Search: “models”

FLARE-BO: Fused Luminance and Adaptive Retinex Enhancement via Bayesian Optimisation for Low-Light Robotic Vision

arXiv:2604.22093v1 Announce Type: new Abstract: Reliable visual perception under low illumination remains a core challenge for autonomous robotic systems, where degraded image quality directly comprom

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Research

FMSD-TTS: Few-shot Multi-Speaker Multi-Dialect Text-to-Speech Synthesis for U-Tsang, Amdo and Kham Speech Dataset Generation

DGX agent

arXiv:2505.14351v4 Announce Type: replace-cross Abstract: Tibetan is a low-resource language with minimal parallel speech corpora spanning its three major dialects-U-Tsang, Amdo, and Kham-limiting pro

researcharxiv-cs-ai

27 Apr 2026

HFX: Joint Design of Algorithms and Systems for Multi-SLO Serving and Fast Scaling

arXiv:2508.15919v3 Announce Type: replace-cross Abstract: Large language model (LLM) serving faces the dual challenge of meeting strict user-specific service-level objectives (SLOs) while minimizing c

applicationsarxiv-cs-ai

Hidden Failure Modes of Gradient Modification under Adam in Continual Learning, and Adaptive Decoupled Moment Routing as a Repair

arXiv:2604.22407v1 Announce Type: cross Abstract: Many continual-learning methods modify gradients upstream (e.g., projection, penalty rescaling, replay mixing) while treating Adam as a neutral backen

Hardware

Incentivizing Neuro-symbolic Language-based Reasoning in VLMs via Reinforcement Learning

arXiv:2604.22062v1 Announce Type: new Abstract: There are 7,407 languages in the world. But, what about the languages that are not there in the world? Are humans so narrow minded that we don't care ab

hardwarearxiv-cs-cl

LLM+Graph@VLDB'2025 Workshop Summary

arXiv:2604.02861v2 Announce Type: replace-cross Abstract: The integration of large language models (LLMs) with graph-structured data has become a pivotal and fast evolving research frontier, drawing s

LTBs-KAN: Linear-Time B-splines Kolmogorov-Arnold Networks

arXiv:2604.22034v1 Announce Type: cross Abstract: Kolmogorov-Arnold Networks (KANs) are a recent neural network architecture offering an alternative to Multilayer Perceptrons (MLPs) with improved expl

MacrOData: New Benchmarks of Thousands of Datasets for Tabular Outlier Detection

arXiv:2602.09329v2 Announce Type: replace Abstract: Quality benchmarks are essential for fairly and accurately tracking scientific progress and enabling practitioners to make informed methodological c

Hardware

Motivating Next-Gen Accelerators with Flexible (N:M) Activation Sparsity via Benchmarking Lightweight Post-Training Sparsification Approaches

arXiv:2509.22166v4 Announce Type: replace-cross Abstract: The demand for efficient large language model (LLM) inference has intensified the focus on sparsification techniques. While semi-structured (N

hardwarearxiv-cs-ai

Multi-Task Optimization over Networks of Tasks

arXiv:2604.21991v1 Announce Type: cross Abstract: Multi-task optimization is a powerful approach for solving a large number of tasks in parallel. However, existing algorithms face distinct limitations

OmniOVCD: Streamlining Open-Vocabulary Change Detection with SAM 3

arXiv:2601.13895v2 Announce Type: replace-cross Abstract: Change Detection (CD) is a fundamental task in remote sensing. It monitors the evolution of land cover over time. Based on this, Open-Vocabula

Representational Harms in LLM-Generated Narratives Against Global Majority Nationalities

arXiv:2604.22749v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for text generation tasks from everyday use to high-stakes enterprise and government applications, in

applicationsarxiv-cs-cl

Local Ai

Robust Fuzzy local k-plane clustering with mixture distance of hinge loss and L1 norm

arXiv:2604.22405v1 Announce Type: new Abstract: K-plane clustering (KPC), hyperplane clustering, and mixture regression all essentially fall within the same class of problems. This problem can be conc

local-aiarxiv-cs-lg

Selective Depthwise Separable Convolution for Lightweight Joint Source-Channel Coding in Wireless Image Transmission

arXiv:2604.22338v1 Announce Type: cross Abstract: Depthwise separable convolutional (DSConv) layers have been successfully applied to deep learning (DL)-based joint source-channel coding (JSCC) scheme

TRACE: Topology-aware Reconstruction of Accidents in CARLA for AV Evaluation

model-releasesarxiv-cs-ro

arXiv:2604.22068v1 Announce Type: cross Abstract: Validating Autonomous Vehicles (AVs) requires exposure to rare, safety-critical scenarios, infrequent in routine driving data. Existing benchmarks add

