Search: “models”

Can a Single Message Paralyze the AI Infrastructure? The Rise of AbO-DDoS Attacks through Targeted Mobius Injection

arXiv:2605.11442v1 Announce Type: cross Abstract: Large Language Model (LLM) agents have emerged as key intermediaries, orchestrating complex interactions between human users and a wide range of digit

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CAST: Collapse-Aware multi-Scale Topology Fusion for Multimodal Coreset Selection

DGX agent

arXiv:2605.11705v1 Announce Type: new Abstract: The training of large multimodal models fundamentally relies on massive image-text datasets, which inevitably incur prohibitive computational overhead.

researcharxiv-cs-cv

13 May 2026

Tutorials

CausalCine: Real-Time Autoregressive Generation for Multi-Shot Video Narratives

arXiv:2605.12496v1 Announce Type: new Abstract: Autoregressive video generation aims at real-time, open-ended synthesis. Yet, cinematic storytelling is not merely the endless extension of a single sce

tutorialsarxiv-cs-cv

Characterizing the Robustness of Black-Box LLM Planners Under Perturbed Observations with Adaptive Stress Testing

arXiv:2505.05665v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have recently demonstrated success in decision-making tasks including planning, control, and prediction, but thei

Debiasing Message Passing to Mitigate Popularity Bias in GNN-based Collaborative Filtering

arXiv:2605.11145v1 Announce Type: cross Abstract: Collaborative filtering (CF) models based on graph neural networks (GNNs) achieve strong performance in recommender systems by propagating user-item s

Decomposing Evolutionary Mixture-of-LoRA Architectures: The Routing Lever, the Lifecycle Penalty, and a Substrate-Conditional Boundary

arXiv:2605.11153v1 Announce Type: new Abstract: We decompose an evolutionary mixture-of-LoRA system on a from-scratch ~150M-parameter widened-D substrate (D=1536, V=32000; D/V approx 0.048; the 'widen

Deep Probabilistic Unfolding for Quantized Compressive Sensing

arXiv:2605.11475v1 Announce Type: new Abstract: We propose a deep probabilistic unfolding model to address the classical quantized compressive sensing problem that leverages an unfolding framework to

researcharxiv-cs-cv

Delightful Gradients Accelerate Corner Escape

arXiv:2605.11908v1 Announce Type: new Abstract: Softmax policy gradient converges at O(1/t), but its transient behavior near sub-optimal corners of the simplex can be exponentially slow. The bottlenec

Disentangled Sparse Representations for Concept-Separated Diffusion Unlearning

arXiv:2605.12122v1 Announce Type: cross Abstract: Unlearning specific concepts in text-to-image diffusion models has become increasingly important for preventing undesirable content generation. Among

researcharxiv-cs-cv

Does Head Pose Correction Improve Biometric Facial Recognition?

arXiv:2512.03199v2 Announce Type: replace Abstract: Biometric facial recognition models often demonstrate significant decreases in accuracy when processing real-world images, often characterized by po

applicationsarxiv-cs-cv

Dual-Temporal LSTM with Hybrid Attention for Airline Passenger Load Factor Forecasting: Integrating Intra-Flight and Inter-Flight Booking Dynamics

arXiv:2605.11569v1 Announce Type: cross Abstract: Accurate short-term demand forecasting is crucial to airline revenue management, yet most existing systems fail to meet this need because current mode

applicationsarxiv-cs-lg

EgoEV-HandPose: Egocentric 3D Hand Pose Estimation and Gesture Recognition with Stereo Event Cameras

arXiv:2605.12297v1 Announce Type: new Abstract: Egocentric 3D hand pose estimation and gesture recognition are essential for immersive augmented/virtual reality, human-computer interaction, and roboti

Enhancing Multilingual Counterfactual Generation through Alignment-as-Preference Optimization

arXiv:2605.11632v1 Announce Type: new Abstract: Self-generated counterfactual explanations (SCEs) are minimally modified inputs (minimality) generated by large language models (LLMs) that flip their o

Environment-Adaptive Preference Optimization for Wildfire Prediction

arXiv:2605.12435v1 Announce Type: new Abstract: Predicting rare extreme events such as wildfires from meteorological data requires models that remain reliable under evolving environmental conditions.

applicationsarxiv-cs-lg

EpiCastBench: Datasets and Benchmarks for Multivariate Epidemic Forecasting

arXiv:2605.11598v1 Announce Type: new Abstract: The increasing adoption of data-driven decision-making in public health has established epidemic forecasting as a critical area of research. Recent adva

