Search: “papers”

A Hypertoroidal Covering for Perfect Color Equivariance

arXiv:2603.04256v3 Announce Type: replace Abstract: When the color distribution of input images changes at inference, the performance of conventional neural network architectures drops considerably. A

researcharxiv-cs-cv

A Kinetic Theory of Encounter-Based Information Propagation in Multi-Robot Systems

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DGX agent

arXiv:2606.02296v1 Announce Type: new Abstract: Multi-robot systems cannot assume persistent network connectivity. We study this problem through target tracking, where performance depends on how quick

researcharxiv-cs-ro

2 Jun 2026

A Lightweight Hybrid MLP-Based Framework for Real-Time Phishing URL Detection Using Structural URL Features

arXiv:2606.00889v1 Announce Type: cross Abstract: Phishing attacks remain a major cybersecurity threat, exploiting deceptive URLs to steal sensitive user information. Traditional blacklist and rule-ba

researcharxiv-cs-lg

A Multiscale Network with Supervised Contrastive Learning for Real-Time Facial Emotion Recognition

arXiv:2606.01069v1 Announce Type: new Abstract: Real-time emotion recognition from facial expressions is a challenging task, particularly in video-based scenarios where multiple emotional states may o

researcharxiv-cs-cv

A Theoretical Framework for Self-Play Theorem Proving Algorithms

arXiv:2606.01861v1 Announce Type: new Abstract: Self-play, a type of training algorithm that enables a model to self-improve, has recently shown promising empirical results in the context of formal th

researcharxiv-cs-lg

AblationBench: Evaluating Automated Planning of Ablations in Empirical AI Research

arXiv:2507.08038v3 Announce Type: replace-cross Abstract: Language model agents are increasingly used to automate scientific research, yet evaluating their scientific contributions remains a challenge

Acting with AI: An Interaction-Based Framework for Agentic Tort Liability

arXiv:2606.00518v1 Announce Type: new Abstract: Agentic AI systems can plan over multiple steps, use tools, and execute tasks over time. When such systems cause harm, tort law struggles to allocate re

Adversarial Attacks on Robot Localization Systems via Deep Feature Perturbation

arXiv:2606.01892v1 Announce Type: new Abstract: Robot localization systems are critical for autonomous navigation and safety. Adversarial perturbations can mislead these systems, resulting in mislocal

safetyarxiv-cs-cv

Local Ai

AFUN: Towards an Affordance Foundation Model for Functionality Understanding

arXiv:2606.02551v1 Announce Type: cross Abstract: Affordance understanding bridges visual perception and physical action, serving as an explainable interface for robot manipulation in open and unstruc

local-aiarxiv-cs-cv

Agent Operating Systems (AOS): Integrating Agentic Control Planes into, and Beyond, Traditional Operating Systems

arXiv:2606.01508v1 Announce Type: cross Abstract: Traditional operating systems were designed around deterministic programs, explicit control flow, and human initiated workflows. Their core abstractio

Agent-R1: A Unified and Modular Framework for Agentic Reinforcement Learning

arXiv:2511.14460v2 Announce Type: replace Abstract: Large language models (LLMs) have rapidly evolved from single-turn text generators into the foundation of increasingly capable agents. As these agen

agentsarxiv-cs-cl

AGENTCL: Toward Rigorous Evaluation of Continual Learning in Language Agents

arXiv:2606.02461v1 Announce Type: new Abstract: Language agents spend substantial inference time solving individual tasks, yet the experience acquired in one episode is often underutilized in future e

Agentic-J: An AI Agent for Biological Microscopy Image Analysis

arXiv:2606.02080v1 Announce Type: cross Abstract: Biological image analysis increasingly demands integration across heterogeneous tools, programming environments, and domain knowledge that few researc

AgentxGCore: Agentic AI for Next-Generation Mobile Core Network

arXiv:2606.00417v1 Announce Type: cross Abstract: To meet the stringent requirements of emerging applications and the increasingly complex network management and operation, the Next Generation Mobile

Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why

arXiv:2606.00093v1 Announce Type: new Abstract: Validating an LLM judge against human annotations usually means reporting several agreement statistics: accuracy, precision, recall, F_1, Cohen's kappa,

Algebraic anti-unification

arXiv:2407.15510v2 Announce Type: replace Abstract: Abstraction is key to human and artificial intelligence as it allows one to identify common structure in otherwise distinct objects or situations. A

