Search: “papers”

Sparse Hypergraph-Enhanced Frame-Event Object Detection with Fine-Grained MoE

arXiv:2604.11140v1 Announce Type: new Abstract: Integrating frame-based RGB cameras with event streams offers a promising solution for robust object detection under challenging dynamic conditions. How

researcharxiv-cs-cv

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Safety

Spatiotemporal-Aware Bit-Flip Injection on DNN-based Advanced Driver Assistance Systems (extended version)

DGX agent

arXiv:2604.03753v2 Announce Type: replace-cross Abstract: Modern advanced driver assistance systems (ADAS) rely on deep neural networks (DNNs) for perception and planning. Since DNNs' parameters resid

safetyarxiv-cs-lg

14 Apr 2026

Speaking to No One: Ontological Dissonance and the Double Bind of Conversational AI

arXiv:2604.10833v1 Announce Type: cross Abstract: Recent reports indicate that sustained interaction with conversational artificial intelligence (AI) systems can, in a small subset of users, contribut

safetyarxiv-cs-ai

Local Ai

SpotFormer: Multi-Scale Spatio-Temporal Transformer for Facial Expression Spotting

arXiv:2407.20799v3 Announce Type: replace Abstract: Facial expression spotting, identifying periods where facial expressions occur in a video, is a significant yet challenging task in facial expressio

local-aiarxiv-cs-cv

Spotlight and Shadow: Attention-Guided Dual-Anchor Introspective Decoding for MLLM Hallucination Mitigation

arXiv:2604.10071v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable reasoning capabilities yet continue to suffer from hallucination, where generated

tutorialsarxiv-cs-cv

StableTTA: Training-Free Test-Time Adaptation that Improves Model Accuracy on ImageNet1K to 96%

arXiv:2604.04552v2 Announce Type: replace-cross Abstract: Ensemble methods are widely used to improve predictive performance, but their effectiveness often comes at the cost of increased memory usage

STGV: Spatio-Temporal Hash Encoding for Gaussian-based Video Representation

arXiv:2604.10910v1 Announce Type: new Abstract: 2D Gaussian Splatting (2DGS) has recently become a promising paradigm for high-quality video representation. However, existing methods employ content-ag

researcharxiv-cs-cv

Stop Fixating on Prompts: Reasoning Hijacking and Constraint Tightening for Red-Teaming LLM Agents

arXiv:2604.05549v2 Announce Type: replace Abstract: With the widespread application of LLM-based agents across various domains, their complexity has introduced new security threats. Existing red-team

safetyarxiv-cs-cl

SynthAgent: Adapting Web Agents with Synthetic Supervision

arXiv:2511.06101v3 Announce Type: replace-cross Abstract: Web agents struggle to adapt to new websites due to the scarcity of environment specific tasks and demonstrations. Recent works have explored

TacMan-Turbo: Proactive Tactile Control for Robust and Efficient Articulated Object Manipulation

arXiv:2508.02204v4 Announce Type: replace Abstract: Adept manipulation of articulated objects is essential for robots to operate successfully in human environments. Such manipulation requires both eff

tutorialsarxiv-cs-ro

TARAC: Mitigating Hallucination in LVLMs via Temporal Attention Real-time Accumulative Connection

arXiv:2504.04099v2 Announce Type: replace-cross Abstract: Large Vision-Language Models have demonstrated remarkable capabilities, yet they suffer from hallucinations that limit practical deployment. W

Hardware

Tessera: Unlocking Heterogeneous GPUs through Kernel-Granularity Disaggregation

arXiv:2604.10180v1 Announce Type: cross Abstract: Disaggregation maps parts of an AI workload to different types of GPUs, offering a path to utilize modern heterogeneous GPU clusters. However, existin

hardwarearxiv-cs-lg

Local Ai

The Impact of Federated Learning on Distributed Remote Sensing Archives

arXiv:2604.11562v1 Announce Type: new Abstract: Remote sensing archives are inherently distributed: Earth observation missions such as Sentinel-1, Sentinel-2, and Sentinel-3 have collectively accumula

local-aiarxiv-cs-cv

The Phantom of PCIe: Constraining Generative Artificial Intelligences for Practical Peripherals Trace Synthesizing

arXiv:2411.06376v3 Announce Type: replace-cross Abstract: Peripheral Component Interconnect Express (PCIe) is the de facto interconnect standard for high-speed peripherals and CPUs. The development of

The Rise and Fall of G in AGI

arXiv:2604.09911v1 Announce Type: cross Abstract: In the psychological literature the term `general intelligence' describes correlations between abilities and not simply the number of abilities. This

The Weight of a Bit: EMFI Sensitivity Analysis of Embedded Deep Learning Models

arXiv:2602.16309v2 Announce Type: replace-cross Abstract: Fault injection attacks on embedded neural network models have been shown as a potent threat. Numerous works studied resilience of models from

TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning

arXiv:2505.11737v4 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) have demonstrated impressive capabilities, their output quality remains inconsistent across various applica

TorchUMM: A Unified Multimodal Model Codebase for Evaluation, Analysis, and Post-training

arXiv:2604.10784v1 Announce Type: new Abstract: Recent advances in unified multimodal models (UMMs) have led to a proliferation of architectures capable of understanding, generating, and editing acros

Towards an Appropriate Level of Reliance on AI: A Preliminary Reliance-Control Framework for AI in Software Engineering

arXiv:2604.10530v1 Announce Type: cross Abstract: How software developers interact with Artificial Intelligence (AI)-powered tools, including Large Language Models (LLMs), plays a vital role in how th

Towards Efficient Large Vision-Language Models: A Comprehensive Survey on Inference Strategies

arXiv:2603.27960v2 Announce Type: replace-cross Abstract: Although Large Vision Language Models (LVLMs) have demonstrated impressive multimodal reasoning capabilities, their scalability and deployment

researcharxiv-cs-cl

Training Deep Visual Networks Beyond Loss and Accuracy Through a Dynamical Systems Approach

arXiv:2604.09716v1 Announce Type: cross Abstract: Deep visual recognition models are usually trained and evaluated using metrics such as loss and accuracy. While these measures show whether a model is

Training-Free Model Ensemble for Single-Image Super-Resolution via Strong-Branch Compensation

arXiv:2604.11564v1 Announce Type: new Abstract: Single-image super-resolution has progressed from deep convolutional baselines to stronger Transformer and state-space architectures, yet the correspond

researcharxiv-cs-cv

Training-Free Multi-User Generative Semantic Communications via Null-Space Diffusion Sampling

arXiv:2405.09866v2 Announce Type: replace-cross Abstract: In recent years, novel communication strategies have emerged to face the challenges that the increased number of connected devices and the hig

researcharxiv-cs-lg

Transformers Learn the Optimal DDPM Denoiser for Multi-Token GMMs

arXiv:2604.10074v1 Announce Type: new Abstract: Transformer-based diffusion models have demonstrated remarkable performance at generating high-quality samples. However, our theoretical understanding o

tutorialsarxiv-cs-lg

Applications

Tuning Language Models for Robust Prediction of Diverse User Behaviors

arXiv:2505.17682v2 Announce Type: replace-cross Abstract: Predicting user behavior is essential for intelligent assistant services, yet deep learning models often struggle to capture long-tailed behav

applicationsarxiv-cs-ai

Local Ai

UHD-GPGNet: UHD Video Denoising via Gaussian-Process-Guided Local Spatio-Temporal Modeling

arXiv:2604.11014v1 Announce Type: new Abstract: Ultra-high-definition (UHD) video denoising requires simultaneously suppressing complex spatio-temporal degradations, preserving fine textures and chrom

local-aiarxiv-cs-cv

Ultra-Low-Dimensional Prompt Tuning via Random Projection

model-releasesarxiv-cs-cl

arXiv:2502.04501v3 Announce Type: replace Abstract: Large language models achieve state-of-the-art performance but are increasingly costly to fine-tune. Prompt tuning is a parameter-efficient fine-tun

Unified Graph Prompt Learning via Low-Rank Graph Message Prompting

model-releasesarxiv-cs-lg

arXiv:2604.11257v1 Announce Type: new Abstract: Graph Data Prompt (GDP), which introduces specific prompts in graph data for efficiently adapting pre-trained GNNs, has become a mainstream approach to

Agents

Unified Unsupervised and Sparsely-Supervised 3D Object Detection by Semantic Pseudo-Labeling and Prototype Learning

arXiv:2602.21484v2 Announce Type: replace Abstract: 3D object detection is essential for autonomous driving and robotic perception, yet its reliance on large-scale manually annotated data limits scala

agentsarxiv-cs-cv

Use of AI Tools: Guidelines to Maintain Academic Integrity in Computing Colleges

arXiv:2604.11111v1 Announce Type: cross Abstract: The rapid adoption of AI tools such as ChatGPT has significantly transformed academic practices, offering considerable benefits for both students and

tutorialsarxiv-cs-ai

Agents

Using Unwrapped Full Color Space Palette Recording to Measure Exposedness of a Vehicle Exterior Parts for External Human Machine Interfaces

arXiv:2604.11406v1 Announce Type: new Abstract: One of the concerns with autonomous vehicles is their ability to communicate their intent to other road users, specially pedestrians, in order to preven

agentsarxiv-cs-ro

Variable Selection Using Relative Importance Rankings

model-releasesarxiv-cs-lg

arXiv:2509.10853v2 Announce Type: replace-cross Abstract: Although conceptually related, variable selection and relative importance (RI) analysis have been treated quite differently in the literature.

