Search: “papers”

Image-Domain Tilt Constrained Distributed Fusion for Maneuvering UAV Tracking with Multi-Camera Electro-Optical Observations

arXiv:2607.01008v1 Announce Type: cross Abstract: Short-horizon prediction is essential for electro-optical UAV tracking, especially when the target is small, maneuvering, or intermittently observed.

researcharxiv-cs-ro

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Local Ai

K-Merge: Online Continual Merging of Adapters for On-device Large Language Models

DGX agent

arXiv:2510.13537v2 Announce Type: replace-cross Abstract: On-device deployment of Large Language Models (LLMs) frequently leverages Low-Rank Adapters (LoRAs) to support diverse downstream tasks under

local-aiarxiv-cs-ai

2 Jul 2026

KungfuBot: Physics-Based Humanoid Whole-Body Control for Learning Highly-Dynamic Skills

arXiv:2506.12851v3 Announce Type: replace-cross Abstract: Humanoid robots are promising to acquire various skills by imitating human behaviors. However, existing algorithms are only capable of trackin

safetyarxiv-cs-ai

Libra: Training the Environment for Agentic Information Retrieval

arXiv:2607.00016v1 Announce Type: cross Abstract: Information localization within massive repositories is a cornerstone of agentic LLM systems. While synthetic data-driven optimization has proven succ

local-aiarxiv-cs-ai

Lost in the Tail: Addressing Geographic Imbalance in Urban Visual Place Recognition

arXiv:2607.00090v1 Announce Type: cross Abstract: Urban-scale Visual Place Recognition (VPR) aims to identify the geographic location of a query image by matching it against a geo-tagged database. Whi

Magic-MM-Embedding: Towards Visual-Token-Efficient Universal Multimodal Embedding with MLLMs

arXiv:2602.05275v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have shown immense promise in universal multimodal retrieval, which aims to find relevant items of various

researcharxiv-cs-cv

Memory-Native Non-Terrestrial Networks for Embodied Intelligence

arXiv:2607.00029v1 Announce Type: cross Abstract: Non-terrestrial networks (NTN) provide ubiquitous connectivity for embodied intelligence (EI), enabling robots in wilderness to leverage cloud resourc

researcharxiv-cs-ai

MindAU: EEG-Conditioned Facial Action Unit Editing via Dual-Stream Manifold Alignment

model-releasesarxiv-cs-cv

arXiv:2607.00410v1 Announce Type: new Abstract: Recent brain decoding studies have made substantial progress in reconstructing externally perceived visual content from neural signals. However, using e

Hardware

MosaicKV: Serving Long-Context LLM with Dynamic Two-D KV Cache Compression

arXiv:2607.00760v1 Announce Type: new Abstract: Long-context LLM services now sustain prompts with hundreds of thousands to millions of tokens, making the key-value (KV) cache a first-order serving co

hardwarearxiv-cs-lg

MoVA: Learning Asymmetric Dual Projections for Modular Long Video-Text Alignment

arXiv:2607.00858v1 Announce Type: new Abstract: Contrastive pre-training has propelled video-text alignment, yet models often inherit the critical limitations of their image-text predecessors like CLI

safetyarxiv-cs-cv

Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning

arXiv:2505.19614v2 Announce Type: replace-cross Abstract: Multimodal learning has seen remarkable progress, particularly with large-scale pre-training across various modalities. Most current approache

safetyarxiv-cs-cv

Tutorials

Muon as a Residual Connection

arXiv:2607.01124v1 Announce Type: cross Abstract: Muon has recently emerged as one of the most effective optimizers for training large neural networks, yet its empirical success has been explained fro

tutorialsarxiv-cs-ai

NeuroFilter: Activation-Based Guardrails for Privacy-Conscious LLM Agents

arXiv:2601.14660v2 Announce Type: replace-cross Abstract: Agentic Large Language Models (LLMs) are models able to reason, plan, and execute tools over unstructured data. These abilities are enabling t

Tutorials

New research from Google. LLMs hallucinate with high confidence, miss their own knowledge boundaries, and misreport uncertainty. Most fixes …