Epistemic Uncertainty for Test-Time Discovery

arXiv:2605.11328v1 Announce Type: new Abstract: Automated scientific discovery using large language models relies on identifying genuinely novel solutions. Standard reinforcement learning penalizes hi

Error whitening: Why Gauss-Newton outperforms Newton

arXiv:2605.11316v1 Announce Type: new Abstract: The Gauss-Newton matrix is widely viewed as a positive semidefinite approximation of the Hessian, yet mounting empirical evidence shows that Gauss-Newto

Fast Image Super-Resolution via Consistency Rectified Flow

arXiv:2605.12377v1 Announce Type: new Abstract: Diffusion models (DMs) have demonstrated remarkable success in real-world image super-resolution (SR), yet their reliance on time-consuming multi-step s

applicationsarxiv-cs-cv

FastUMAP: Scalable Dimensionality Reduction via Bipartite Landmark Sampling

arXiv:2605.11428v1 Announce Type: new Abstract: Exploratory analysis of high-dimensional data rarely stops at a single embedding. In practice, analysts rerun dimensionality reduction after changing pr

Local Ai

FeatMap: Understanding image manipulation in the feature space and its implications for feature space geometry

arXiv:2605.11203v1 Announce Type: cross Abstract: Intermediate feature representations represent the backbone for the expressivity and adaptability of deep neural networks. However, their geometric st

local-aiarxiv-cs-cv

Local Ai

FedRot-LoRA: Mitigating Rotational Misalignment in Federated LoRA

arXiv:2602.23638v2 Announce Type: replace Abstract: Federated LoRA provides a communication-efficient mechanism for fine-tuning large language models on decentralized data. In practice, however, a dis

local-aiarxiv-cs-lg

FedSurrogate: Backdoor Defense in Federated Learning via Layer Criticality and Surrogate Replacement

arXiv:2605.11122v1 Announce Type: cross Abstract: Federated Learning remains highly susceptible to backdoor attacks--malicious clients inject targeted behaviours into the global model. Existing defens

Fully AI-Generated Image Detection: Definition, Recent Advances and Challenges

arXiv:2502.19716v2 Announce Type: replace Abstract: Recent advances in visual generative models have enabled the creation of highly realistic, fully AI-generated images without relying on real source

researcharxiv-cs-cv

Grokking or Glitching? How Low-Precision Drives Slingshot Loss Spikes

arXiv:2605.06152v2 Announce Type: replace-cross Abstract: Deep neural networks exhibit periodic loss spikes during unregularized long-term training, a phenomenon known as the 'Slingshot Mechanism.' Ex

GRP: Goal-Reversed Prompting for Zero-Shot Evaluation with LLMs

arXiv:2503.06139v2 Announce Type: replace Abstract: Pairwise LLM-as-a-judge evaluation asks the judge to identify the better of two candidate answers. We study a one-line modification that asks for th

How Does Differential Privacy Affect Social Bias in LLMs? A Systematic Evaluation

arXiv:2605.11195v1 Announce Type: new Abstract: Large language models (LLMs) trained on web-scale corpora can memorize sensitive training data, posing significant privacy risks. Differential privacy (

How far can bias go? Tracing bias from pretraining data to alignment

arXiv:2411.19240v2 Announce Type: replace Abstract: As LLMs are increasingly integrated into user-facing applications, addressing biases that perpetuate societal inequalities is crucial. While much wo

Improving the Performance and Learning Stability of Parallelizable RNNs Designed for Ultra-Low Power Applications

arXiv:2605.11855v1 Announce Type: new Abstract: Sequence learning is dominated by Transformers and parallelizable recurrent neural networks (RNNs) such as state-space models, yet learning long-term de

Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning

arXiv:2605.11889v1 Announce Type: new Abstract: Collaborative machine learning involves training high-quality models using datasets from a number of sources. To incentivize sources to share data, exis

Information theoretic underpinning of self-supervised learning by clustering

arXiv:2605.11870v1 Announce Type: new Abstract: Self-supervised learning (SSL) is recognized as an essential tool for building foundation models for Artificial Intelligence applications. The advances

Instruct-ICL: Instruction-Guided In-Context Learning for Post-Disaster Damage Assessment

arXiv:2605.11439v1 Announce Type: new Abstract: Rapid and accurate situational awareness is essential for effective response during natural disasters, where delays in analysis can significantly hinder

applicationsarxiv-cs-cv

Kairos: A Scalable Serving System for Physical AI

arXiv:2605.11381v1 Announce Type: new Abstract: Physical AI is experiencing rapid growth with frontier foundation models increasing its capabilities across general environments. Physical AI tasks are

researcharxiv-cs-ro

KAN-CL: Per-Knot Importance Regularization for Continual Learning with Kolmogorov-Arnold Networks

arXiv:2605.12306v1 Announce Type: cross Abstract: Catastrophic forgetting remains the central obstacle in continual learning (CL): parameters shared across tasks interfere with one another, and existi