Local Ai

{alpha}Depth: Learning Single-Pass Soft Boundary Decomposition for Stereo Conversion

arXiv:2606.00386v1 Announce Type: new Abstract: Accurately modeling soft boundaries, e.g., hair and defocus blur, is a fundamental challenge in stereo conversion due to the ambiguous blending of foreg

local-aiarxiv-cs-cv

An NLP-Driven Framework for Curriculum-Labor Market Alignment: Schema-Constrained LLM Extraction, ESCO-Anchored Semantic Matching, and Multi-Dimensional Gap Quantification

arXiv:2606.01982v1 Announce Type: new Abstract: Schema-constrained information extraction from diverse educational and labor-market corpora remains an open challenge in natural language processing bec

Announcing Spanner Graph algorithms: Google-grade intelligence for connected data

model-releasesgoogle-cloud-ai

At Google Cloud Next, we announced the preview of graph algorithms with Spanner Graph, bringing Google Research’s state-of-the-art graph mining capabilities natively to your database. These graph inte

ART: Attention Run-time Termination for Efficient Large Language Model Decoding

arXiv:2606.00024v1 Announce Type: new Abstract: Long-context decoding in Large Language Models (LLMs) is severely constrained by the memory bandwidth required to fetch the extensive Key-Value (KV) cac

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training

model-releasesarxiv-cs-cv

arXiv:2606.00602v1 Announce Type: new Abstract: Learning transferable and interpretable representations from medical volumetric scans remains challenging due to complex anatomical structures and weak,

Attention-guided Fine-tuning of Multimodal Large Language Models Improves Chain-of-Thought Reasoning

arXiv:2606.01558v1 Announce Type: new Abstract: The effectiveness of Chain-of-Thought (CoT) prompting in Multimodal Large Language Models (MLLMs) remains uncertain: across several visual reasoning ben

researcharxiv-cs-cv

Authenticity Debt and the Synthetic Content Threat Landscape: A Layered Framework for Trust, Provenance, and IP Governance in the Generative AI Era

arXiv:2606.00621v1 Announce Type: cross Abstract: Generative artificial intelligence has fundamentally changed how content is now produced. It has enabled how high-fidelity text, images, audio, and vi

Automated Conjecture Resolution with Formal Verification

arXiv:2604.03789v2 Announce Type: replace-cross Abstract: Recent advances in large language models have significantly improved their ability to perform mathematical reasoning, extending from elementar

Automated Essay Scoring and Language Certification: Assessing Generalizability, Agreement and Validity for French

arXiv:2606.02009v1 Announce Type: new Abstract: In Automated Essay Scoring (AES), benchmarking practices have fostered minimalist evaluation practices, in contrast with the broader-view recommendation

safetyarxiv-cs-cl

Behavior Cloning of MPC for 3-DOF Robotic Manipulators

arXiv:2606.00383v1 Announce Type: cross Abstract: While Model Predictive Control (MPC) provides strong stability and robustness, it imposes a significant computational burden on real-time systems. Thi

safetyarxiv-cs-lg

Benchmarks for Vision-Language Models in Urban Perception Should Be Reliability-Aware and Negotiated

arXiv:2606.00871v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used to generate structured descriptions of street-level imagery for tasks such as streetscape auditing

BERT4beam: Large AI Model Enabled Generalized Beamforming Optimization

arXiv:2509.11056v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) is anticipated to emerge as a pivotal enabler for the forthcoming sixth-generation (6G) wireless communication sy

researcharxiv-cs-lg

Beyond Rigid: Benchmarking Non-Rigid Video Editing

model-releasesarxiv-cs-cv

arXiv:2601.18340v2 Announce Type: replace Abstract: As video generation models are increasingly expected to manipulate physical dynamics, there is a growing need to move evaluation beyond appearance f

Beyond Static Gaussians: An Empirical Investigation of Architectural Paradigms for Dynamic 3D Scene Reconstruction

model-releasesarxiv-cs-cv

arXiv:2606.00452v1 Announce Type: new Abstract: Dynamic scene reconstruction via 3D Gaussian Splatting (3DGS) has emerged as a compelling approach for representing evolving environments, yet understan

Beyond Task Success: Behavioral and Representational Diagnostics for WAM and VLA

arXiv:2606.01095v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies and World-Action Models (WAM) represent two increasingly important paradigms for robotic manipulation. However,

Beyond the Mouth: Upper-Face Affective Cues in Audiovisual Sentence Recognition under Acoustic Uncertainty

arXiv:2606.00670v1 Announce Type: cross Abstract: Face-to-face speech comprehension is inherently multimodal, integrating acoustic signals with visible articulation, facial expression, head motion, an

