Search: “models”

Bias-constrained multimodal intelligence for equitable and reliable clinical AI

arXiv:2604.16884v1 Announce Type: new Abstract: The integration of medical imaging and clinical text has enabled the emergence of generalist artificial intelligence (AI) systems for healthcare. Howeve

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Bit-Flip Vulnerability of Shared KV-Cache Blocks in LLM Serving Systems

DGX agent

arXiv:2604.17249v1 Announce Type: cross Abstract: Rowhammer on GPU DRAM has enabled adversarial bit flips in model weights; shared KV-cache blocks in LLM serving systems present an analogous but previ

hardwarearxiv-cs-lg

21 Apr 2026

Bridging the Culture Gap: A Framework for LLM-Driven Socio-Cultural Localization of Math Word Problems in Low-Resource Languages

arXiv:2508.14913v4 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated significant capabilities in solving mathematical problems expressed in natural language. However, mul

local-aiarxiv-cs-cl

Causally-Constrained Probabilistic Forecasting for Time-Series Anomaly Detection

arXiv:2604.17998v1 Announce Type: new Abstract: Anomaly detection in multivariate time series is a central challenge in industrial monitoring, as failures frequently arise from complex temporal dynami

local-aiarxiv-cs-lg

CHIMERA: A Knowledge Base of Scientific Idea Recombinations for Research Analysis and Ideation

arXiv:2505.20779v5 Announce Type: replace Abstract: A hallmark of human innovation is recombination -- the creation of novel ideas by integrating elements from existing concepts and mechanisms. In thi

researcharxiv-cs-cl

CoGR-MoE: Concept-Guided Expert Routing with Consistent Selection and Flexible Reasoning for Visual Question Answering

arXiv:2604.16930v1 Announce Type: new Abstract: Visual Question Answering (VQA) requires models to identify the correct answer options based on both visual and textual evidence. Recent Mixture-of-Expe

tutorialsarxiv-cs-cv

Applications

Conditional Evidence Reconstruction and Decomposition for Interpretable Multimodal Diagnosis

arXiv:2604.17030v1 Announce Type: new Abstract: Neurobiological and neurodegenerative diseases are inherently multifactorial, arising from coupled influences spanning genetic susceptibility, brain alt

applicationsarxiv-cs-cv

Convergence theory for Hermite approximations under adaptive coordinate transformations

arXiv:2604.16975v1 Announce Type: cross Abstract: Recent work has shown that parameterizing and optimizing coordinate transformations using normalizing flows, i.e., invertible neural networks, can sig

COSEARCH: Joint Training of Reasoning and Document Ranking via Reinforcement Learning for Agentic Search

arXiv:2604.17555v1 Announce Type: cross Abstract: Agentic search -- the task of training agents that iteratively reason, issue queries, and synthesize retrieved information to answer complex questions

safetyarxiv-cs-cl

DARLING: Detection Augmented Reinforcement Learning with Non-Stationary Guarantees

arXiv:2604.16684v1 Announce Type: new Abstract: We study model-free reinforcement learning (RL) in non-stationary finite-horizon episodic Markov decision processes (MDPs) without prior knowledge of th

DeepDetect: Learning All-in-One Dense Keypoints

arXiv:2510.17422v4 Announce Type: replace Abstract: Keypoint detection is the foundation of many computer vision tasks, including image registration, structure-from-motion, 3D reconstruction, visual o

Designing Explainable Conversational Agentic Systems for Guarani Speakers

arXiv:2603.05743v3 Announce Type: replace Abstract: Although artificial intelligence (AI) and Human-Computer Interaction (HCI) systems are often presented as universal solutions, their design remains

agentsarxiv-cs-cl

DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty

arXiv:2506.12622v2 Announce Type: replace Abstract: Deep reinforcement learning (RL) has achieved remarkable success, yet its deployment in real-world scenarios is often limited by vulnerability to en

safetyarxiv-cs-lg

EEG-Based Emergency Braking Intensity Prediction Using Blind Source Separation

arXiv:2604.18220v1 Announce Type: cross Abstract: Electroencephalography (EEG) signals have been promising for long-term braking intensity prediction but are prone to various artifacts that limit thei

Ego-InBetween: Generating Object State Transitions in Ego-Centric Videos

arXiv:2604.17749v1 Announce Type: new Abstract: Understanding physical transformation processes is crucial for both human cognition and artificial intelligence systems, particularly from an egocentric

Eluder dimension: localise it!

arXiv:2601.09825v2 Announce Type: replace Abstract: We establish a lower bound on the eluder dimension of generalised linear model classes, showing that standard eluder dimension-based analysis cannot

