Search: “framework”

HARP: Hierarchical Adaptive Ranking with Preference-Adaptive Fusion for Query-Based CVE Prioritization

arXiv:2608.19430v1 Announce Type: cross Abstract: Vulnerability prioritization is inherently preference dependent, since the same CVE can receive different remediation priority under different operati

safetyarxiv-cs-cl

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

HBVLA: Pushing 1-Bit Post-Training Quantization for Vision-Language-Action Models

DGX agent

arXiv:2602.13710v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models enable instruction-following embodied control, but their large compute and memory footprints hinder deployment o

safetyarxiv-cs-lg

21 Aug 2026

How agents can delegate better

model-releasesgoogle-cloud-ai

In any organizational behavior class, students will learn that effective delegation is among the most important skills for a seasoned leader. Getting meaningful work done involves careful coordination

ID-VTG: Image-Disambiguated Video Temporal Grounding

arXiv:2608.20127v1 Announce Type: new Abstract: Video Temporal Grounding (VTG) faces significant challenges when natural language queries must distinguish between multiple events involving visually si

researcharxiv-cs-cv

In 1948, a 32-year-old at Bell Labs published a paper nobody fully understood. Engineers found it too mathematical. Mathematicians found it …

model-releaseselon-musk--x

In 1948, a 32-year-old at Bell Labs published a paper nobody fully understood. Engineers found it too mathematical. Mathematicians found it too engineering-focused. One prominent mathematician reviewe

In Two Minds about Lifelong Learning: Exploring Hemispheric Redundancy and Specialisation in Neural Models

arXiv:2608.19514v1 Announce Type: cross Abstract: Persistent intelligent systems require the ability to learn continually, but current machine learning approaches face significant challenges in this a

tutorialsarxiv-cs-ai

Inject, Align, Recover: Staged Post-Training for Retrieval-Free Document Knowledge Internalization

model-releasesarxiv-cs-ai

arXiv:2608.20281v1 Announce Type: cross Abstract: Large language models often fail to answer questions about a bounded document collection when the source documents are not retrieved at inference time

Learn for Variation: Efficient AAV Trajectory Learning through a Differentiable Wireless World Model

arXiv:2603.18853v3 Announce Type: replace-cross Abstract: Autonomous aerial vehicles (AAVs) enable data collection for sixth-generation Internet-of-Things networks, but their trajectories couple nonli

safetyarxiv-cs-lg

Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space

arXiv:2608.19977v1 Announce Type: new Abstract: Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating this behavior in quadrupedal robots ha

safetyarxiv-cs-ro

Learning piecewise-smooth dynamical systems

model-releasesarxiv-cs-lg

arXiv:2608.19785v1 Announce Type: cross Abstract: Discovering dynamical systems from trajectory data is a central problem in applied mathematics and engineering. Whilst recent advances in machine lear

Learning the Right Abstraction: Neural Reduced Dynamics for Complex Robot Control

arXiv:2608.19375v1 Announce Type: new Abstract: High-fidelity embodied AI simulators provide realistic evaluation of complex robotic systems, but their computational cost limits their direct use for l

safetyarxiv-cs-ro

Let's Scale Step by Step: Compute-Efficient Hyperparameter Transfer for Large-Scale Mixture-of-Experts

arXiv:2608.20061v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures significantly expand model capacity without a proportional increase in computational cost. However, optimizing

tutorialsarxiv-cs-ai

Listening Forward: Next Patch Embedding Prediction Enables Scalable Audio Learners

arXiv:2608.19863v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has driven substantial progress in audio representation learning, though existing methods have increasingly relied on e

tutorialsarxiv-cs-ai

LLM as Detector: An In-context Learning Approach for Tabular Anomaly Detection

arXiv:2608.19463v1 Announce Type: new Abstract: Anomaly detection in tabular data is challenging because abnormal samples often arise as violations of cross-feature dependencies rather than simple mar

applicationsarxiv-cs-lg

Longitudinal Bayesian Learning of Continuous Disease Position across the Alzheimer's Disease Continuum

arXiv:2608.19436v1 Announce Type: cross Abstract: Alzheimer's disease (AD) progresses as a continuous biological process, whereas most existing neuroimaging-based artificial intelligence methods remai

