type: cross Abstract: Activated PI3K8 Syndrome (APDS) is a rare genetic immune disorder caused by variants in PIK3CD or PIK3R1, with highly heterogeneous symptoms that ofte

Simultaneous Monitoring of Shape and Surface Color via 4D Point Clouds: A Registration-free Approach

arXiv:2605.08753v1 Announce Type: new Abstract: Advanced manufacturing technologies allow for the production of intricate parts featuring high shape complexity and spatially-varying material compositi

SocialDirector: Training-Free Social Interaction Control for Multi-Person Video Generation

arXiv:2605.10079v1 Announce Type: new Abstract: Video generation has advanced rapidly, producing photorealistic videos from text or image prompts. Meanwhile, film production and social robotics increa

SPECTRE: Hybrid Ordinary-Parallel Speculative Serving for Resource-Efficient LLM Inference

arXiv:2605.08151v1 Announce Type: cross Abstract: LLM serving platforms are increasingly deployed as multi-model cloud systems, where user demand is often long-tailed: a few popular large models recei

Sundial: A Family of Highly Capable Time Series Foundation Models

arXiv:2502.00816v4 Announce Type: replace Abstract: We introduce Sundial, a family of native, flexible, and scalable time series foundation models. To predict the next-patch's distribution, we propose

Temporal Tokenization Strategies for Event Sequence Modeling with Large Language Models

arXiv:2512.13618v3 Announce Type: replace Abstract: Representing continuous time is a critical and under-explored challenge in modeling temporal event sequences with large language models (LLMs). Vari

Safety

The Geometric Structure of Models Learning Sparse Data

arXiv:2605.08464v1 Announce Type: new Abstract: The manifold hypothesis (MH) is often used to explain how machine learning can overcome the curse of dimensionality. However, the MH is only applicable

safetyarxiv-cs-lg

Research

Threat Modelling using Domain-Adapted Language Models: Empirical Evaluation and Insights

arXiv:2605.10808v1 Announce Type: cross Abstract: Large Language Models(LLMs) are increasingly explored for cybersecurity applications such as vulnerability detection. In the domain of threat modellin

researcharxiv-cs-ai

Toward General and Robust LLM-enhanced Text-attributed Graph Learning

arXiv:2504.02343v2 Announce Type: replace Abstract: Recent advancements in Large Language Models (LLMs) and the proliferation of Text-Attributed Graphs (TAGs) across various domains have positioned LL

Towards Robust Sequential Decomposition for Complex Image Editing

arXiv:2605.09233v1 Announce Type: cross Abstract: Recent advances in visual generative models have enabled high-fidelity image editing guided by human instructions. However, these models often struggl

TransmissiveGS: Residual-Guided Disentangled Gaussian Splatting for Transmissive Scene Reconstruction and Rendering

arXiv:2605.10705v1 Announce Type: new Abstract: Transmissive scenes are ubiquitous in daily life, yet reconstructing and rendering them remains highly challenging due to the inherent entanglement betw

TSNN: A Non-parametric and Interpretable Framework for Traffic Time Series Forecasting

arXiv:2605.09208v1 Announce Type: new Abstract: Although many complex models were proposed to analyze time series data, some studies have demonstrated remarkable performance with simpler structures. A

Unlocking air traffic flow prediction through microscopic aircraft-state modeling

arXiv:2605.10083v1 Announce Type: new Abstract: Short-term air traffic flow prediction in terminal airspace is essential for proactive air traffic management. Existing approaches predominantly model t

VAE with Hyperspherical Coordinates: Improving Anomaly Detection from Hypervolume-Compressed Latent Space

arXiv:2601.18823v3 Announce Type: replace Abstract: Variational autoencoders (VAE) encode data into lower-dimensional latent vectors before decoding those vectors back to data. Once trained, one can h

Weakly Supervised Concept Learning for Object-centric Visual Reasoning

arXiv:2605.08201v1 Announce Type: cross Abstract: Neurosymbolic systems promise to combine deep neural network's (DNN) processing of raw sensor inputs with few-shot performance of symbolic artificial

What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies

arXiv:2605.08289v1 Announce Type: cross Abstract: Multivariate time series forecasting is critical in many real-world systems, and thus modeling cross-channel dependencies is essential. Although exist

What Time Is It? How Data Geometry Makes Time Conditioning Optional for Flow Matching

arXiv:2605.08344v1 Announce Type: new Abstract: Recent work has shown that models flow matching models can be trained without explicit time conditioning, challenging the standard view that the interpo

Yield Curve Forecasting using Machine Learning and Econometrics: A Comparative Analysis

arXiv:2605.09842v1 Announce Type: new Abstract: While machine learning has revolutionized many fields such as natural language processing (NLP) and computer vision, its impact on time-series forecasti

Accelerated Relax-and-Round for Concave Coverage Problems

arXiv:2605.06900v1 Announce Type: cross Abstract: We present an accelerated relax-and-round algorithm for concave coverage problems, which generalize the classic maximum coverage problem. Building on

