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How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models

arXiv:2604.21106v1 Announce Type: cross Abstract: We measure how much one extra recurrence is worth to a looped (depth-recurrent) language model, in equivalent unique parameters. From an iso-depth swe

researcharxiv-cs-cl

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How to Allocate, How to Learn? Dynamic Rollout Allocation and Advantage Modulation for Policy Optimization

DGX agent

arXiv:2602.19208v2 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective for Large Language Model (LLM) reasoning, yet current methods face

safetyarxiv-cs-ai

24 Apr 2026

How VLAs (Really) Work In Open-World Environments

arXiv:2604.21192v1 Announce Type: cross Abstract: Vision-language-action models (VLAs) have been extensively used in robotics applications, achieving great success in various manipulation problems. Mo

Human Presence Detection via Wi-Fi Range-Filtered Doppler Spectrum on Commodity Laptops

arXiv:2603.10845v3 Announce Type: replace-cross Abstract: Human Presence Detection (HPD) is key to enable intelligent power management and security features in everyday devices. In this paper we propo

researcharxiv-cs-ai

HWE-Bench: Benchmarking LLM Agents on Real-World Hardware Bug Repair Tasks

arXiv:2604.14709v2 Announce Type: replace Abstract: Existing benchmarks for hardware design primarily evaluate Large Language Models (LLMs) on isolated, component-level tasks such as generating HDL mo

Hybrid Deep Learning Approach for Coupled Demand Forecasting and Supply Chain Optimization

arXiv:2604.21567v1 Announce Type: cross Abstract: Supply chain resilience and efficiency are vital in industries characterized by volatile demand and uncertain supply, such as textiles and personal pr

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering

arXiv:2604.21027v1 Announce Type: new Abstract: Electronic health record (EHR) question answering is often handled by LLM-based pipelines that are costly to deploy and do not explicitly leverage the h

HyperAdapt: Simple High-Rank Adaptation

arXiv:2509.18629v3 Announce Type: replace-cross Abstract: Foundation models excel across diverse tasks, but adapting them to specialized applications often requires fine-tuning, an approach that is me

Hyperboloid GPLVM for Discovering Continuous Hierarchies via Nonparametric Estimation

arXiv:2410.16698v2 Announce Type: replace Abstract: Dimensionality reduction (DR) offers a useful representation of complex high-dimensional data. Recent DR methods focus on hyperbolic geometry to der

HyperFM: An Efficient Hyperspectral Foundation Model with Spectral Grouping

model-releasesarxiv-cs-cv

arXiv:2604.21127v1 Announce Type: new Abstract: The NASA PACE mission provides unprecedented hyperspectral observations of ocean color, aerosols, and clouds, offering new insights into how these compo

Hyperloop Transformers

arXiv:2604.21254v1 Announce Type: cross Abstract: LLM architecture research generally aims to maximize model quality subject to fixed compute/latency budgets. However, many applications of interest su

ICNN-enhanced 2SP: Leveraging input convex neural networks for solving two-stage stochastic programming

model-releasesarxiv-cs-lg

arXiv:2505.05261v3 Announce Type: replace-cross Abstract: Two-stage stochastic programming (2SP) offers a basic framework for modelling decision-making under uncertainty, yet scalability remains a cha

ID-Eraser: Proactive Defense Against Face Swapping via Identity Perturbation

arXiv:2604.21465v1 Announce Type: new Abstract: Deepfake technologies have rapidly advanced with modern generative AI, and face swapping in particular poses serious threats to privacy and digital secu

researcharxiv-cs-cv

Identifying Bias in Machine-generated Text Detection

arXiv:2512.09292v2 Announce Type: replace-cross Abstract: The meteoric rise in text generation capability has been accompanied by parallel growth in interest in machine-generated text detection: the c

Ideological Bias in LLMs' Economic Causal Reasoning

arXiv:2604.21334v1 Announce Type: new Abstract: Do large language models (LLMs) exhibit systematic ideological bias when reasoning about economic causal effects? As LLMs are increasingly used in polic

ILDR: Geometric Early Detection of Grokking

model-releasesarxiv-cs-lg

arXiv:2604.20923v1 Announce Type: new Abstract: Grokking describes a delayed generalization phenomenon in which a neural network achieves perfect training accuracy long before validation accuracy impr