Maximum Likelihood Reinforcement Learning

arXiv:2602.02710v2 Announce Type: replace Abstract: Reinforcement learning (RL) is the method of choice for training models in setups where the objective function can only be evaluated by sampling fro

researcharxiv-cs-lg

Microlensify: a Transformer Based Machine Learning Classifier for Microlensing Events Trained on TESS Light Curves

arXiv:2608.19419v1 Announce Type: cross Abstract: Microlensing can reveal populations of faint compact objects that are otherwise difficult to detect. Depending on their design, all-sky surveys have t

researcharxiv-cs-lg

Agents

MidTool: Mid-training Data Synthesis for Agentic Tool Use

arXiv:2608.20314v1 Announce Type: new Abstract: Mid-training is increasingly recognized as a critical stage for shaping the capabilities of large language models. Recent work has shown that targeted m

agentsarxiv-cs-ai

Mitigating Identity Essentialism in LLM Agents with Longitudinal Life Trajectories

arXiv:2608.19621v1 Announce Type: new Abstract: Large language models (LLMs) offer a scalable approach to social simulation, but their credibility depends on how agents are constructed. Existing metho

safetyarxiv-cs-cl

Multi-Source Wasserstein Distributionally Robust Graph Learning

arXiv:2608.19914v1 Announce Type: new Abstract: Network topology inference from graph signals is central to graph signal processing with applications in neuroscience, sensor, and social networks. In p

safetyarxiv-cs-lg

MUST-PET: MUltimodal Self-supervised learning across Tracers for whole-body PET/CT-based lesion segmentation

arXiv:2608.19666v1 Announce Type: new Abstract: Deep learning-based whole-body PET-CT lesion segmentation can support cancer staging, treatment planning, and response assessment, but generalization is

researcharxiv-cs-cv

Local Ai

Open-Vocabulary 3D Object Detection with Co-Distillation Discovery and Dual Guidance Robust Training

arXiv:2608.19973v1 Announce Type: cross Abstract: Recently, open-vocabulary 3D object detection (3D-OVD) has gained increasing attention for its ability to detect unseen objects in 3D scenes. Existing

local-aiarxiv-cs-ai

Orthogonal JEPA: Factorized Predictive States for Latent World Models

arXiv:2608.20065v1 Announce Type: new Abstract: World models construct latent states that support prediction, planning, and reasoning about an underlying system. Joint-embedding predictive architectur

tutorialsarxiv-cs-lg

OrthoSkillVLA: Continual Skill Learning via Gradient-Informed Skill Subspace Adaptation

model-releasesarxiv-cs-cv

arXiv:2608.19589v1 Announce Type: cross Abstract: Pretrained Vision-Language-Action models provide a strong foundation for robot learning, but sequentially adapting them to diverse skills can perturb

PEA-DPO: Perception-Enhanced Alignment Direct Preference Optimization for MLLMs Alignment

arXiv:2608.19598v1 Announce Type: cross Abstract: Direct Preference Optimization (DPO) has emerged as an effective approach for aligning large language models (LLMs) with human preferences. However, i

PhysSFI-Net: Physics-informed Geometric Learning of Skeletal and Facial Interactions for Orthognathic Surgical Outcome Prediction

arXiv:2601.02088v3 Announce Type: replace Abstract: Orthognathic surgery repositions jaw bones to restore occlusion and enhance facial aesthetics. Accurate simulation of postoperative facial morpholog

researcharxiv-cs-cv

Local Ai

Prompt-Conditioned Channel Attention for Hierarchical Feature Modulation toward Anatomy-Agnostic Segmentation

arXiv:2608.20229v1 Announce Type: cross Abstract: Anatomically plausible segmentation remains challenging because of low contrast, ambiguous boundaries, and modality-specific artifacts. Interactive se

local-aiarxiv-cs-ai

ProteinZero: Self-Improving Protein Generation via Online Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2506.07459v4 Announce Type: replace Abstract: Protein generative models have shown remarkable promise in protein design, yet their success rates remain constrained by reliance on curated sequenc

Quantifying Event Impacts on Time Series via Multiscale Contrastive Learning

arXiv:2608.19447v1 Announce Type: new Abstract: Shocks that spread through the web, such as cybersecurity breach disclosures, can abruptly disrupt financial time series and cause substantial abnormal

applicationsarxiv-cs-lg

Quantum Gaussian processes for prediction of channel observations

model-releasesarxiv-cs-lg

arXiv:2608.19306v1 Announce Type: cross Abstract: Given a set of input states, we consider the task of predicting the expectation value of a Pauli observable at the output of an unknown quantum evolut

Quantum Kernel Estimation for the Discovery of Early Lung Cancer Detection

arXiv:2608.19304v1 Announce Type: cross Abstract: Lung cancer screening with low-dose chest computed tomography reduces mortality, but its impact is limited by uptake, adherence, and management challe

QUASAR: A Quantum-Classical Neural Network for SAR Satellite Physical-Layer Authentication

arXiv:2608.20240v1 Announce Type: new Abstract: X-band SAR satellites (8-12 GHz) play a critical role in disaster response, environmental monitoring, and military intelligence. Yet, they lack robust p