Approximation Error Upper and Lower Bounds for Holder Class with Transformers

arXiv:2605.07463v1 Announce Type: new Abstract: We explore the expressive power of Transformers by establishing precise approximation error upper and lower bounds for Holder class. Specifically, a new

AT-VLA: Adaptive Tactile Injection for Enhanced Feedback Reaction in Vision-Language-Action Models

arXiv:2605.07308v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have significantly advanced the capabilities of robotic agents in executing diverse tasks; however, they still face

applicationsarxiv-cs-ro

AudioFace: Language-Assisted Speech-Driven Facial Animation with Multimodal Language Models

arXiv:2605.07478v1 Announce Type: new Abstract: Speech-driven facial animation requires accurate correspondence between acoustic signals and facial motion, especially for articulation-related mouth mo

BeeVe: Unsupervised Acoustic State Discovery in Honey Bee Buzzing

arXiv:2605.07903v1 Announce Type: cross Abstract: Discovering structure in biological signals without supervision is a fundamental problem in computational intelligence, yet existing bioacoustic metho

Beyond Single Ground Truth: Reference Monism as Epistemic Injustice in ASR Evaluation

arXiv:2605.07084v1 Announce Type: new Abstract: Automatic speech recognition (ASR) evaluation compares system output to ground truth transcripts, with Word Error Rate (WER) quantifying the distance be

Can LLMs Take Retrieved Information with a Grain of Salt?

arXiv:2605.06919v1 Announce Type: new Abstract: Large language models have demonstrated impressive retrieval-augmented capabilities. However, a crucial area remains underexplored: their ability to app

Chordless cycle filtrations for dimensionality detection in complex networks via topological data analysis

arXiv:2509.08350v2 Announce Type: replace-cross Abstract: Many complex networks, ranging from social to biological systems, exhibit structural patterns consistent with an underlying hyperbolic geometr

Diffusion Path Samplers via Sequential Monte Carlo

arXiv:2601.21951v2 Announce Type: replace-cross Abstract: We develop diffusion-based samplers for target distributions known up to a normalising constant. To this end, we rely on the well-known diffus

Direct Reasoning Optimization: Token-Level Reasoning Reflectivity Meets Rubric Gates for Unverifiable Tasks

arXiv:2506.13351v3 Announce Type: replace-cross Abstract: Reinforcement learning (RL) training of large language models (LLMs) on unverifiable tasks is challenging even when a reasonable-quality refer

Discovering Learning-Friendly Generation Orders for Sequential Computation

arXiv:2506.23875v4 Announce Type: replace-cross Abstract: Sequential computation via autoregressive generation can make difficult tasks learnable, but the generation order of intermediate states stron

DynaRetarget: Dynamically-Feasible Retargeting using Sampling-Based Trajectory Optimization

arXiv:2602.06827v2 Announce Type: replace Abstract: In this paper, we introduce DynaRetarget, a complete pipeline for retargeting human motions to humanoid control policies. The core component of Dyna

applicationsarxiv-cs-ro

Emergence of Distortions in High-Dimensional Guided Diffusion Models

arXiv:2602.00716v4 Announce Type: replace-cross Abstract: Classifier-free guidance (CFG) is the de facto standard for conditional sampling in diffusion models, yet it often reduces sample diversity. U

Exploring CoCo Challenges in ML Engineering Teams: Insights From the Semiconductor Industry

arXiv:2605.07389v1 Announce Type: cross Abstract: The integration of machine learning (ML) into complex software systems has increased challenges in collaboration and communication (CoCo) of the teams

Fast and Effective Redistricting Optimization via Composite-Move Tabu Search

arXiv:2605.06682v1 Announce Type: new Abstract: Spatial redistricting is a practical combinatorial optimization problem that demands high-quality solutions, rapid turnaround, and flexibility to accomm

From Feasible to Practical: Pareto-Optimal Synthesis Planning

arXiv:2605.07521v1 Announce Type: new Abstract: Current computer-aided synthesis planning (CASP) methods often treat retrosynthesis as solved once a single feasible route is identified, focusing prima

From Surface Learning to Deep Understanding: A Grounded AI Tutoring System for Moodle

arXiv:2605.06963v1 Announce Type: cross Abstract: This demo paper describes the development of the AI Teaching & Learning Assistant, a modular Moodle plugin that leverages Retrieval-Augmented Generati

Hardware

GATO: GPU-Accelerated and Batched Trajectory Optimization for Scalable Edge Model Predictive Control

arXiv:2510.07625v2 Announce Type: replace Abstract: While Model Predictive Control (MPC) delivers strong performance across robotics applications, solving the underlying (batches of) nonlinear traject

hardwarearxiv-cs-ro

Geometric Analysis of Neural Regression Collapse via Intrinsic Dimension

arXiv:2510.01105v2 Announce Type: replace Abstract: Neural multivariate regression underpins a wide range of domains, including control, robotics, and finance, yet the geometry of its learned represen

Hybrid TF--IDF Logistic Regression and MLP Neural Baseline for Indonesian Three-Class Sentiment Analysis on Social Media Text

arXiv:2605.07793v1 Announce Type: new Abstract: This paper presents a compact three-class sentiment analysis study for Indonesian social media text. The task is formulated with positive, negative, and