Search: “research”

L3Cube-MahaPOS: A Marathi Part-of-Speech Tagging Dataset and BERT Models

arXiv:2606.24825v1 Announce Type: new Abstract: Part-of-Speech (POS) tagging is a foundational NLP task underpinning machine translation, information extraction, and syntactic parsing. Despite Marathi

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LecturaAgents: A Multi-Agent Framework for Adaptive Personalized AI-Assisted Learning and Embodied Teaching

DGX agent

arXiv:2606.16428v2 Announce Type: replace-cross Abstract: Effective personalized AI-assisted learning demands systems that can not only generate accurate learner-specific educational materials, but al

safetyarxiv-cs-ai

24 Jun 2026

Machine Learning and Deep Learning for Exoplanet Detection and Atmospheric Characterization with JWST and the Upcoming Ariel Mission

arXiv:2606.23766v1 Announce Type: cross Abstract: The detection and atmospheric characterization of exoplanets have entered a new data-intensive era driven by the James Webb Space Telescope and the up

Multimedia and Visual Analytics in the Agentic Era

model-releasesarxiv-cs-ai

arXiv:2504.06138v3 Announce Type: replace-cross Abstract: Professional users need tools to help them gain actionable insights from large multimedia collections. Foundation models and AI agents have ra

NatureBench: Can Coding Agents Match the Published SOTA of Nature-Family Papers?

arXiv:2606.24530v1 Announce Type: new Abstract: We introduce NatureBench, a cross-discipline benchmark of 90 tasks distilled from peer-reviewed Nature-family publications, designed to evaluate whether

OpenThoughts-Agent: Data Recipes for Agentic Models

model-releasesarxiv-cs-ai

arXiv:2606.24855v1 Announce Type: new Abstract: Agentic language models dramatically expand the applications of AI yet little is publicly known about how to curate training data for broadly capable ag

Skills for the future software profession: beyond agentic AI!

arXiv:2606.21894v2 Announce Type: replace-cross Abstract: As coding agents are rapidly changing software engineering, a natural question is: what are the core skills needed by future software engineer

agentsarxiv-cs-ai

SP-Mind: An Autonomous Reasoning Agent for Spatial Proteomics Analysis

model-releasesarxiv-cs-ai

arXiv:2606.24235v1 Announce Type: new Abstract: Spatial proteomics enables single-cell-resolution characterization of protein expression within tissue architecture, playing a critical role in understa

To Compare, or Not to Compare: On Methodological Practices in Evaluating Social Bias

arXiv:2606.24596v1 Announce Type: new Abstract: As Large Language Models are increasingly deployed in critical applications, robustly evaluating their social biases is paramount. However, the current

Toward Self-Evolution-Ready Workflow Harnesses: A Reversible Migration Path and Convertibility Taxonomy for Expert LLM Pipelines

arXiv:2606.24598v1 Announce Type: cross Abstract: While expert-validated 'LLM + script' workflows deliver significant value, they remain static: they encode hard-won domain knowledge yet fail to adapt

agentsarxiv-cs-ai

Transformer-Based Language Models Across Domain Verticals: Architectures, Applications and Critical Assessment

arXiv:2606.24331v1 Announce Type: new Abstract: Transformer-based language models have become the default substrate for natural language processing and the pace of new releases has made it hard for pr

VisChronos: Revolutionizing Image Captioning Through Real-Life Events

arXiv:2606.24058v1 Announce Type: new Abstract: This paper aims to bridge the semantic gap between visual content and natural language understanding by leveraging historical events in the real world a

applicationsarxiv-cs-cv

When AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments

arXiv:2407.18957v5 Announce Type: replace-cross Abstract: Can AI Agents simulate real-world trading environments to investigate the impact of external factors on stock trading activities (e.g., macroe

safetyarxiv-cs-ai

A Completion-Aware Framework for Impactful Counterfactual Explainability in Graph Neural Networks

arXiv:2606.22033v1 Announce Type: new Abstract: In this study, we propose a novel pipeline for generic, model-agnostic, local-level counterfactual explainability in graph neural networks (GNNs). Altho

applicationsarxiv-cs-lg

A Linear Fractional Transformation Model and Calibration Method for Light Field Camera

arXiv:2511.03962v2 Announce Type: replace Abstract: Accurate intrinsic calibration is a crucial yet challenging prerequisite for 3D reconstruction using light field cameras. Existing calibration model

A Skin-Tone-Aware Dual-Representation Remote Photoplethysmography Framework for Contactless Respiratory Rate Estimation

arXiv:2606.21511v1 Announce Type: cross Abstract: Respiratory rate is a vital indicator of pulmonary and cardiovascular health, yet conventional methods for estimating respiratory rate are often intru

