Search: “models”

Compositional Policy Violations: When Step-Level Compliance Fails In Agentic AI Workflows

arXiv:2609.18820v1 Announce Type: new Abstract: Agentic workflows now make consequential decisions in regulated settings, and the governance placed around them is almost entirely step-scoped: input-ou

safetyarxiv-cs-ai

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Comprehensive reconstruction of collider events with hypergraph representation learning and graph-conditioned diffusion

DGX agent

arXiv:2609.18928v1 Announce Type: cross Abstract: In particle collider experiments, event reconstruction is the task of inferring the kinematics of short-lived particles produced in the hard scatter f

researcharxiv-cs-lg

17 Sept 2026

Compressive sensing inspired self-supervised single-pixel imaging

arXiv:2603.29732v2 Announce Type: replace Abstract: Single-pixel imaging (SPI) is a promising imaging modality with distinctive advantages in strongly perturbed environments. Existing SPI methods lack

local-aiarxiv-cs-cv

Copy What Is Seen, Generate What Is Not: Training-Free Anomaly-Aware Video Restoration

arXiv:2609.18836v1 Announce Type: new Abstract: A surveillance system that detects an anomaly often has to repair the footage as well, yet the two tasks are studied in isolation: training-free anomaly

Decoder-Agnostic Token Merging for Vision Transformers: A Systematic Study of G2TM

arXiv:2609.18279v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved state-of-the-art performance across a range of computer vision tasks, mainly thanks to the self-attention mecha

Diff-SPORT: Diffusion-based Sensor Placement Optimization and Reconstruction of Turbulent flows in urban environments

arXiv:2506.00214v2 Announce Type: replace-cross Abstract: Rapid urbanization demands efficient monitoring of turbulent wind and pollutant dispersion, yet existing reconstruction and sensor placement s

Divide and Conquer: Mixture-of-Bottleneck Experts in Informative Ordinal Space for Video-based Multimodal Sentiment Analysis

arXiv:2609.18470v1 Announce Type: cross Abstract: Video-based Multimodal sentiment analysis (MSA) must handle information from text, audio, and image sequence in human speaking videos, yet current met

researcharxiv-cs-cl

Enhancing Physics-Informed Neural Networks with Domain-aware Fourier Features: Towards Improved Performance and Interpretable Results

arXiv:2603.02948v2 Announce Type: replace-cross Abstract: Physics-Informed Neural Networks (PINNs) incorporate physics into neural networks by embedding partial differential equations (PDEs) into thei

Evolution of US Oral Political Language

arXiv:2609.17755v1 Announce Type: cross Abstract: The analysis of US political language is usually based on the written form (e.g. presidential addresses) or posts broadcasted on various social networ

Evolving Error States: Failure-Aware Progressive Repair for Ultrasound Lesion Segmentation

arXiv:2609.18256v1 Announce Type: new Abstract: Reliability under sparse and heterogeneous failures remains a fundamental challenge for medical image segmentation. High average accuracy can conceal a

Agents

EvoUndo: Recoverability-Constrained Self-Evolution for LLM Agent Harnesses

arXiv:2608.28363v2 Announce Type: replace Abstract: LLM agents increasingly modify their own prompts, tools, middleware, resources, and execution harnesses at runtime. Such self-evolution can improve

agentsarxiv-cs-ai

Exact semantic readout from compressed vector representations

arXiv:2609.18047v1 Announce Type: new Abstract: We characterize when compressed vector representations admit exact linear or affine readouts of a finite lexicon's truth conditions: one fixed map per p

researcharxiv-cs-cl

Exponential Hardness of Off-Policy Evaluation under History-Dependent Logging

arXiv:2609.19135v1 Announce Type: new Abstract: Can a logged dataset visit every hidden state frequently and still be exponentially uninformative about a target policy's value? We show that it can whe

safetyarxiv-cs-lg

Hardware

FAME: An FPGA-Based Platform for Approximate Multipliers Evaluation with Pattern-Guided DNN Retraining

arXiv:2609.17730v1 Announce Type: cross Abstract: Approximate multipliers can reduce hardware area and energy consumption in Deep Neural Network (DNN) inference; however, they introduce computational

hardwarearxiv-cs-lg

Hardware

Fathom: Per-Query Read Depth for Sparse Decoding over Offloaded KV Caches

arXiv:2609.17652v1 Announce Type: cross Abstract: When agentic sessions run to a million tokens with many sessions resident at once, the KV cache and the index that ranks it live in host memory, and t

hardwarearxiv-cs-cl

Human-Centric Grasp State Assessment: Toward Transferring Subjective Evaluation to Robots

arXiv:2609.17540v1 Announce Type: new Abstract: We propose a framework that transfers tacit human subjective criteria to robotic systems for the appropriate grasping of deformable objects. Achieving s

researcharxiv-cs-ro

Human Resilience in the AI Era -- What Machines Can't Replace

arXiv:2510.25218v2 Announce Type: replace-cross Abstract: AI is changing work and decision making faster than many institutions can adapt their operating practices. We argue that this adaptation gap m

