Search: “papers”

arXiv:2511.08654v2 Announce Type: replace-cross Abstract: This paper analyses AI-generated podcasts produced by Google's NotebookLM, which generates audio podcasts with two chatty AI hosts discussing

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Analogies between Transformer Layers and Power Method

DGX agent

arXiv:2605.25619v1 Announce Type: new Abstract: In the paper we show that there is an analogy between the operations occurring in a layer of a transformer (projections and layer normalizations, disreg

safetyarxiv-cs-lg

26 May 2026

ATWL: A Formal Language for Representing, Comparing, and Reusing Visual Analytics Workflows

arXiv:2605.25489v1 Announce Type: new Abstract: Visual analytics (VA) workflows are inherently complex, involving data transformation, feature engineering, visual representation, and human interpretat

Compliant Non-Prehensile Pushing Manipulation

arXiv:2605.25672v1 Announce Type: new Abstract: In this paper, we address the challenge of performing non-prehensile pushing operations with a compliant robotic manipulation system. To ensure safe ope

researcharxiv-cs-ro

Context-Instrumental Data Distillation for Kubernetes Manifest Generation: Method and Experimental Evaluation

arXiv:2605.25835v1 Announce Type: cross Abstract: This paper examines the specialization of Small Language Models (SLMs) with up to 4 billion parameters for generating artifacts in domain-specific lan

CyBOKClaw: Human-in-the-Loop CyBOK Mapping for Cybersecurity Curriculum

arXiv:2605.24663v1 Announce Type: cross Abstract: This paper presents CyBOKClaw, an interpretable human-in-the-loop retrieval framework for mapping cybersecurity keywords or phrases (KWoPs) to the Cyb

safetyarxiv-cs-ai

DeepSeekMath Meets Order Book: Group-Aware Policy Optimization for High-Frequency Directional Trading

arXiv:2605.25527v1 Announce Type: new Abstract: This paper studies reinforcement learning for high-frequency trading on limit order books by pairing an Order-Flow-based state model with policy-gradien

safetyarxiv-cs-lg

ECo-MoE: Embodiment-Conditioned Mixture of Experts Increases the Evolvability of Robots

arXiv:2605.24225v1 Announce Type: new Abstract: In this paper, we introduce a model of evolution and learning in robots that co-optimizes a distribution of latent design vectors (genotypes) and a mixt

Fine-Tuning Language Models to Know What They Know

arXiv:2602.02605v2 Announce Type: replace-cross Abstract: Evaluating true metacognition in Large Language Models (LLMs) is difficult due to biases and heuristics. This paper presents a framework to me

From Model Scaling to System Scaling: Scaling the Harness in Agentic AI

arXiv:2605.26112v1 Announce Type: new Abstract: This paper studies the next major bottleneck in agentic AI as system scaling, not only model scaling: the design of auditable, persistent, modular, and

GRAIL: AI translation for scientists application workflow on satellite data

arXiv:2605.24784v1 Announce Type: new Abstract: Domain scientists increasingly develop Python scripts to analyze satellite imagery but they lack scalability to large-scale data. This paper demonstrate

agentsarxiv-cs-ai

Merge-Bench: Resolve Merge Conflicts with Large Language Models

model-releasesarxiv-cs-lg

arXiv:2605.25890v1 Announce Type: new Abstract: This paper applies machine learning to the difficult and important task of version control merging. (1) We constructed a dataset, Merge-Bench, of 7938 r

MuGen: Multi-Skill Generative Locomotion Controller for Humanoid Robots

arXiv:2605.24592v1 Announce Type: new Abstract: This paper presents MuGen, a data-driven framework for learning and deploying multi-skill locomotion on humanoid robots. MuGen enables a robot to perfor

Passivity-based Semi-autonomous Rotational Motion Navigation for Rigid-body Networks: Stability and Human Passivity Analysis

arXiv:2605.24731v1 Announce Type: cross Abstract: This paper presents a novel passivity-based semi-autonomous attitude control framework, with a particular focus on attitude kinematics defined on the

agentsarxiv-cs-ro

PolyGnosis 2.0: Enhancing LLM Reasoning via Agentic Harness Engineering for Polymarket and OSINT Insight Extraction

arXiv:2605.25958v1 Announce Type: new Abstract: This paper introduces PolyGnosis 2.0, a pioneering multi-agent architecture designed to extract predictive intelligence by synthesizing Polymarket anoma

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Posture Clip: Sit properly or I wont let you work

arXiv:2605.25664v1 Announce Type: cross Abstract: Poor posture is a significant concern due to its detrimental effects on health and productivity. This paper presents a collar-clipped device called Po