A Stitch in Time Saves Nine: Preserving Policy Compatibility Under Perception Updates in End-to-End Autonomous Driving

arXiv:2606.21509v1 Announce Type: new Abstract: End-to-end autonomous driving systems tightly couple perception and decision-making through latent representations. Consequently, updates to perception

safetyarxiv-cs-ro

Adam symmetry theorem: characterization of the convergence of the stochastic Adam optimizer

arXiv:2511.06675v2 Announce Type: replace-cross Abstract: Beside the standard stochastic gradient descent (SGD) method, the Adam optimizer due to Kingma & Ba (2014) is currently probably the best-know

AI Agents Can Already Autonomously Perform Experimental High Energy Physics

arXiv:2603.20179v3 Announce Type: replace-cross Abstract: Large language model-based AI agents are now able to autonomously execute substantial portions of a high energy physics (HEP) analysis pipelin

AIR: Adaptive Interleaved Reasoning with Code in MLLMs

arXiv:2606.23678v1 Announce Type: new Abstract: Following the paradigm shift initiated by OpenAI o3, interleaved reasoning with code to enhance multimodal large language models (MLLMs) has become a pi

agentsarxiv-cs-cv

Analysis and Prediction of At-Risk Students Using Machine Learning Algorithms

arXiv:2606.20617v1 Announce Type: cross Abstract: Student attrition represents a significant challenge for higher education institutions because it impacts both academic results and financial viabilit

applicationsarxiv-cs-lg

ASCII Art Turns LLMs into VLA Controllers

arXiv:2606.21470v1 Announce Type: cross Abstract: Vision--Language--Action (VLA) controllers are often built by extending vision--language models (VLMs) with action supervision, relying on multimodal

Bayesian Adaptation Gym: A Benchmark for the Bayesian Low-Rank Adaptation of Multi-Modal Language Models

arXiv:2606.22188v1 Announce Type: new Abstract: Large multi-modal language models are increasingly deployed in high-stakes domains, making well-calibrated uncertainty essential. Traditional Bayesian m

Beyond a Single Light: A Large-Scale Aerial Dataset for Urban Scene Reconstruction Under Varying Illumination

arXiv:2512.14200v2 Announce Type: replace Abstract: Recent advances in Neural Radiance Fields and 3D Gaussian Splatting have demonstrated strong potential for large-scale UAV-based 3D reconstruction t

applicationsarxiv-cs-cv

Tutorials

Decision-Focused Learning: When and Why Traditional Prediction Models Fail

arXiv:2606.21773v1 Announce Type: new Abstract: Plugging predictions of unknown parameters into downstream optimization problems, often referred to as the ``predict-then-optimize'' paradigm, has long

tutorialsarxiv-cs-lg

Tutorials

Do Sparse Autoencoders Learn Meaningful Concept Hierarchies?

arXiv:2606.22994v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) have become an important tool for unsupervised concept discovery in large models. To make the resulting feature spaces more i

tutorialsarxiv-cs-lg

GAPartManip: A Large-scale Part-centric Dataset for Material-Agnostic Articulated Object Manipulation

arXiv:2411.18276v3 Announce Type: replace Abstract: Effectively manipulating articulated objects in household scenarios is a crucial step toward achieving general embodied artificial intelligence. Mai

applicationsarxiv-cs-ro

HEAS: Hierarchical Evolutionary Agent-Based Simulation Framework for Multi-Objective Policy Search

arXiv:2508.15555v4 Announce Type: replace-cross Abstract: HEAS is a Python framework that connects agent-based simulation, evolutionary search, and scenario-based evaluation in a single reproducible p

safetyarxiv-cs-lg

Large Language Model-Assisted Cleaning of Report-Derived Labels in a Large-Scale Chest CT Dataset

arXiv:2606.22382v1 Announce Type: cross Abstract: Purpose: To evaluate whether large language model (LLM)-assisted label cleaning can identify label-report discordance in CT-RATE, a large-scale public

Lessons from the Field: A Case Study of Robotic Intervention in an Industrial Emergency

arXiv:2606.23246v1 Announce Type: new Abstract: Incidents in chemical plants can pose a high level of risk and harsh environments for first responders. Contamination and explosion hazards can deny hum

applicationsarxiv-cs-ro

Leveraging LaBSE with Progressive Curriculum Learning for Multicultural Polarization

arXiv:2606.21718v1 Announce Type: cross Abstract: Detecting online polarization remains a critical challenge, particularly in multilingual and multicultural contexts where intergroup hostility is prev

LUMINA-26: Low-Light Understanding for Modeling and Interpreting Night-time Actions

arXiv:2606.23118v1 Announce Type: new Abstract: Low-light human action recognition remains a challenging problem due to poor illumination, amplified noise, motion ambiguity, and diverse real-world sce