Hyperbolic Graph Representation Learning for Differential Diagnosis on Biomedical Knowledge Graphs

arXiv:2609.18481v1 Announce Type: new Abstract: Biomedical knowledge graphs combine ontology-derived hierarchies with transversal associations among heterogeneous entities such as phenotypes, diseases

Is Luke the Author of a Gospel and the Acts of the Apostles?

arXiv:2609.17762v1 Announce Type: cross Abstract: According to Christian tradition, Luke is credited with authoring a Gospel and the Acts of the Apostles, even if his name does not appear in either bo

Tutorials

Machine learning kinetics from molecular dynamics data

arXiv:2609.17736v1 Announce Type: cross Abstract: Most molecular transitions occur on timescales far beyond direct molecular dynamics simulations. The committor, the probability that a configuration r

tutorialsarxiv-cs-lg

Making AI-Assisted Claims Independently Challengeable: Publication Authority and a Protocol for Falsifiable Publication Records

arXiv:2609.17631v1 Announce Type: new Abstract: AI-assisted claims can appear authoritative when evidence, analysis, human authorization, presentation, and correction history refer to different states

local-aiarxiv-cs-ai

MI-DETR: A Strong Baseline for Moving Infrared Small Target Detection with Motion Integration

arXiv:2603.05071v2 Announce Type: replace Abstract: Detecting moving infrared small targets is challenging because tiny, low-contrast targets occupy few pixels and are easily obscured by dynamic backg

MINT: Multimodal Imaging-to-Speech Knowledge Transfer for Early Alzheimer's Screening

arXiv:2602.23994v2 Announce Type: replace-cross Abstract: Alzheimer's disease is a progressive neurodegenerative disorder in which mild cognitive impairment (MCI) precedes dementia. Structural MRI pro

Online Robust Reinforcement Learning Through Monte-Carlo Planning

arXiv:2609.18599v1 Announce Type: cross Abstract: Monte Carlo Tree Search (MCTS) is a powerful framework for solving complex decision-making problems, yet it often relies on the assumption that the si

PACT-WAM: Predicting Actions and Visual Foresight with Compact Temporal Encoding for Robot Manipulation

arXiv:2602.15882v2 Announce Type: replace-cross Abstract: Robot manipulation uses temporal context to select actions and visual foresight to assess their consequences, yet dense representations of pas

Prepared Or Unprepared? Evaluating Healthcare Workforce Readiness for Clinical Adoption of Artificial Intelligence in Nigeria

arXiv:2609.19096v1 Announce Type: cross Abstract: Artificial intelligence (AI) is increasingly integrated into healthcare systems worldwide, yet its successful clinical adoption depends critically on

Probabilistic Linear Explanations

arXiv:2609.19077v1 Announce Type: cross Abstract: Formal explainability provides mathematically grounded justifications for individual predictions. However, abductive explanations often exceed human c

Q-BIOLAT: Binary Latent Protein Fitness Landscapes for QUBO-Based Optimization

arXiv:2603.27526v2 Announce Type: replace Abstract: Protein fitness optimization is a discrete search problem, and the representation used for prediction also determines the neighborhood graph travers

RankGround: Efficient High-Resolution GUI Grounding via Lightweight Reranker-Guided Crop Selection

arXiv:2609.18690v1 Announce Type: cross Abstract: Graphical User Interface (GUI) grounding is a fundamental perception task for multimodal agents, enabling them to interpret natural language instructi

local-aiarxiv-cs-cl

Reaching Every Position Without Searching: Rotating Sparse Wiring on the Hypercube as a Substitute for Attention

arXiv:2609.18145v1 Announce Type: new Abstract: Attention pays, at every layer and for every input, the cost of searching for whom to connect. We ask how far one can get with wiring that is fixed, spa

Scalable Music Cover Retrieval Using Lyrics-Aligned Audio Embeddings

arXiv:2601.11262v2 Announce Type: replace-cross Abstract: Music Cover Retrieval, also known as Version Identification, aims to recognize distinct renditions of the same underlying musical work, a task

Scaling Articulated Rationales for MLLM-based Recommendation

arXiv:2609.17639v1 Announce Type: cross Abstract: Modern recommendation systems largely infer user preferences from implicit behaviors such as clicks, watch time, and negative feedback, but these sign