VERTIGO: Visual Preference Optimization for Cinematic Camera Trajectory Generation

arXiv:2604.02467v2 Announce Type: replace-cross Abstract: Cinematic camera control relies on a tight feedback loop between director and cinematographer, where camera motion and framing are continuousl

Vestibular reservoir computing

arXiv:2604.09943v1 Announce Type: new Abstract: Reservoir computing (RC) is a computational framework known for its training efficiency, making it ideal for physical hardware implementations. However,

researcharxiv-cs-lg

Vibe-driven model-based engineering

arXiv:2604.10645v1 Announce Type: cross Abstract: There is a pressing need for better development methods and tools to keep up with the growing demand and increasing complexity of new software systems

VisText-Mosquito: A Unified Multimodal Dataset for Visual Detection, Segmentation, and Textual Explanation on Mosquito Breeding Sites

arXiv:2506.14629v3 Announce Type: replace-cross Abstract: Mosquito-borne diseases pose a major global health risk, requiring early detection and proactive control of breeding sites to prevent outbreak

researcharxiv-cs-cl

Visual Late Chunking: An Empirical Study of Contextual Chunking for Efficient Visual Document Retrieval

arXiv:2604.10167v1 Announce Type: cross Abstract: Multi-vector models dominate Visual Document Retrieval (VDR) due to their fine-grained matching capabilities, but their high storage and computational

researcharxiv-cs-cl

VLMaterial: Vision-Language Model-Based Camera-Radar Fusion for Physics-Grounded Material Identification

arXiv:2604.11671v1 Announce Type: cross Abstract: Accurate material recognition is a fundamental capability for intelligent perception systems to interact safely and effectively with the physical worl

safetyarxiv-cs-ro

WARPED: Wrist-Aligned Rendering for Robot Policy Learning from Egocentric Human Demonstrations

arXiv:2604.10809v1 Announce Type: new Abstract: Recent advancements in learning from human demonstration have shown promising results in addressing the scalability and high cost of data collection req

safetyarxiv-cs-ro

WBCBench 2026: A Challenge for Robust White Blood Cell Classification Under Class Imbalance

model-releasesarxiv-cs-cv

arXiv:2604.10797v1 Announce Type: new Abstract: We present WBCBench 2026, an ISBI challenge and benchmark for automated WBC classification designed to stress-test algorithms under three key difficulti

Applications

What Do Vision-Language Models Encode for Personalized Image Aesthetics Assessment?

arXiv:2604.11374v1 Announce Type: cross Abstract: Personalized image aesthetics assessment (PIAA) is an important research problem with practical real-world applications. While methods based on vision

applicationsarxiv-cs-cl

When Can You Poison Rewards? A Tight Characterization of Reward Poisoning in Linear MDPs

arXiv:2604.10062v1 Announce Type: new Abstract: We study reward poisoning attacks in reinforcement learning (RL), where an adversary manipulates rewards within constrained budgets to force the target

safetyarxiv-cs-lg

Who Gets Which Message? Auditing Demographic Bias in LLM-Generated Targeted Text

arXiv:2601.17172v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly capable of generating personalized, persuasive text at scale, raising new questions about bias a

Who Handles Orientation? Investigating Invariance in Feature Matching

arXiv:2604.11809v1 Announce Type: new Abstract: Finding matching keypoints between images is a core problem in 3D computer vision. However, modern matchers struggle with large in-plane rotations. A st

tutorialsarxiv-cs-cv

Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2604.10079v1 Announce Type: new Abstract: Supervised Fine-Tuning (SFT) is the standard approach for adapting large language models (LLMs) to downstream tasks. However, we observe a persistent fa

WM-DAgger: Enabling Efficient Data Aggregation for Imitation Learning with World Models

arXiv:2604.11351v1 Announce Type: new Abstract: Imitation learning is a powerful paradigm for training robotic policies, yet its performance is limited by compounding errors: minor policy inaccuracies

safetyarxiv-cs-ro

Wolkowicz-Styan Upper Bound on the Hessian Eigenspectrum for Cross-Entropy Loss in Nonlinear Smooth Neural Networks

arXiv:2604.10202v1 Announce Type: cross Abstract: Neural networks (NNs) are central to modern machine learning and achieve state-of-the-art results in many applications. However, the relationship betw

YIELD: A Large-Scale Dataset and Evaluation Framework for Information Elicitation Agents

arXiv:2604.10968v1 Announce Type: new Abstract: Most conversational agents (CAs) are designed to satisfy user needs through user-driven interactions. However, many real-world settings, such as academi

safetyarxiv-cs-cl