Emergency Stopping for Liquid-manipulating Robots

arXiv:2604.16667v1 Announce Type: new Abstract: Manipulating open liquid containers is challenging because liquids are highly sensitive to vessel accelerations and jerks. Although spill-free liquid ma

safetyarxiv-cs-ro

EmoVerse: A MLLMs-Driven Emotion Representation Dataset for Interpretable Visual Emotion Analysis

arXiv:2511.12554v2 Announce Type: replace Abstract: Visual Emotion Analysis (VEA) aims to bridge the affective gap between visual content and human emotional responses. Despite its promise, progress i

End-to-End Optimization of LLM-Driven Multi-Agent Search Systems via Heterogeneous-Group-Based Reinforcement Learning

arXiv:2506.02718v2 Announce Type: replace Abstract: Large language models (LLMs) are versatile, yet their deployment in complex real-world settings is limited by static knowledge cutoffs and the diffi

safetyarxiv-cs-lg

Evidence-Augmented Policy Optimization with Reward Co-Evolution for Long-Context Reasoning

arXiv:2601.10306v2 Announce Type: replace-cross Abstract: While Reinforcement Learning (RL) has advanced LLM reasoning, applying it to long-context scenarios is hindered by sparsity of outcome rewards

safetyarxiv-cs-cl

Expressive yet Efficient Feature Expansion with Adaptive Cross-Hadamard Products

arXiv:2505.22226v2 Announce Type: replace Abstract: Recent theoretical advances reveal that the Hadamard product induces nonlinear representations and implicit high-dimensional mappings for the field

FairNVT: Improving Fairness via Noise Injection in Vision Transformers

arXiv:2604.16780v1 Announce Type: new Abstract: This paper presents FairNVT, a lightweight debiasing framework for pretrained transformer-based encoders that improves both representation and predictio

Fast Online 3D Multi-Camera Multi-Object Tracking and Pose Estimation

arXiv:2604.16522v1 Announce Type: new Abstract: This paper proposes a fast and online method for jointly performing 3D multi-object tracking and pose estimation using multiple monocular cameras. Our a

Applications

Federated Rule Ensemble Method in Medical Data

arXiv:2604.17956v1 Announce Type: new Abstract: Machine learning has become integral to medical research and is increasingly applied in clinical settings to support diagnosis and decision-making; howe

applicationsarxiv-cs-lg

FlowC2S: Flowing from Current to Succeeding Frames for Fast and Memory-Efficient Video Continuation

arXiv:2604.17625v1 Announce Type: new Abstract: This paper introduces a novel methodology for generating fast and memory-efficient video continuations. Our method, dubbed FlowC2S, fine-tunes a pre-tra

tutorialsarxiv-cs-cv

From Verbatim to Gist: Distilling Pyramidal Multimodal Memory via Semantic Information Bottleneck for Long-Horizon Video Agents

arXiv:2603.01455v2 Announce Type: replace-cross Abstract: While multimodal large language models have demonstrated impressive short-term reasoning, they struggle with long-horizon video understanding

researcharxiv-cs-cl

Generalizable Radio-Frequency Radiance Fields for Spatial Spectrum Synthesis

arXiv:2502.05708v3 Announce Type: replace-cross Abstract: We present GRaF, Generalizable Radio-Frequency (RF) Radiance Fields, a framework that models RF signal propagation to synthesize spatial spect

tutorialsarxiv-cs-lg

HeteroCache: A Dynamic Retrieval Approach to Heterogeneous KV Cache Compression for Long-Context LLM Inference

arXiv:2601.13684v2 Announce Type: replace Abstract: The linear memory growth of the KV cache poses a significant bottleneck for LLM inference in long-context tasks. Existing static compression methods

researcharxiv-cs-cl

Hybrid Multi-Dimensional MRI Prostate Cancer Detection via Hadamard Network-Based Bias Correction and Residual Networks

arXiv:2604.17107v1 Announce Type: new Abstract: Magnetic Resonance Imaging (MRI) is vital for prostate cancer (PCa) diagnosis. While advanced techniques such as Hybrid Multi-dimensional MRI (HM-MRI) h

Hybrid Spectro-Temporal Fusion Framework for Structural Health Monitoring

arXiv:2604.16589v1 Announce Type: new Abstract: Structural health monitoring plays a critical role in ensuring structural safety by analyzing vibration responses from engineering systems. This paper p

safetyarxiv-cs-lg

Inductive Convolution Nuclear Norm Minimization for Tensor Completion with Arbitrary Sampling

arXiv:2604.17001v1 Announce Type: new Abstract: The recently established Convolution Nuclear Norm Minimization (CNNM) addresses the problem of extit{tensor completion with arbitrary sampling} (TCAS),