Agents

LDDR: Linear-DPP-Based Dynamic-Resolution Frame Sampling for Video MLLMs

arXiv:2605.11477v1 Announce Type: new Abstract: Video understanding in multimodal large language models requires selecting informative frames from long, redundant videos under limited visual-token bud

agentsarxiv-cs-cv

LEAP: Unlocking dLLM Parallelism via Lookahead Early-Convergence Token Detection

arXiv:2605.10980v1 Announce Type: new Abstract: Diffusion Language Models (dLLMs) have garnered significant attention for their potential in highly parallel processing. The parallel capabilities of ex

Learn to Think: Improving Multimodal Reasoning through Vision-Aware Self-Improvement Training

arXiv:2605.11931v1 Announce Type: new Abstract: Post-training with explicit reasoning traces is common to improve the reasoning capabilities of Multimodal Large Language Models (MLLMs). However, acqui

safetyarxiv-cs-cv

Learnable Multi-level Discrete Wavelet Transforms for 3D Gaussian Splatting Frequency Modulation

arXiv:2602.14199v2 Announce Type: replace-cross Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful approach for novel view synthesis. However, the number of Gaussian primitives often gro

Learning Action Manifold with Multi-view Latent Priors for Robotic Manipulation

arXiv:2605.11832v1 Announce Type: new Abstract: This paper tackles spatial perception and manipulation challenges in Vision-Language-Action (VLA) models. To address depth ambiguity from monocular inpu

researcharxiv-cs-ro

LiBrA-Net: Lie-Algebraic Bilateral Affine Fields for Real-Time 4K Video Dehazing

arXiv:2605.11508v1 Announce Type: new Abstract: Currently, there is a gap in the field of ultra-high-definition (UHD) video dehazing due to the lack of a benchmark for evaluation. Furthermore, existin

LOFT: Low-Rank Orthogonal Fine-Tuning via Task-Aware Support Selection

arXiv:2605.11872v1 Announce Type: new Abstract: Orthogonal parameter-efficient fine-tuning (PEFT) adapts pretrained weights through structure-preserving multiplicative transformations, but existing me

LongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced Colleagues

arXiv:2605.12493v1 Announce Type: new Abstract: Long-term memory is crucial for agents in specialized web environments, where success depends on recalling interface affordances, state dynamics, workfl

MaskTab: Scalable Masked Tabular Pretraining with Scaling Laws and Distillation for Industrial Classification

arXiv:2605.11408v1 Announce Type: cross Abstract: Tabular data forms the backbone of high-stakes decision systems in finance, healthcare, and beyond. Yet industrial tabular datasets are inherently dif

applicationsarxiv-cs-cl

MEME: Multi-entity & Evolving Memory Evaluation

arXiv:2605.12477v1 Announce Type: cross Abstract: LLM-based agents increasingly operate in persistent environments where they must store, update, and reason over information across many sessions. Whil

Tutorials

Mind the Pause: Disfluency-Aware Objective Tuning for Multilingual Speech Correction with LLMs

arXiv:2605.12242v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) transcripts often contain disfluencies, such as fillers, repetitions, and false starts, which reduce readability and

tutorialsarxiv-cs-cl

Missing Old Logits in Asynchronous Agentic RL: Semantic Mismatch and Repair Methods for Off-Policy Correction

arXiv:2605.12070v1 Announce Type: new Abstract: Asynchronous reinforcement learning improves rollout throughput for large language model agents by decoupling sample generation from policy optimization

Multi-Task Representation Learning for Conservative Linear Bandits

arXiv:2605.12176v1 Announce Type: new Abstract: This paper presents the Constrained Multi-Task Representation Learning (CMTRL) framework for linear bandits. We consider T linear bandit tasks in a d di

Nautilus: From One Prompt to Plug-and-Play Robot Learning

model-releasesarxiv-cs-ro

arXiv:2605.11665v1 Announce Type: new Abstract: Robot learning research is fragmented across policy families, benchmark suites, and real robots; each implementation is entangled with the others in a c

NavOL: Navigation Policy with Online Imitation Learning

model-releasesarxiv-cs-ro

arXiv:2605.11762v1 Announce Type: new Abstract: Learning robust navigation policies remains a core challenge in robotics. Offline imitation learning suffers from distribution shift and compounding err