Refined Analysis of Entropy-Regularized Actor-Critic

arXiv:2605.24357v1 Announce Type: new Abstract: In this paper, we study the role of the critic in actor--critic for entropy-regularized, finite, discounted environments. We establish that, when the cr

safetyarxiv-cs-lg

Soft Pneumatic Grippers: Topology optimization, 3D-printing and Experimental validation

arXiv:2511.19211v3 Announce Type: replace Abstract: This paper presents a systematic topology optimization framework for designing a soft pneumatic gripper (SPG), explicitly considering the design-dep

researcharxiv-cs-ro

Spectral Probe-Circuits: A Three-Step Recipe for Identifying Attention-Head Circuits in Pretrained Transformers

arXiv:2605.24059v1 Announce Type: cross Abstract: We present a three-step recipe for identifying attention-head circuits in pretrained transformers. A per-head spectral signal -- the time-integrated p

Stop Comparing LLM Agents Without Disclosing the Harness

arXiv:2605.23950v1 Announce Type: new Abstract: This position paper argues that, for long-horizon tasks evaluated across models with comparable frontier capability, the agent execution harness, namely

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Applications

StrTransformer: Source-Wise Structured Transformers for Unsupervised Blind Source Recovery

arXiv:2605.25648v1 Announce Type: cross Abstract: This paper proposes StrTransformer, a source-wise structured Transformer framework for blind source recovery and branch-wise latent modeling. Instead

applicationsarxiv-cs-lg

Toward Enactive Artificial Intelligence

arXiv:2605.24238v1 Announce Type: new Abstract: In this paper, we advocate for incorporating enactive approaches to perception and cognition into artificial intelligence (AI). Enactive approaches view

agentsarxiv-cs-ai

Towards Low-Gravity Planetary Exploration using Reinforcement Learning for Walking, Jumping, and In-flight Attitude Control

arXiv:2605.24643v1 Announce Type: new Abstract: This paper presents reinforcement learning (RL) policies for dynamic quadrupedal locomotion in planetary exploration scenarios. Building on a taskoptimi

Zeroth-Order Nonconvex Nonsmooth Optimization with Heavy-Tailed Noise

arXiv:2605.24513v1 Announce Type: new Abstract: This paper considers the nonconvex nonsmooth problem in which the objective function is Lipschitz continuous. We focus on the stochastic setting where t

A graph-based analysis of semantic types and coercion in contextualized word embeddings

arXiv:2605.23710v1 Announce Type: new Abstract: Semantic type mismatch between a noun and its context is central to coercion phenomena. This paper introduces a graph-based method to examine how lexica

researcharxiv-cs-cl

Tutorials

Accelerating Divisible Load Processing Through Machine Learning: A Practical Framework for Large-Scale Workloads

arXiv:2605.23247v1 Announce Type: new Abstract: In this paper, we introduce the first machine learning framework for predicting optimal processing times in Single-Level Tree Network (SLTN) architectur

tutorialsarxiv-cs-lg

AI Evaluation Should Require Standardized Item-Level Data Releases

arXiv:2604.03244v2 Announce Type: replace Abstract: This position paper argues that standardized item-level benchmark data should become the default infrastructure for AI evaluation. Current evaluatio

Tutorials

Beyond Normal References: Discriminative Few-Shot Anomaly Detection

arXiv:2605.23231v1 Announce Type: new Abstract: This paper considers a practical few-shot anomaly detection (FSAD) setting, termed discriminative FSAD, where a limited number of both normal and anomal

tutorialsarxiv-cs-cv

Diffusion Domain Expansion: Learning to Coordinate Pre-trained Diffusion Models

arXiv:2605.23275v1 Announce Type: new Abstract: In this paper, we propose Diffusion Domain Expansion (DDE), a method that efficiently extends pre-trained diffusion models to generate larger objects an

DRL-Driven Edge-Aware Utility Optimization for Multi-Slice 6G Networks

arXiv:2605.23056v1 Announce Type: cross Abstract: Virtual Reality (VR) services delivered over 6G networks demand ultra-low latency and high bandwidth to ensure seamless user experiences. This paper p

Generator-Refiner-Examiner: A Tri-Module Data Augmentation Framework for 3D Human Avatar Learning from Monocular Videos

arXiv:2605.23555v1 Announce Type: new Abstract: This paper addresses the challenge of reconstructing photorealistic and animatable 3D human avatars from monocular videos. While existing methods rely o

researcharxiv-cs-cv

On the Koopman-Based Generalization Bounds for Multi-Task Deep Learning

arXiv:2512.19199v2 Announce Type: replace-cross Abstract: The paper establishes generalization bounds for multitask deep neural networks using operator-theoretic techniques. The authors propose a tigh