SEAM: Submap-Anchored Evidence for Lifelong LiDAR Mapping under Trajectory Deformation

arXiv:2609.18819v1 Announce Type: new Abstract: We propose SEAM, a LiDAR-based lifelong mapping framework. Instead of relying on a single anchor spanning the entire session, SEAM generates evidence ba

safetyarxiv-cs-ro

Semantic CSI Feedback for Beam Selection: When Task-Aware Embeddings from Sparse Pilots Outperform Full-Bandwidth Reconstruction

arXiv:2609.18368v1 Announce Type: cross Abstract: Classical CSI feedback in FDD massive MIMO transmits a compressed reconstruction of the channel, optimizing fidelity to the original signal regardless

STRADAViT: Self-Supervised Domain Adaptation of Vision Transformer Backbones for Radio Astronomy

arXiv:2603.29660v4 Announce Type: replace-cross Abstract: Next-generation radio astronomy surveys are delivering millions of resolved sources, yet scalable morphology analysis remains difficult across

SVMemAgent: A Streaming Video Memory Agent for Query-Agnostic Online Frame Selection

arXiv:2609.18540v1 Announce Type: new Abstract: Most keyframe selection studies focus on offline settings, assuming access to the full video and query in advance. In contrast, real-world streaming sce

safetyarxiv-cs-cv

TalkMatrix: Generating Character Dialogue that is Both Consistent and Diverse

arXiv:2609.19022v1 Announce Type: cross Abstract: Candidate-based decoding typically selects a completion for each prompt independently, but many applications require a collection of outputs that sati

local-aiarxiv-cs-ai

The Uneven Impact of Generative AI on Student Learning: Examining the Roles of Reliance, Evaluation Literacy, and Course Policy in AI-related Courses

arXiv:2609.18676v1 Announce Type: new Abstract: Generative artificial intelligence (GenAI) is changing how students learn, yet the roles of course context, cognitive reliance, evaluation literacy, and

safetyarxiv-cs-ai

Towards Generalizable Deepfake Detection via Real Distribution Bias Correction

arXiv:2603.14005v2 Announce Type: replace Abstract: To generalize deepfake detectors to future unseen forgeries, most existing methods attempt to simulate the dynamically evolving forgery types using

safetyarxiv-cs-cv

UMI-Bridge: Action-Anchored Latent Alignment across Human and Robot Manipulation Data

arXiv:2609.18232v1 Announce Type: new Abstract: Real-robot demonstrations are limited, motivating the use of human manipulation data collected without robots, including egocentric videos and handheld

safetyarxiv-cs-ro

Understanding Dynamic Scenes at Gigapixel Scale: Wide-Area Spatio-Temporal Perception from UAVs

arXiv:2609.18210v1 Announce Type: new Abstract: UAV-borne imaging has advanced from megapixel to gigapixel sensors, shifting aerial perception from recognizing individual targets to understanding enti

VLM-MPPI: Grounding Natural Language in Behaviorally Diverse Trajectories for Aerial Navigation

arXiv:2609.18451v1 Announce Type: new Abstract: We present a hierarchical UAV navigation framework that aligns natural-language intent with dynamically feasible flight behaviors in cluttered indoor en

safetyarxiv-cs-ro

Tutorials

What You Can't See Is Still What You Learn: A Preregistered Sixty-Society Confirmation That Evidence Masking Drives Compositional Generalization

arXiv:2609.17637v1 Announce Type: new Abstract: Restricting what a module can read may improve what a system learns to compute. We test this in a preregistered confirmation with sixty four-cell system

tutorialsarxiv-cs-ai

When Is Graph Structure Worth Its Cost? The Case for Structure Pricing in Retrieval-Augmented Generation

arXiv:2609.18099v1 Announce Type: new Abstract: Graph-based retrieval-augmented generation (RAG) can help answer questions that require information from many documents. However, building a graph often

A Cyber Range Evaluation of Autonomous Network Incident Response Agents

arXiv:2609.16541v1 Announce Type: cross Abstract: We test the performance of agents for automated network intrusion response in a cyber range intended for human operator training. The range implements

safetyarxiv-cs-ai

A Systematic Evaluation of Machine Learning Methods for Fault Detection and Line Identification in Electrical Power Grids

arXiv:2609.16744v1 Announce Type: new Abstract: The integration of renewable energy sources into the electrical grid introduces complex challenges in fault detection and coordination of grid recovery

safetyarxiv-cs-lg

AI Policies: Help or Hindrance? A Software Developer's Perspective

arXiv:2609.16496v1 Announce Type: cross Abstract: AI policies introduced by software organisations to mitigate LLM-related risks such as sensitive information leaks and unauthorised usage are not usef

Amortized Probabilistic Retrieval of Atmospheric CO2 from OCO-2 Spectra Using Deep Learning with Laplace Approximations and Normalizing Flows

arXiv:2606.17413v2 Announce Type: replace Abstract: Space-based monitoring of atmospheric carbon dioxide (CO_2) constrains the global carbon budget. NASA's Orbiting Carbon Observatory-2 (OCO-2) estima