New research from Google. LLMs hallucinate with high confidence, miss their own knowledge boundaries, and misreport uncertainty. Most fixes bolt calibration on from the outside. RLMF turns the model o

tutorialsdair-ai--x

PedNStream: Scalable Network Flow Simulation for Pedestrian Traffic Management

arXiv:2607.01021v1 Announce Type: new Abstract: Large-scale crowd management requires pedestrian simulations that are both computationally efficient and compatible with feedback-based control. However

applicationsarxiv-cs-ai

Perceive-to-Reason: Decoupling Perception and Reasoning for Fine-Grained Visual Reasoning

arXiv:2607.01191v1 Announce Type: new Abstract: Fine-grained visual reasoning remains challenging for vision-language models, especially when small but critical visual cues are buried in high-resoluti

local-aiarxiv-cs-cv

PETIMOT: A Novel Framework for Inferring Protein Motions from Sparse Data Using SE(3)-Equivariant Graph Neural Networks

arXiv:2504.02839v2 Announce Type: replace-cross Abstract: Proteins move and deform to ensure their biological functions. Despite significant progress in protein structure prediction, approximating con

researcharxiv-cs-lg

Planning over MAPF Agent Dependencies via Multi-Dependency PIBT

arXiv:2603.23405v2 Announce Type: replace-cross Abstract: Modern Multi-Agent Path Finding (MAPF) algorithms must plan for hundreds to thousands of agents in congested environments within a second, req

Post-Training Pruning for Diffusion Transformers

arXiv:2607.00927v1 Announce Type: cross Abstract: Diffusion Transformers (DiTs) have demonstrated impressive performance in image generation but suffer from substantial computational overhead and reso

Prompt Optimization for User Simulation in Conversational Recommender Systems: A Multi-Objective Framework

arXiv:2607.00010v1 Announce Type: cross Abstract: Conversational recommender systems (CRSs) are a core component of next-generation intelligent recommender systems because they enable users to activel

safetyarxiv-cs-ai

Prompting GPT-5 on Scrum Certification Questions: An Empirical Accuracy Study

arXiv:2607.00049v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in Agile Software Development for documentation, coaching, and training. As practitioners adopt the

QCA: Query- and Content-Aware Keyframe Selection for Long Video Understanding

arXiv:2607.00983v1 Announce Type: new Abstract: Video understanding is often plagued by severe temporal redundancy, where processing dense frame sequences is both semantically inefficient and computat

researcharxiv-cs-cv

QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networks

model-releasesarxiv-cs-cv

arXiv:2607.00974v1 Announce Type: cross Abstract: Static radio maps provide location-dependent propagation priors, but they cannot capture short-term blockage caused by moving objects. Direct sensing-

Quantifying the Affective Gap: A Zero-Shot Evaluation of LLMs on Fine-Grained Emotion Taxonomies

model-releasesarxiv-cs-cl

arXiv:2607.00968v1 Announce Type: new Abstract: Emotion recognition in natural language is a foundational challenge in affective computing, with critical implications for human-computer interaction, m

Quantum vs. Classical Machine Learning: A Unified Empirical Comparison

model-releasesarxiv-cs-lg

arXiv:2607.01197v1 Announce Type: new Abstract: Quantum computing has emerged as a promising computational paradigm for machine learning (ML), with the potential to offer computational advantages over

Recovering Input Text from Hidden States: Study of Gradient-Based Inversion of Decoder-Only Language Models

arXiv:2607.00852v1 Announce Type: cross Abstract: This work studies the hidden-state inversion problem: recovering the original input token sequence of a decoder-only language model from its last-laye

Robust Operational Space Control with Conformal Disturbance Bounds for Safe Redundant Manipulation

arXiv:2607.00424v1 Announce Type: new Abstract: Redundant robotic manipulators operating in constrained and human-interactive environments require accurate task-space tracking together with rigorous s

safetyarxiv-cs-ro

Hardware

ROSA: A Robotics Foundation Model Serving System for Robot Factories

arXiv:2607.01088v1 Announce Type: new Abstract: Robotics foundation models (RFMs) are making general-purpose robots increasingly practical for factory deployments. While RFM serving systems are centra

hardwarearxiv-cs-ro

Segmenting, Fast and Slow: Real-Time Open-Vocabulary Video Instance Segmentation with Dual-Path Processing

arXiv:2607.00124v1 Announce Type: new Abstract: Object-centric models inspired by DETR have become the dominant paradigm for open-vocabulary video instance segmentation (OV-VIS). While recent efforts

local-aiarxiv-cs-cv

SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization

arXiv:2604.06817v2 Announce Type: replace Abstract: We present SemEval-2026 Task 9, a shared task on online polarization detection, covering 22 languages and comprising over 110K annotated instances.

researcharxiv-cs-cl

Semi-Bandit Learning for Monotone Stochastic Optimization

arXiv:2312.15427v3 Announce Type: replace Abstract: Stochastic optimization is a widely used approach for optimization under uncertainty, where uncertain input parameters are modeled by random variabl

safetyarxiv-cs-lg

SenseWalk: Agent-Based Semantic Trajectory Simulation Powered by Large Language Models in Zoned Environments

arXiv:2607.00989v1 Announce Type: cross Abstract: Semantic trajectory analysis has recently emerged as an approach for modeling human movement by capturing implicit patterns and behaviors through sema