Reading Between the Pixels: An Inscriptive Jailbreak Attack on Text-to-Image Models

arXiv:2604.05853v3 Announce Type: replace Abstract: Modern text-to-image (T2I) models can now render legible, paragraph-length text, enabling a fundamentally new class of misuse. We identify and forma

safetyarxiv-cs-cv

Rethinking Patch Based Multivariate Time Series Forecasting with Semantic Structured Partitioning

arXiv:2608.19966v1 Announce Type: new Abstract: Multivariate time series forecasting (MTSF) is a fundamental task in many real world applications. Existing patch based forecasting methods generally fa

applicationsarxiv-cs-ai

RoMAN-Flow: Taming Autoregressive Normalizing Flows for Offline Reinforcement Learning in Robotic Manipulation

arXiv:2608.20208v1 Announce Type: new Abstract: Offline reinforcement learning improves robotic policies using previously collected data without further environment interaction. Yet prevalent diffusio

safetyarxiv-cs-cv

Hardware

S^2GS: Structured Sparse Gaussian Streaming for Efficient Free-Viewpoint Video Reconstruction on Edge-IoT Devices

arXiv:2608.19639v1 Announce Type: new Abstract: Streaming reconstruction of Free-Viewpoint Videos (FVVs) supports immersive Internet of Things (IoT) services, such as telepresence and digital twin vis

hardwarearxiv-cs-cv

SABET-QA: Temporal Knowledge Graph Question Answering

arXiv:2608.20083v1 Announce Type: cross Abstract: Question Answering over Temporal Knowledge Graphs (TKGQA) requires reasoning over time-sensitive facts, yet existing embedding-based methods struggle

SafeBranch: Branch-Pair Safety Alignment for Embodied Agents

arXiv:2608.19729v1 Announce Type: new Abstract: Vision-language-model-based embodied agents can complete instructed tasks but often violate safety constraints in the process, a problem recently framed

SAPO: Single-Rollout Autoregressive Policy Optimization for Agentic Reinforcement Learning

arXiv:2608.19842v1 Announce Type: new Abstract: Agentic reinforcement learning (RL) has become a critical stage in the post-training of large language models. Existing critic-free, group-relative meth

Scaffolding Minds: Optimizing Latent Visual Target Representations for Multimodal Reasoning

arXiv:2608.19669v1 Announce Type: new Abstract: Latent reasoning has advanced multimodal reasoning through a two-stage training paradigm: (1) a helper image is encoded into latent tokens to teach visu

safetyarxiv-cs-cv

Scale-Separated Conditioning for Style-Encoder-Free Diffusion Stylization

model-releasesarxiv-cs-ai

arXiv:2608.19719v1 Announce Type: cross Abstract: Reference-based diffusion stylization requires separating target geometry from transferable appearance. Existing tuning-based methods often rely on al

SCAPE: Scenario-Conditioned Simulation-Augmented Policy Evaluation

arXiv:2608.19425v1 Announce Type: cross Abstract: Reliable performance evaluation is a central bottleneck for deploying robot-learning policies in real-world conditions. Real-world testing is faithful

Silhouette-based Gait Foundation Model

arXiv:2512.00691v2 Announce Type: replace Abstract: Gait patterns play a critical role in human identification and healthcare analytics, yet current progress remains constrained by small, narrowly des

applicationsarxiv-cs-cv

Tools

Simulation: the new Scaling Law — Joon Sung Park, Simile AI

Simile AI’s CEO Joon Sung Park describes how the company moved from the 2024 “Summer of Simulative AI” and its landmark *Generative Agents* paper to building digital twins that predict individual and

toolslatent-space

skchange: Fast and Flexible Algorithms for Changepoint Detection

arXiv:2608.19767v1 Announce Type: cross Abstract: Skchange is an open-source Python library for detecting structural changes in time series. It implements modern change detection algorithms within a u

tutorialsarxiv-cs-lg

Local Ai

SPyCE: Skill-Policy Co-evolution for Multimodal Agents

arXiv:2607.13854v2 Announce Type: replace Abstract: Multimodal agents that think with images iteratively manipulate visual evidence and invoke tools across many steps. Existing reinforcement learning

local-aiarxiv-cs-cl

Teacher-free Latent Self-distillation and Class-separable Representations for Lightweight IoT Attack Detection

arXiv:2403.15509v3 Announce Type: replace-cross Abstract: Knowledge distillation (KD) has been widely used to improve lightweight AI models by transferring soft-label knowledge from a large teacher mo

applicationsarxiv-cs-ai

TempJail: Temporal Jailbreak Attack against Large Vision-Language Models via Subtitle Scheduling

model-releasesarxiv-cs-ai

arXiv:2608.19737v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) have achieved remarkable progress in video understanding and reasoning. Despite extensive studies on text- and im