Search: “models”

FMI_SU_Yotkova_Kastreva at SemEval-2026 Task 13: Lightweight Detection of LLM-Generated Code via Stylometric Signals

arXiv:2605.04157v1 Announce Type: new Abstract: SemEval-2026 Task 13 investigates machine-generated code detection across multiple programming languages and application scenarios, asking participating

researcharxiv-cs-cl

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Agents

GeoDecider: A Coarse-to-Fine Agentic Workflow for Explainable Lithology Classification

DGX agent

arXiv:2605.03383v1 Announce Type: new Abstract: Lithology classification aims to infer subsurface rock types from well-logging signals, supporting downstream applications like reservoir characterizati

agentsarxiv-cs-ai

7 May 2026

Gradient Flow Structure and Quantitative Dynamics of Multi-Head Self-Attention

arXiv:2605.04279v1 Announce Type: new Abstract: Transformer self-attention can be interpreted as a gradient flow on the unit sphere, in which tokens evolve under softmax interaction potentials and ten

applicationsarxiv-cs-lg

GraphPI: Efficient Protein Inference with Graph Neural Networks

arXiv:2605.04376v1 Announce Type: new Abstract: The integration of deep learning approaches in biomedical research has been transformative, enabling breakthroughs in various applications. Despite thes

Height-Guided Projection Reparameterization for Camera-LiDAR Occupancy

arXiv:2605.05072v1 Announce Type: new Abstract: 3D occupancy prediction aims to infer dense, voxel-wise scene semantics from sensor observations, where the 2D-to-3D view transformation serves as a cru

applicationsarxiv-cs-cv

Hermes Agent just keeps getting better.

Nous Research announced improvements or updates to their Hermes Agent system, highlighting enhanced capabilities or performance. The post was shared on X (formerly Twitter), suggesting it covers recen

agentsnous-research--x

Hierarchical Support Vector State Partitioning for Distilling Black Box Reinforcement Learning Policies

arXiv:2605.04254v1 Announce Type: new Abstract: We introduce State Vector Space Partitioning (SVSP), a novel method to mimic a black box reinforcement learning policy using a set of human-interpretabl

.@huggingface's agentic robotics app store for Reachy Mini is a big step toward more accessible physical AI. 🙌 Excited to see NVIDIA Isaac …

.@huggingface's agentic robotics app store for Reachy Mini is a big step toward more accessible physical AI. 🙌 Excited to see NVIDIA Isaac GR00T N integrated with Hugging Face LeRobot, helping develop

hardwareclem-delangue--x

Human-AI Co-Mentorship in Project-Based Learning: A Case Study in Financial Forecasting

arXiv:2605.05144v1 Announce Type: new Abstract: This paper reflects on a AI research project carried out by a team of high-school and early-undergraduate students under the mentorship of graduate rese

applicationsarxiv-cs-lg

Improving Bias Correction Standards by Quantifying its Effects on Treatment Outcomes

arXiv:2407.14861v3 Announce Type: replace-cross Abstract: With the growing access to administrative health databases, retrospective studies have become crucial evidence for medical treatments. Yet, no

Improving Medical VQA through Trajectory-Aware Process Supervision

arXiv:2605.04064v1 Announce Type: cross Abstract: Reasoning capabilities are crucial for reliable medical visual question answering (VQA); however, existing datasets rarely include reasoning explanati

safetyarxiv-cs-cv

InterFuserDVS: Event-Enhanced Sensor Fusion for Safe RL-Based Decision Making

arXiv:2605.04355v1 Announce Type: new Abstract: Autonomous driving systems rely heavily on robust sensor fusion to perceive complex envi- ronments. Traditional setups using RGB cameras and LiDAR often

safetyarxiv-cs-cv

InterMesh: Explicit Interaction-Aware End-to-End Multi-Person Human Mesh Recovery

arXiv:2605.04554v1 Announce Type: new Abstract: Humans constantly interact with their surroundings. Existing end-to-end multi-person human mesh recovery methods, typically based on the DETR framework,

ITBoost: Information-Theoretic Trust for Robust Boosting

arXiv:2605.04671v1 Announce Type: new Abstract: Gradient boosting remains a strong and widely used method for tabular data learning, but its performance often degrades when training labels are noisy.