Local Ai

ImageHD: Energy-Efficient On-Device Continual Learning of Visual Representations via Hyperdimensional Computing

arXiv:2604.21280v1 Announce Type: new Abstract: On-device continual learning (CL) is critical for edge AI systems operating on non-stationary data streams, but most existing methods rely on backpropag

local-aiarxiv-cs-cv

Impact-Aware Model Predictive Control for UAV Landing on a Heaving Platform

arXiv:2604.21078v1 Announce Type: new Abstract: Landing UAVs on heaving marine platforms is challenging because relative vertical motion can generate large impact forces and cause rebound on touchdown

researcharxiv-cs-ro

Agents

Improving Clinical Diagnosis with Counterfactual Multi-Agent Reasoning

arXiv:2603.27820v2 Announce Type: replace Abstract: Clinical diagnosis is a complex reasoning process in which clinicians gather evidence, form hypotheses, and test them against alternative explanatio

agentsarxiv-cs-cl

Improving Performance in Classification Tasks with LCEN and the Weighted Focal Differentiable MCC Loss

arXiv:2604.21252v1 Announce Type: new Abstract: The LASSO-Clip-EN (LCEN) algorithm was previously introduced for nonlinear, interpretable feature selection and machine learning. However, its design an

Inferring High-Level Events from Timestamped Data: Complexity and Medical Applications

arXiv:2604.21793v1 Announce Type: new Abstract: In this paper, we develop a novel logic-based approach to detecting high-level temporally extended events from timestamped data and background knowledge

InfiniPipe: Elastic Pipeline Parallelism for Efficient Variable-Length Long-Context LLM Training

arXiv:2509.21275v3 Announce Type: replace-cross Abstract: Long context training is crucial for LLM's context extension. Existing schemes, such as sequence parallelism, incur substantial communication

Information Bottleneck-Guided Heterogeneous Graph Learning for Interpretable Neurodevelopmental Disorder Diagnosis

arXiv:2502.20769v3 Announce Type: replace Abstract: Developing interpretable models for neurodevelopmental disorders (NDDs) diagnosis presents significant challenges in effectively encoding, decoding,

tutorialsarxiv-cs-cv

Instance-level Visual Active Tracking with Occlusion-Aware Planning

arXiv:2604.21453v1 Announce Type: new Abstract: Visual Active Tracking (VAT) aims to control cameras to follow a target in 3D space, which is critical for applications like drone navigation and securi

applicationsarxiv-cs-cv

Integrated packing, placement, scheduling, and routing of personalized production: a pharmaceutical Industry 4.0 use-case with a planar transport system

arXiv:2604.21029v1 Announce Type: cross Abstract: The recent emergence of planar transport systems necessitates re-evaluation of Flexible Manufacturing Systems (FMS) to address the simultaneous schedu

Intent Laundering: AI Safety Datasets Are Not What They Seem

arXiv:2602.16729v3 Announce Type: replace-cross Abstract: We systematically evaluate the quality of widely used adversarial safety datasets from two perspectives: in isolation and in practice. In isol

Interpretable facial dynamics as behavioral and perceptual traces of deepfakes

model-releasesarxiv-cs-cv

arXiv:2604.21760v1 Announce Type: new Abstract: Deepfake detection research has largely converged on deep learning approaches that, despite strong benchmark performance, offer limited insight into wha

Interpretable Quantile Regression by Optimal Decision Trees

arXiv:2604.21042v1 Announce Type: new Abstract: The field of machine learning is subject to an increasing interest in models that are not only accurate but also interpretable and robust, thus allowing

InVitroVision: a Multi-Modal AI Model for Automated Description of Embryo Development using Natural Language

arXiv:2604.21061v1 Announce Type: new Abstract: The application of artificial intelligence (AI) in IVF has shown promise in improving consistency and standardization of decisions, but often relies on

researcharxiv-cs-ai

IRIS: Interpolative Renyi Iterative Self-play for Large Language Model Fine-Tuning

arXiv:2604.20933v1 Announce Type: cross Abstract: Self-play fine-tuning enables large language models to improve beyond supervised fine-tuning without additional human annotations by contrasting annot

It's High Time: A Survey of Temporal Question Answering

arXiv:2505.20243v4 Announce Type: replace Abstract: Time plays a critical role in how information is generated, retrieved, and interpreted. In this survey, we provide a comprehensive overview of Tempo