Sensorless Four-Channel Control Architecture Using Inverse Dynamics Modeling for Human-Scale Bilateral Teleoperation

arXiv:2607.01201v1 Announce Type: new Abstract: The four-channel teleoperation architecture is a well-established framework for achieving transparency in bilateral systems. However, its performance in

applicationsarxiv-cs-ro

SkillSelect-Serve: Budget-Controllable and QoS-Aware Skill Service Recommendation and Composition for Small LLM Agents

arXiv:2607.00011v1 Announce Type: cross Abstract: Reusable skill libraries are becoming important infrastructure for large language model (LLM) agents, yet existing selection methods often treat skill

SlowBA: An efficiency backdoor attack towards VLM-based GUI agents

arXiv:2603.08316v3 Announce Type: replace-cross Abstract: Modern vision-language-model (VLM) based graphical user interface (GUI) agents are expected not only to execute actions accurately but also to

agentsarxiv-cs-cl

SoK: Attack and Defense Landscape of Mobile On-device AI Systems

arXiv:2607.00362v1 Announce Type: cross Abstract: Mobile on-device AI (MoAI) systems that integrate locally deployed AI models with conventional mobile software components are emerging as a key paradi

local-aiarxiv-cs-ai

Spatio-Temporal Gaussian Process for Building Terrain-Incorporating Wind Power Curves

arXiv:2607.00051v1 Announce Type: cross Abstract: Accurate modeling of wind turbine power curves is crucial for optimal wind farm operation. Nearly all existing power curve models focus on temporal va

safetyarxiv-cs-lg

Tail-Shape Estimation in LLM Evaluation Is Fragile: A Protocol for Diagnosing False Positives

model-releasesarxiv-cs-lg

arXiv:2606.16511v2 Announce Type: replace Abstract: Recent work motivates moving large language model (LLM) evaluation from mean-based to tail-aware metrics, including conditional value-at-risk and ta

TANDEM: Temporal Attention-guided Neural Differential Equations for Missingness in Time Series Classification

arXiv:2508.17519v3 Announce Type: replace-cross Abstract: Handling missing data in time series classification remains a significant challenge in various domains. Traditional methods often rely on impu

The MMM Data Model -- A Normative Specification for Knowledge Interoperability in a Decentralisable Knowledge Commons

arXiv:2607.00032v1 Announce Type: new Abstract: Many information systems are built around documents: self-contained units optimised for print production and linear reading. While effective for large-s

applicationsarxiv-cs-ai

Towards Memory-Efficient Autoregressive Video Generation via Instance-Specific Parametric Absorption

arXiv:2607.00712v1 Announce Type: new Abstract: Autoregressive (AR) streaming models have emerged as a powerful paradigm for long video generation. However, the linearly growing Key-Value (KV) cache p

local-aiarxiv-cs-cv

Typography-Based Monocular Distance Estimation for Advanced Driver-Assistance Systems

arXiv:2607.00319v1 Announce Type: new Abstract: Estimating the distance to a leading vehicle is a basic input to forward collision warning, adaptive cruise control, and automated emergency braking. Pr

applicationsarxiv-cs-cv

Universal Image Immunization against Diffusion-based Image Editing via Semantic Injection

arXiv:2602.14679v2 Announce Type: replace Abstract: Diffusion model advances have enabled powerful text-guided image editing, but also raise ethical and legal risks such as deepfakes and unauthorized

applicationsarxiv-cs-cv

Vibe Coding Ate My Homework: An evaluation of AI approaches to greenfield software engineering and programming

arXiv:2606.18293v2 Announce Type: replace-cross Abstract: Thanks to rapid developments in generative AI, we are in the midst of a paradigm shift that may change how we interact with computers forever.

researcharxiv-cs-ai

VisReason: A Large-Scale Dataset for Visual Chain-of-Thought Reasoning

model-releasesarxiv-cs-cv

arXiv:2511.17731v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting has proven remarkably effective for eliciting complex reasoning in large language models (LLMs). Yet, its potential

1/ On Training in Imagination - Dwarkesh's episode has a segment on dreaming as one of the next training paradigms. The idea is that a model…

1/ On Training in Imagination - Dwarkesh's episode has a segment on dreaming as one of the next training paradigms. The idea is that a model learns mostly inside its own, by imagining what would happe

researchyann-lecun--x

1 Jul 2026

A Large-Language-Model Supported Personalized Driving Framework for Lane Change in Highway Scenarios

model-releasesarxiv-cs-ro

arXiv:2606.31483v1 Announce Type: new Abstract: Personalized driving can improve the user acceptance of automated driving systems. However, existing methods still provide limited support for translati

1 Jul 2026

A Lifecycle and Application-Stack Survey of Large Language Model Vulnerabilities: Attacks, Risks, Defenses, and Open Problems