Tutorials

Beyond Tool Adoption: A Practical Five-Stage Developmental Continuum for AI Literacy in Higher Education

arXiv:2606.00038v1 Announce Type: cross Abstract: Artificial intelligence (AI) literacy is increasingly recognized as a foundational competency for all university graduates. Yet students' engagement w

tutorialsarxiv-cs-ai

BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining

model-releasesarxiv-cs-lg

arXiv:2510.06048v4 Announce Type: replace Abstract: Effective data selection is essential for pretraining large language models (LLMs), enhancing efficiency and improving generalization to downstream

BOUTEF: A Multilingual Corpus for FakeNews in North Africa -- Language as a Weapon

arXiv:2606.00193v1 Announce Type: new Abstract: The rapid spread of fake news on social media has become a major challenge, particularly in multilingual and under-resourced contexts such as North Afri

Brain-Atlas-Guided Generative Counterfactual Attention for Explainable Cognitive Decline Diagnosis Using Multimodal Connectomes

arXiv:2606.01237v1 Announce Type: new Abstract: Mild cognitive impairment (MCI) and subjective cognitive decline (SCD) are closely associated with the early Alzheimer's disease continuum, where accura

Breaking the Reversal Curse in Autoregressive Language Models via Identity Bridge

arXiv:2602.02470v2 Announce Type: replace Abstract: Autoregressive large language models (LLMs) have achieved remarkable success in many complex tasks, yet they can still fail in very simple logical r

Tutorials

Bridging the Gap: Transfer Learning from English PLMs to Malaysian English

arXiv:2407.01374v2 Announce Type: replace Abstract: Malaysian English is a low resource creole language, where it carries the elements of Malay, Chinese, and Tamil languages, in addition to Standard E

tutorialsarxiv-cs-cl

Bridging the Last Mile of Time Series Forecasting with LLM Agents

arXiv:2606.02497v1 Announce Type: new Abstract: Time series forecasting has advanced rapidly, especially with the emergence of foundation models that show strong zero-shot performance on numerical ext

Tutorials

C-LEAD: Contrastive Learning for Enhanced Adversarial Defense

arXiv:2510.27249v2 Announce Type: replace Abstract: Deep neural networks (DNNs) have achieved remarkable success in computer vision tasks such as image classification, segmentation, and object detecti

tutorialsarxiv-cs-cv

CEAR: Certified Ensemble Adversarial Robustness in DNNs

arXiv:2606.01437v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs) are highly susceptible to adversarial perturbations, leading to extensive research on robustness for safety-critical appli

Challenger at MultiPRIDE: Is It Hate Speech or Reclaimed?

arXiv:2606.01298v1 Announce Type: new Abstract: The spread of hate speech has become increasingly harmful in modern digital environments, particularly on social networking platforms. While recent adva

Characterization of Multi-Model Agentic AI Systems on General Tasks via Trace-Driven Simulation

arXiv:2606.01725v1 Announce Type: new Abstract: Agentic AI completes tasks through iterative planning, tool use, and reasoning based on observed outcomes. Despite its popularity, its system-level beha

Characterizing Web Search in The Age of Generative AI

arXiv:2510.11560v2 Announce Type: replace-cross Abstract: The advent of LLMs has given rise to generative search, a new search paradigm in which LLMs retrieve information from the web related to a que

CLAW: A Vision-Language-Action Framework for Weight-Aware Robotic Grasping

arXiv:2509.14143v2 Announce Type: replace Abstract: Vision-language-action (VLA) models have recently emerged as a promising paradigm for robotic control, enabling end-to-end policies that ground natu

safetyarxiv-cs-ro

Co-training with Ego-centric Video and Demonstration for Robot Navigation Task

arXiv:2606.01951v1 Announce Type: new Abstract: Vision-language-action (VLA) models are promising for diverse robotic tasks, but their performance heavily depends on large-scale high-quality training

researcharxiv-cs-ro

Code2Math: Can Your Code Agent Effectively Evolve Math Problems Through Exploration?

arXiv:2603.03202v3 Announce Type: replace Abstract: As large language models (LLMs) advance their mathematical capabilities toward the IMO and research level, the scarcity of challenging, high-quality

agentsarxiv-cs-cl

Collaborative Few-Step Distillation and Low-Bit Quantization for Wan2.2 Dual-Expert Video Diffusion Models

arXiv:2606.00658v1 Announce Type: cross Abstract: Large video diffusion models achieve strong visual quality but remain expensive to deploy because each sample requires many denoising steps and a larg