Information Representation Fairness in Long-Document Embeddings: The Peculiar Interaction of Positional and Language Bias

arXiv:2601.16934v2 Announce Type: replace Abstract: To be discoverable in an embedding-based search process, each part of a document should be reflected in its embedding representation. To quantify an

safetyarxiv-cs-cl

Instruction-as-State: Environment-Guided and State-Conditioned Semantic Understanding for Embodied Navigation

arXiv:2604.18223v1 Announce Type: new Abstract: Vision-and-Language Navigation requires agents to follow natural-language instructions in visually changing environments. A central challenge is the dyn

agentsarxiv-cs-cv

KaLDeX: Kalman Filter based Linear Deformable Cross Attention for Retina Vessel Segmentation

arXiv:2410.21160v2 Announce Type: replace-cross Abstract: Background and Objective: In the realm of ophthalmic imaging, accurate vascular segmentation is paramount for diagnosing and managing various

Learning the Riccati solution operator for time-varying LQR via Deep Operator Networks

arXiv:2604.18507v1 Announce Type: cross Abstract: We propose a computational framework for replacing the repeated numerical solution of differential Riccati equations in finite-horizon Linear Quadrati

Live LTL Progress Tracking: Towards Task-Based Exploration

arXiv:2604.17106v1 Announce Type: new Abstract: Motivated by the challenge presented by non-Markovian objectives in reinforcement learning (RL), we present a novel framework to track and represent the

agentsarxiv-cs-lg

LLM as a Tool, Not an Agent: Code-Mined Tree Transformations for Neural Architecture Search

arXiv:2604.16555v1 Announce Type: cross Abstract: Neural Architecture Search (NAS) aims to automatically discover high-performing deep neural network (DNN) architectures. However, conventional algorit

agentsarxiv-cs-cv

MAPLE: A Meta-learning Framework for Cross-Prompt Essay Scoring

arXiv:2604.17569v1 Announce Type: new Abstract: Automated Essay Scoring (AES) faces significant challenges in cross-prompt settings, where models must generalize to unseen writing prompts. To address

tutorialsarxiv-cs-cl

Matrix: Peer-to-Peer Multi-Agent Synthetic Data Generation Framework

arXiv:2511.21686v2 Announce Type: replace Abstract: Synthetic data has become increasingly important for training large language models, especially when real data is scarce, expensive, or privacy-sens

agentsarxiv-cs-cl

Memory Centric Power Allocation for Multi-Agent Embodied Question Answering

arXiv:2604.17810v1 Announce Type: new Abstract: This paper considers multi-agent embodied question answering (MA-EQA), which aims to query robot teams on what they have seen over a long horizon. In co

agentsarxiv-cs-ro

Applications

MoGERNN: An Inductive Traffic Predictor for Unobserved Locations

arXiv:2501.12281v2 Announce Type: replace Abstract: Given a partially observed road network, how can we predict the traffic state of interested unobserved locations? Traffic prediction is crucial for

applicationsarxiv-cs-lg

Motion-Guided Semantic Alignment with Negative Prompts for Zero-Shot Video Action Recognition

arXiv:2604.17062v1 Announce Type: new Abstract: Zero-shot action recognition is challenging due to the semantic gap between seen and unseen classes. We present a novel framework that enhances CLIP wit

Navigating Distribution Shifts in Medical Image Analysis: A Survey

arXiv:2411.05824v3 Announce Type: replace-cross Abstract: Medical Image Analysis (MedIA) has become indispensable in modern healthcare, enhancing clinical diagnostics and personalized treatment. Despi

Neural Network-Based Adaptive Event-Triggered Control for Dual-Arm Unmanned Aerial Manipulator Systems

arXiv:2604.17048v1 Announce Type: new Abstract: This paper investigates the control problem of dual-arm unmanned aerial manipulator systems (DAUAMs). Strong coupling between the dual-arm and the multi

researcharxiv-cs-ro

Noise-Adaptive Diffusion Sampling for Inverse Problems Without Task-Specific Tuning

arXiv:2604.16919v1 Announce Type: cross Abstract: Diffusion models (DMs) have recently shown remarkable performance on inverse problems (IPs). Optimization-based methods can fast solve IPs using DMs a

local-aiarxiv-cs-cv

NPCNet: Navigator-Driven Pseudo Text for Deep Clustering of Early Sepsis Phenotyping

arXiv:2602.03562v2 Announce Type: replace Abstract: Electronic Health Records (EHRs) provide high-dimensional temporal data essential for patient modeling; however, conventional algorithmic approaches

NVGS: Neural Visibility for Occlusion Culling in 3D Gaussian Splatting

arXiv:2511.19202v2 Announce Type: replace Abstract: 3D Gaussian Splatting can exploit frustum culling and level-of-detail strategies to accelerate rendering of scenes containing a large number of prim

local-aiarxiv-cs-cv

OASIS: On-Demand Hierarchical Event Memory for Streaming Video Reasoning

arXiv:2604.17052v1 Announce Type: new Abstract: Streaming video reasoning requires models to operate in a setting where history grows without bound while meaningful evidence remains scarce. In such a