Universal Transformers Need Memory: Depth-State Trade-offs in Adaptive Recursive Reasoning

arXiv:2604.21999v1 Announce Type: cross Abstract: We study learned memory tokens as computational scratchpad for a single-block Universal Transformer (UT) with Adaptive Computation Time (ACT) on Sudok

Unlocking Optical Prior: Spectrum-Guided Knowledge Transfer for SAR Generalized Category Discovery

arXiv:2604.22174v1 Announce Type: new Abstract: Generalized Category Discovery (GCD) holds significant promise for the label-scarce Synthetic Aperture Radar (SAR) domain, yet its efficacy is severely

safetyarxiv-cs-cv

When Cow Urine Cures Constipation on YouTube: Limits of LLMs in Detecting Culture-specific Health Misinformation

model-releasesarxiv-cs-cl

arXiv:2604.22002v1 Announce Type: new Abstract: Social media platforms have become primary channels for health information in the Global South. Using gomutra (cow urine) discourse on YouTube in India

A Compact Peristaltic Pump Based on Magneto-Elastic Hysteresis with Single Pneumatic Control

arXiv:2604.21729v1 Announce Type: new Abstract: Pumping fluids is fundamental to a wide range of industrial, environmental, and biomedical applications. Among various pumping mechanisms, peristaltic p

researcharxiv-cs-ro

Tutorials

A Comprehensive Guide to Differential Privacy: From Theory to User Expectations

arXiv:2509.03294v3 Announce Type: replace-cross Abstract: The increasing availability of personal data has enabled significant advances in fields such as machine learning, healthcare, and cybersecurit

tutorialsarxiv-cs-ai

Adaptive Soft Error Protection for Neural Network Processing

arXiv:2407.19664v3 Announce Type: replace Abstract: Previous research on selective protection for neural network components typically exploits only static vulnerability differences. Although these met

researcharxiv-cs-lg

Adaptive Test-Time Compute Allocation with Evolving In-Context Demonstrations

arXiv:2604.21018v1 Announce Type: new Abstract: While scaling test-time compute can substantially improve model performance, existing approaches either rely on static compute allocation or sample from

Back to the Future: The Role of Past and Future Context Predictability in Incremental Language Production

arXiv:2511.07752v3 Announce Type: replace Abstract: Contextual predictability shapes how we choose and encode words in production. The effects of a word's predictability given preceding or past contex

applicationsarxiv-cs-cl

Beyond Single Plots: A Benchmark for Question Answering on Multi-Charts

arXiv:2604.21344v1 Announce Type: cross Abstract: Charts are widely used to present complex information. Deriving meaningful insights in real-world contexts often requires interpreting multiple relate

C-SHAP for time series: An approach to high-level temporal explanations

arXiv:2504.11159v2 Announce Type: replace Abstract: In high-stakes domains, such as healthcare and industry, the explainability of AI-based decision-making has become crucial. Without insight into mod

applicationsarxiv-cs-ai

Clinical Reasoning AI for Oncology Treatment Planning: A Multi-Specialty Case-Based Evaluation

arXiv:2604.20869v1 Announce Type: cross Abstract: Background: More than 80% of U.S. cancer care is delivered in community settings, where survival remains worse than at academic centers. Clinicians mu

Compliance Moral Hazard and the Backfiring Mandate

arXiv:2604.21789v1 Announce Type: cross Abstract: Competing firms that serve shared customer populations face a fundamental information aggregation problem: each firm holds fragmented signals about ri

Dementia classification from spontaneous speech using wrapper-based feature selection

arXiv:2502.03484v2 Announce Type: replace-cross Abstract: Dementia encompasses a group of syndromes that impair cognitive functions such as memory, reasoning, and the ability to perform daily activiti

researcharxiv-cs-lg

Droplet-LNO: Physics-Informed Laplace Neural Operators for Accurate Prediction of Droplet Spreading Dynamics on Complex Surfaces

arXiv:2604.20993v1 Announce Type: new Abstract: Spreading of liquid droplets on solid substrates constitutes a classic multiphysics problem with widespread applications ranging from inkjet printing, s

Agents

Efficient Agent Evaluation via Diversity-Guided User Simulation

arXiv:2604.21480v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as customer-facing agents, yet evaluating their reliability remains challenging due to stochastic

agentsarxiv-cs-ai

FairQE: Multi-Agent Framework for Mitigating Gender Bias in Translation Quality Estimation

arXiv:2604.21420v1 Announce Type: new Abstract: Quality Estimation (QE) aims to assess machine translation quality without reference translations, but recent studies have shown that existing QE models