JEPAMatch: Geometric Representation Shaping for Semi-Supervised Learning

arXiv:2604.21046v1 Announce Type: new Abstract: Semi-supervised learning has emerged as a powerful paradigm for leveraging large amounts of unlabeled data to improve the performance of machine learnin

tutorialsarxiv-cs-lg

Job Skill Extraction via LLM-Centric Multi-Module Framework

arXiv:2604.21525v1 Announce Type: new Abstract: Span-level skill extraction from job advertisements underpins candidate-job matching and labor-market analytics, yet generative large language models (L

researcharxiv-cs-cl

KD-CVG: A Knowledge-Driven Approach for Creative Video Generation

arXiv:2604.21362v1 Announce Type: new Abstract: Creative Generation (CG) leverages generative models to automatically produce advertising content that highlights product features, and it has been a si

safetyarxiv-cs-cv

Kernel-Smith: A Unified Recipe for Evolutionary Kernel Optimization

arXiv:2603.28342v2 Announce Type: replace Abstract: We present Kernel-Smith, a framework for high-performance GPU kernel and operator generation that combines a stable evaluation-driven evolutionary a

KGiRAG: An Iterative GraphRAG Approach for Responding Sensemaking Queries

arXiv:2604.20859v1 Announce Type: cross Abstract: Recent literature highlights the potential of graph-based approaches within large language model (LLM) retrieval-augmented generation (RAG) pipelines

researcharxiv-cs-ai

KinetiDiff: Docking-Guided Diffusion for De Novo ACVR1 Inhibitor Design in Fibrodysplasia Ossificans Progressiva

arXiv:2604.20886v1 Announce Type: cross Abstract: We present KinetiDiff, a structure-based framework for de novo kinase inhibitor design that integrates a Geometry-Complete Diffusion Model with real-t

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems

arXiv:2508.10177v3 Announce Type: replace Abstract: Recent Large Language Model (LLM)-based AutoML systems demonstrate impressive capabilities but face significant limitations such as constrained expl

LAF-Based Evaluation and UTTL-Based Learning Strategies with MIATTs

arXiv:2604.20944v1 Announce Type: cross Abstract: In many real-world machine learning (ML) applications, the true target cannot be precisely defined due to ambiguity or subjectivity information. To ad

Language as a Latent Variable for Reasoning Optimization

arXiv:2604.21593v1 Announce Type: new Abstract: As LLMs reduce English-centric bias, a surprising trend emerges: non-English responses sometimes outperform English on reasoning tasks. We hypothesize t

Language-Conditioned Safe Trajectory Generation for Spacecraft Rendezvous

arXiv:2512.09111v3 Announce Type: replace-cross Abstract: Reliable real-time trajectory generation is essential for future autonomous spacecraft. While recent progress in nonconvex guidance and contro

Large-Scale Data Parallelization of Product Quantization and Inverted Indexing Using Dask

arXiv:2604.21645v1 Announce Type: new Abstract: Large-scale Nearest Neighbor (NN) search, though widely utilized in the similarity search field, remains challenged by the computational limitations inh

Latent Denoising Improves Visual Alignment in Large Multimodal Models

model-releasesarxiv-cs-cv

arXiv:2604.21343v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) such as LLaVA are typically trained with an autoregressive language modeling objective, providing only indirect supervisi

LatRef-Diff: Latent and Reference-Guided Diffusion for Facial Attribute Editing and Style Manipulation

arXiv:2604.21279v1 Announce Type: new Abstract: Facial attribute editing and style manipulation are crucial for applications like virtual avatars and photo editing. However, achieving precise control

researcharxiv-cs-cv

Learn Weightlessness: Imitate Non-Self-Stabilizing Motions on Humanoid Robot

arXiv:2604.21351v1 Announce Type: new Abstract: The integration of imitation and reinforcement learning has enabled remarkable advances in humanoid whole-body control, facilitating diverse human-like

tutorialsarxiv-cs-ro

Learning Dynamic Representations and Policies from Multimodal Clinical Time-Series with Informative Missingness

arXiv:2604.21235v1 Announce Type: cross Abstract: Multimodal clinical records contain structured measurements and clinical notes recorded over time, offering rich temporal information about the evolut

safetyarxiv-cs-cl

Learning Linear Regression with Low-Rank Tasks in-Context

arXiv:2510.04548v2 Announce Type: replace-cross Abstract: In-context learning (ICL) is a key building block of modern large language models, yet its theoretical mechanisms remain poorly understood. It

tutorialsarxiv-cs-lg

Learning Physics from Pretrained Video Models: A Multimodal Continuous and Sequential World Interaction Models for Robotic Manipulation

arXiv:2603.00110v2 Announce Type: replace Abstract: The scarcity of large-scale robotic data has motivated the repurposing of foundation models from other modalities for policy learning. In this work,

safetyarxiv-cs-ro