Kinematic Discriminants of Deceleration Behavior Modes in Car-Following: Evidence from NGSIM Trajectory Data

arXiv:2605.05050v1 Announce Type: cross Abstract: Gap-closing rate and visual looming swap discriminative dominance depending on deceleration intensity - a finding that reconciles a long-standing conf

agentsarxiv-cs-lg

Layerwise LQR for Geometry-Aware Optimization of Deep Networks

arXiv:2605.04230v1 Announce Type: new Abstract: Geometry-aware optimizers such as Newton and natural gradient can improve conditioning in deep learning, but scalable variants such as K-FAC, Shampoo, a

Tutorials

LEGO: LoRA-Enabled Generator-Oriented Framework for Synthetic Image Detection

arXiv:2605.04445v1 Announce Type: new Abstract: The rapid advancement of generative technologies has made synthetic images nearly indistinguishable from real ones, thereby creating an urgent need for

tutorialsarxiv-cs-cv

Lightning Unified Video Editing via In-Context Sparse Attention

arXiv:2605.04569v1 Announce Type: new Abstract: Video editing has evolved toward In-Context Learning (ICL) paradigms, yet the resulting quadratic attention costs create a critical computational bottle

LTGS: Long-Term Gaussian Scene Chronology From Sparse View Updates

arXiv:2510.09881v3 Announce Type: replace Abstract: Recent advances in novel-view synthesis can create the photo-realistic visualization of real-world environments from conventional camera captures. H

applicationsarxiv-cs-cv

MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion Attacks

arXiv:2312.06423v3 Announce Type: replace-cross Abstract: Machine learning (ML) has gained significant adoption in Android malware detection to address the escalating threats posed by the rapid prolif

Massively Parallel Exact Inference for Hawkes Processes

arXiv:2604.01342v2 Announce Type: replace Abstract: Multivariate Hawkes processes are a widely used class of self-exciting point processes, but maximum likelihood estimation naively scales as O(N^2) i

hardwarearxiv-cs-lg

Material Database Agent: A Multimodal Agentic Framework for Scientific Literature Mining

arXiv:2605.04278v1 Announce Type: new Abstract: Materials science workflows rely on structured and unstructured data from the vast body of available scientific literature. However, most of the experim

agentsarxiv-cs-cl

MenuNet: A Strategy-Proof Mechanism for Matching Markets

arXiv:2605.03216v1 Announce Type: cross Abstract: Strategy-proofness is a fundamental desideratum in mechanism design, ensuring truthful reporting and robust participation. Stability is another centra

safetyarxiv-cs-ai

Morphology-Guided Cross-Task Coupling for Joint Building Height and Footprint Estimation

arXiv:2605.04731v1 Announce Type: new Abstract: Building height (BH) and building footprint (BF) jointly describe the vertical and horizontal extent of the built environment and are required inputs fo

Industry

Mozilla says 271 vulnerabilities found by Mythos have 'almost no false positives'

Mozilla ran an agentic harness powered by Claude Mythos Preview across Firefox's source code, identifying 271 security bugs fixed in Firefox 150 . The breakthrough was achieved through improvements in

industryars-technica

Multi-Scale Wavelet Transformers for Operator Learning of Dynamical Systems

arXiv:2602.01486v2 Announce Type: replace Abstract: Recent years have seen a surge in data-driven surrogates for dynamical systems that can be orders of magnitude faster than numerical solvers. Howeve

New Bigtable in-memory tier for sub-millisecond read latency

In the high-stakes world of digital infrastructure, speed isn't just a metric — it’s currency. At Google Cloud Next ‘26 we announced the Bigtable in-memory tier, a breakthrough for our fully managed c

safetygoogle-cloud-ai

On the Architectural Complexity of Neural Networks

arXiv:2605.04325v1 Announce Type: new Abstract: We introduce a unified theoretical framework for the rigorous analysis and systematic construction of deep neural networks (DNNs). This framework addres

Optimize-at-Capture: Highly-adaptive Exposure Controlling for In-Vehicle Non-contact Heart-rate Monitoring

arXiv:2605.04397v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) holds great promise for continuous heart-rate monitoring of drivers in intelligent vehicles. However, its performance

Pack it in: Packing into Partially Filled Containers Through Contact

arXiv:2602.12095v3 Announce Type: replace Abstract: The automation of warehouse operations is crucial for improving productivity and reducing human exposure to hazardous environments. One operation fr

researcharxiv-cs-ro

PAIR-CI: Calibrated Conditional Independence Testing for Causal Discovery with Incomplete Data

arXiv:2605.04838v1 Announce Type: cross Abstract: The standard constraint-based paradigm for causal discovery with incomplete data -- impute first, test second -- is frequently miscalibrated: any cons

Parloa builds service agents customers want to talk to

Parloa, an AI company, has developed service agents powered by OpenAI's technology that are designed to provide natural, conversational customer interactions. These agents aim to improve customer expe

applicationsopenai

PhysForge: Generating Physics-Grounded 3D Assets for Interactive Virtual World

arXiv:2605.05163v1 Announce Type: new Abstract: Synthesizing physics-grounded 3D assets is a critical bottleneck for interactive virtual worlds and embodied AI. Existing methods predominantly focus on