GeCo: Evaluating Geometric Consistency for Video Generation via Motion and Structure

arXiv:2512.22274v2 Announce Type: replace Abstract: We introduce GeCo, a geometry-grounded metric for jointly detecting geometric deformation and occlusion-inconsistency artifacts in static scenes. By

GeoMind: An Agentic Workflow for Lithology Classification with Reasoned Tool Invocation

arXiv:2604.21501v1 Announce Type: new Abstract: Lithology classification in well logs is a fundamental geoscience data mining task that aims to infer rock types from multi dimensional geophysical sequ

ID-Eraser: Proactive Defense Against Face Swapping via Identity Perturbation

arXiv:2604.21465v1 Announce Type: new Abstract: Deepfake technologies have rapidly advanced with modern generative AI, and face swapping in particular poses serious threats to privacy and digital secu

researcharxiv-cs-cv

Materialistic RIR: Material Conditioned Realistic RIR Generation

arXiv:2604.21119v1 Announce Type: cross Abstract: Rings like gold, thuds like wood! The sound we hear in a scene is shaped not only by the spatial layout of the environment but also by the materials o

Local Ai

Mind the Gap: Optimal and Equitable Encouragement Policies

arXiv:2309.07176v5 Announce Type: replace Abstract: In consequential domains, it is often impossible to compel individuals to take treatment, so that optimal policy rules are merely suggestions in the

local-aiarxiv-cs-lg

MISTY: High-Throughput Motion Planning via Mixer-based Single-step Drifting

arXiv:2604.21489v1 Announce Type: cross Abstract: Multi-modal trajectory generation is essential for safe autonomous driving, yet existing diffusion-based planners suffer from high inference latency d

Mitigating Lost in Multi-turn Conversation via Curriculum RL with Verifiable Accuracy and Abstention Rewards

arXiv:2510.18731v2 Announce Type: replace-cross Abstract: Large Language Models demonstrate strong capabilities in single-turn instruction following but suffer from Lost-in-Conversation (LiC), a degra

Principled Evaluation with Human Labels: One Rater at a Time and Rater Equivalence

arXiv:2106.01254v3 Announce Type: replace Abstract: In many classification tasks, there is no definitive ground truth, only human judgments that may disagree. We address two challenges that arise in s

Probably Approximately Consensus: On the Learning Theory of Finding Common Ground

arXiv:2604.21811v1 Announce Type: cross Abstract: A primary goal of online deliberation platforms is to identify ideas that are broadly agreeable to a community of users through their expressed prefer

Rectified Schrodinger Bridge Matching for Few-Step Visual Navigation

arXiv:2604.05673v2 Announce Type: replace-cross Abstract: Visual navigation is a core challenge in Embodied AI, requiring autonomous agents to translate high-dimensional sensory observations into cont

Reinforcement Learning with Foundation Priors: Let the Embodied Agent Efficiently Learn on Its Own

arXiv:2310.02635v5 Announce Type: replace-cross Abstract: Reinforcement learning (RL) is a promising approach for solving robotic manipulation tasks. However, it is challenging to apply the RL algorit

Retrofit: Continual Learning with Controlled Forgetting for Binary Security Detection and Analysis

arXiv:2511.11439v2 Announce Type: replace-cross Abstract: Binary security has increasingly relied on deep learning to reason about malware behavior and program semantics. However, the performance ofte

SafeRedirect: Defeating Internal Safety Collapse via Task-Completion Redirection in Frontier LLMs

arXiv:2604.20930v1 Announce Type: cross Abstract: Internal Safety Collapse (ISC) is a failure mode in which frontier LLMs, when executing legitimate professional tasks whose correct completion structu

Sculpt4D: Generating 4D Shapes via Sparse-Attention Diffusion Transformers

arXiv:2604.21592v1 Announce Type: new Abstract: Recent breakthroughs in 3D generative modeling have yielded remarkable progress in static shape synthesis, yet high-fidelity dynamic 4D generation remai

researcharxiv-cs-cv

SDNGuardStack: An Explainable Ensemble Learning Framework for High-Accuracy Intrusion Detection in Software-Defined Networks

arXiv:2604.20934v1 Announce Type: cross Abstract: Software-Defined Networking (SDN) is another technology that has been developing in the last few years as a relevant technique to improve network prog

researcharxiv-cs-lg

Self-Predictive Representation for Autonomous UAV Object-Goal Navigation

arXiv:2604.21130v1 Announce Type: new Abstract: Autonomous Unmanned Aerial Vehicles (UAVs) have revolutionized industries through their versatility with applications including aerial surveillance, sea

safetyarxiv-cs-ro

Spectral Embeddings Leak Graph Topology: Theory, Benchmark, and Adaptive Reconstruction

arXiv:2604.21094v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) excel on relational data, but standard benchmarks unrealistically assume the graph is centrally available. In practice, set