Memory Contagion: Cross-Temporal Propagation of Evaluator Bias via Agent Memory

arXiv:2606.23195v1 Announce Type: new Abstract: Large Language Model (LLM) agents increasingly rely on memory systems to maintain long-term coherence. Recent work shows that agent memories degrade dur

safetyarxiv-cs-lg

Model Merging in the Essential Subspace

arXiv:2602.20208v2 Announce Type: replace Abstract: Model merging aims to integrate multiple task-specific fine-tuned models derived from a shared pre-trained checkpoint into a single multi-task model

NegAS: Negative Label Guided Attention and Scoring for Out-of-Distribution Object Detection with Vision-Language Models

arXiv:2606.22537v1 Announce Type: new Abstract: Out-of-Distribution (OOD) detection is essential for ensuring the robustness and reliability of object detection systems deployed in safety-critical app

safetyarxiv-cs-cv

Local Ai

NeoLoc-68: End-to-end 68-point neonatal facial landmark localisation in neonatal clinical environments

arXiv:2606.20823v1 Announce Type: new Abstract: Facial landmark localisation is a prerequisite for developing automated, non-contact neonatal pain assessment methods. Clinicians use pain scales to jud

local-aiarxiv-cs-cv

Noise is Signal: Density-Based Outliers as Leading Indicators of Occupational Emergence in Labor Market Text

arXiv:2606.22769v1 Announce Type: new Abstract: Standard NLP pipelines for occupational clustering discard the 10-15% of job postings that density-based methods assign to noise. We argue this is an er

safetyarxiv-cs-lg

Local Ai

Over-the-Air Federated Learning: Rethinking Edge AI Through Signal Processing

arXiv:2512.03719v2 Announce Type: replace-cross Abstract: Over-the-Air Federated Learning (AirFL) is an emerging paradigm that tightly integrates wireless signal processing and distributed machine lea

local-aiarxiv-cs-lg

Hardware

RAVEN: Agentic RAG for Automated Vulnerability Repair

arXiv:2606.22647v1 Announce Type: cross Abstract: Automated vulnerability repair has emerged as a promising direction to mitigate the growing number of software vulnerabilities. Recent advances in Lar

hardwarearxiv-cs-lg

Hardware

Real-World Deployment of Massively Parallel Sampling-Based MPC for Contact-Rich Manipulation

arXiv:2606.20712v1 Announce Type: new Abstract: Sampling-based Model Predictive Control (SMPC) is a promising strategy for contact-rich robotic manipulation, combining gradient-free optimization with

hardwarearxiv-cs-ro

Sakana Fugu Technical Report

arXiv:2606.21228v1 Announce Type: new Abstract: The capabilities of frontier Large Language Models (LLMs) continue to advance, with different providers increasingly specializing in distinct domains. T

agentsarxiv-cs-lg

SegTME-UNI2: A Foundation Model-Based Framework for Generalisable Multiclass Cell Segmentation and LLM-Driven Tumour Microenvironment Characterisation in Histopathology

arXiv:2606.17702v2 Announce Type: replace Abstract: Characterising the tumour microenvironment (TME) from routine H&E-stained histology images requires simultaneous cell segmentation, feature extracti

Sequential Minimal Optimization Algorithm for One-Class Support Vector Machines With Privileged Information

arXiv:2606.22210v1 Announce Type: new Abstract: One of the powerful techniques in data modeling is accounting for features that are available at the training stage, but are not available when the trai

ShotcreteDepth: A Bi-modal Dataset for Robust Robotic Depth Perception in Shotcrete Construction Environments

arXiv:2606.23152v1 Announce Type: new Abstract: We introduce ShotcreteDepth, a bi-modal dataset from the construction domain that captures both an active shotcreting process and general construction e

agentsarxiv-cs-ro

TaigiSpeech: A Low-Resource Real-World Speech Intent Dataset and Preliminary Results with Scalable Data Mining In-the-Wild

arXiv:2603.21478v2 Announce Type: replace-cross Abstract: Speech technologies have advanced rapidly and serve diverse populations worldwide. However, many languages remain underrepresented due to limi

Local Ai

Tessellated Biomes: Distributed Robotic Assemblies for Architectural Resilience

arXiv:2606.20647v1 Announce Type: new Abstract: This paper presents Tessellated Biomes, a cyber-physical framework for the adaptive robotic construction and reconfiguration of modular multi-material a

local-aiarxiv-cs-ro

Toward Non-Expert Customized Congestion Control: Large Language Model-Assisted CCA Code Generation with eBPF Deployment

arXiv:2601.22461v2 Announce Type: replace-cross Abstract: General-purpose congestion control algorithms (CCAs) are designed to achieve general congestion control goals, but they may not meet the speci

applicationsarxiv-cs-lg

Towards Robust Personalized Federated Learning: Vulnerability Assessment and Defense Co-Design

arXiv:2606.22782v1 Announce Type: new Abstract: The proliferation of IoT devices has fueled distributed edge systems to collect vast amounts of sensitive data, creating fertile ground for on-device ma