Physical Adversarial Clothing Evades Visible-Thermal Detectors via Non-Overlapping RGB-T Pattern

arXiv:2605.04675v1 Announce Type: new Abstract: Visible-thermal (RGB-T) object detection is a crucial technology for applications such as autonomous driving, where multimodal fusion enhances performan

agentsarxiv-cs-cv

Predictive and Prescriptive AI toward Optimizing Wildfire Suppression

arXiv:2605.04510v1 Announce Type: cross Abstract: Intense wildfire seasons require critical prioritization decisions to allocate scarce suppression resources over a dispersed geographical area. This p

applicationsarxiv-cs-lg

Programmatic Context Augmentation for LLM-based Symbolic Regression

arXiv:2605.03101v1 Announce Type: new Abstract: Symbolic regression (SR), the task of discovering mathematical expressions that best describe a given dataset, remains a fundamental challenge in scient

researcharxiv-cs-ai

Quantization and Fast Inference (MEAP) - How much performance are you actually getting from quantization in production? [D]

applicationsr-machinelearning

This discussion examines the practical performance gains of quantization techniques when deployed in production environments, particularly addressing whether theoretical speedups translate to real-wor

QUIVER: Cost-Aware Adaptive Preference Querying in Surrogate-Assisted Evolutionary Multi-Objective Optimization

arXiv:2605.04267v1 Announce Type: new Abstract: Interactive multi-objective optimization systems face a budget allocation dilemma: one can spend resources on expensive objective evaluations or on elic

RouteFormer: A Transformer-Based Routing Framework for Autonomous Vehicles

arXiv:2504.05407v2 Announce Type: replace-cross Abstract: Autonomous surveillance missions in Internet of Things (IoT) networks often involve solving NP-hard combinatorial optimization problems to ens

agentsarxiv-cs-lg

SCOUT: Active Information Foraging for Long-Text Understanding with Decoupled Epistemic States

arXiv:2605.04496v1 Announce Type: new Abstract: Long-Text Understanding (LTU) at million-token scale requires balancing reasoning fidelity with computational efficiency. Frontier long-context LLMs can

researcharxiv-cs-cl

ScriptHOI: Learning Scripted State Transitions for Open-Vocabulary Human-Object Interaction Detection

arXiv:2605.05057v1 Announce Type: new Abstract: Open-vocabulary human-object interaction (HOI) detection requires recognizing interaction phrases that may not appear as annotated categories during tra

Secure short-term GPU capacity for ML workloads with EC2 Capacity Blocks for ML and SageMaker training plans

In this post, you will learn how to secure reserved GPU capacity for short-term workloads using Amazon Elastic Compute Cloud (Amazon EC2) Capacity Blocks for ML and Amazon SageMaker training plans. Th

hardwareaws-ml-blog

Seems like a massively underinvested area in the “pivot to enterprise.” The fact that the Labs are building their own deployment consultanci…

applicationsethan-mollick--x

Seems like a massively underinvested area in the “pivot to enterprise.” The fact that the Labs are building their own deployment consultancies (which will take a long time) suggests a failure of imagi

SemiConLens: Visual Analytics for 2D Semiconductor Discovery

arXiv:2605.04067v1 Announce Type: cross Abstract: The past few years have witnessed vibrant efforts in discovering new two-dimensional (2D) semiconductor materials from both academia and the industry,

hardwarearxiv-cs-lg

Sentiment Analysis and Customer Satisfaction Prediction on E-Commerce Platforms Based on YouTube Comments Using the XGBoost Algorithm

arXiv:2605.04887v1 Announce Type: new Abstract: The exponential expansion of digital commerce in Indonesia has significantly shifted consumer interactions toward video-centric social networks, particu

researcharxiv-cs-cl

Sequential Strategic Classification with Multi-Stage Selective Classifiers

arXiv:2605.04202v1 Announce Type: new Abstract: Strategic classification studies the problem where self-interested individuals or agents manipulate their response to obtain favorable decision outcomes

Software Engineering for Self-Adaptive Robotics: A Research Agenda

arXiv:2505.19629v3 Announce Type: replace-cross Abstract: Self-adaptive robotic systems operate autonomously in dynamic and uncertain environments, requiring robust real-time monitoring and adaptive b

safetyarxiv-cs-ro

Tutorials

Stream-T1: Test-Time Scaling for Streaming Video Generation

arXiv:2605.04461v1 Announce Type: new Abstract: While Test-Time Scaling (TTS) offers a promising direction to enhance video generation without the surging costs of training, current test-time video ge

tutorialsarxiv-cs-cv