Tutorials

On the Provable Importance of Gradients for Language-Assisted Image Clustering

arXiv:2510.16335v4 Announce Type: replace Abstract: This paper investigates the recently emerged problem of Language-assisted Image Clustering (LaIC), where textual semantics are leveraged to improve

tutorialsarxiv-cs-cv

Operator-Based Generalization Bound for Deep Learning: Insights on Multi-Task Learning

arXiv:2512.19184v2 Announce Type: replace-cross Abstract: This paper presents novel generalization bounds for vector-valued neural networks and deep kernel methods, focusing on multi-task learning thr

Order-Optimal Sequential 1-Bit Mean Estimation in General Tail Regimes

model-releasesarxiv-cs-lg

arXiv:2604.07796v2 Announce Type: replace-cross Abstract: In this paper, we study the problem of mean estimation under 1-bit communication constraints. We propose a novel adaptive mean estimator based

Applications

PLACE: Prompt Learning for Attributed Community Search in Large Graphs

arXiv:2507.05311v2 Announce Type: replace-cross Abstract: In this paper, we propose PLACE (Prompt Learning for Attributed Community Search), an innovative graph prompt learning framework for ACS. Enli

applicationsarxiv-cs-ai

Real-Time Earthquake Magnitude Classification from Initial P-Waves: Models, Dataset, and Comparative Analysis for South Asia

arXiv:2605.22836v1 Announce Type: cross Abstract: Rapid earthquake magnitude estimation is crucial for effective early warning systems that can save lives and reduce economic damage. In this paper, we

Robust Counterfactual Inference in Markov Decision Processes

arXiv:2502.13731v5 Announce Type: replace Abstract: This paper addresses a key limitation in existing counterfactual inference methods for Markov Decision Processes (MDPs). Current approaches assume a

SciNet: Evaluating AI Agents in Relation-Aware Scientific Literature Retrieval

arXiv:2601.03260v2 Announce Type: replace-cross Abstract: AI agents have seen widespread adoption in information retrieval for scientific research, giving rise to tools such as Deep Research. However,

researcharxiv-cs-cl

Signal Temporal Logic Motion Planning via Graphs of Convex Sets

arXiv:2605.23240v1 Announce Type: new Abstract: This paper investigates continuous-time motion planning under Signal Temporal Logic (STL) specifications. The goal is to generate smooth robot trajector

researcharxiv-cs-ro

The Surprising Difficulty of Search in Model-Based Reinforcement Learning

arXiv:2601.21306v2 Announce Type: replace-cross Abstract: This paper investigates search in model-based reinforcement learning (RL). Conventional wisdom holds that long-term predictions and compoundin

U-CESE: Unified Clip-based Event Search Engine for AI Challenge HCMC 2025

arXiv:2605.23274v1 Announce Type: new Abstract: Retrieving events from large-scale video datasets is challenging due to complex temporal, spatial, and multimodal information. This paper presents U-CES

researcharxiv-cs-cv

Soft Bayesian Context Tree Models for Real-Valued Time Series

arXiv:2601.11079v2 Announce Type: replace Abstract: This paper proposes the soft Bayesian context tree model (Soft-BCT), which is a novel BCT model for real-valued time series. The Soft-BCT considers

23 May 2026

Stabilising Explainability Fragility in Cybersecurity AI: The Impact and Mitigation of Multicollinearity in Public Benchmark Datasets

model-releasesarxiv-cs-lg

arXiv:2605.22529v1 Announce Type: new Abstract: This paper investigates a unexplored yet impactful vulnerability in AI explainability used in intrusion detection (IDS): multicollinearity-induced insta

23 May 2026

Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development

arXiv:2605.20456v1 Announce Type: cross Abstract: Agentic AI coding systems can inspect repositories, plan implementation steps, edit files, call tools, run tests, and submit pull requests. These capa

agentsarxiv-cs-ai

Audience Engagement with Arabic Women's Social Empowerment and Wellbeing: A Decadal Corpus

model-releasesarxiv-cs-cl

arXiv:2605.22204v1 Announce Type: new Abstract: This paper presents the Arabic Women and Society Corpus, a ten year collection of 252,487 public Arabic Facebook posts related to women's empowerment an

Enhancing Causal Reasoning in Large Language Models: A Causal Attribution Model for Precision Fine-Tuning

arXiv:2401.00139v3 Announce Type: replace-cross Abstract: This paper introduces a causal attribution model to enhance the interpretability of large language models (LLMs) and improve their causal reas

researcharxiv-cs-cl

Learning Altruistic Collaboration in Heterogeneous Multi-Team Systems

arXiv:2605.21723v1 Announce Type: new Abstract: This paper studies heterogeneous multi-team collaboration through dynamic robot allocation, where robots are treated as transferable resources. Leveragi