Search: “papers”

How Small Can 6G Reason? Scaling Tiny-to-Small Language Models for AI-Native Networks

model-releasesarxiv-cs-ai

arXiv:2603.02156v2 Announce Type: replace-cross Abstract: Emerging 6G visions, reflected in ongoing standardization efforts within 3GPP, IETF, ETSI, ITU-T, and the O-RAN Alliance, increasingly charact

Research

Hybrid-IR: Dual-Path Hybrid Retrieval with Iterative Reasoning for Complex Medical Question Answering

DGX agent

arXiv:2606.25338v1 Announce Type: new Abstract: Large language models (LLMs) have shown promising performance across a wide range of biomedical applications, including medical question answering (QA),

researcharxiv-cs-cl

25 Jun 2026

Local Ai

Hypergraph Normal World Models for Logical Visual Anomaly Detection

arXiv:2606.25368v1 Announce Type: new Abstract: Visual anomaly detection is often deployed with only normal training images. Most one-class detectors map test patches or features to a normal reference

local-aiarxiv-cs-cv

Invisible to humans, visible to machines: a preregistered audit of Unicode fidelity across four biomedical bibliographic APIs

arXiv:2606.24897v1 Announce Type: cross Abstract: Biomedical text mining, scientometrics, and the construction of training corpora for biomedical large language models (LLMs) all assume that the abstr

KidRisk: Benchmark Dataset for Children Dangerous Action Recognition

model-releasesarxiv-cs-cv

arXiv:2606.25298v1 Announce Type: new Abstract: Children are naturally energetic, and during their spontaneous activities, they often encounter potentially dangerous situations, especially when lackin

Latent Block-Diffusion Temporal Point Processes: A Semi-Autoregressive Framework for Asynchronous Event Sequence Generation

arXiv:2606.24982v1 Announce Type: new Abstract: Modeling and sampling from the underlying distribution of asynchronous event sequences are crucial in various real-world applications, including social

Learning Optimization Proxies for Sequential Contextual Stochastic Programs: An Order Fulfillment Application

arXiv:2606.25362v1 Announce Type: cross Abstract: Sequential contextual stochastic programs model real-time decision systems in which each time epoch commits to an action under uncertainty whose conse

Learning to Erase Private Knowledge from Multi-Documents for Retrieval-Augmented Large Language Models

arXiv:2504.09910v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) is a promising technique for applying LLMs to proprietary domains. However, retrieved documents may contain sen

Lightweight PCGAE-Net: Parallel CrossGate Attention and Bottleneck AutoEncoder for Efficient 5G Channel Prediction

arXiv:2606.25401v1 Announce Type: cross Abstract: Accurate channel state information (CSI) prediction is essential for proactive beamforming and resource management in 5G massive MIMO systems, yet the

safetyarxiv-cs-ai

LLM Performance on a Real, Double-Marked GCSE Benchmark

model-releasesarxiv-cs-cl

arXiv:2606.24973v1 Announce Type: new Abstract: We introduce a dataset of 32,534 double-marked real student responses to GCSE mock exams (GCSEs are the UK's national exams, taken at age ~16), spanning

MedGuards: Multi-Agent System for Reliable Medical Error Detection and Correction

arXiv:2606.25651v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed in healthcare settings, accurate error detection and correction in generated or existing text

safetyarxiv-cs-cl

MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation

arXiv:2606.26016v1 Announce Type: new Abstract: Normalizing Flows (NFs) are powerful generative models capable of exact density estimation and sampling. However, their strict invertibility often force

Minimalist Preprocessing Approach for Image Synthesis Detection

arXiv:2606.25297v1 Announce Type: new Abstract: Generative models have significantly advanced image generation, resulting in synthesized images that are increasingly indistinguishable from authentic o

Model Forensics: Investigating Whether Concerning Behavior Reflects Misalignment

arXiv:2606.26071v1 Announce Type: new Abstract: A central goal of safety research is determining whether a model is misaligned. Prior work has largely focused on detecting concerning behavior. But beh

New research from Meta. Building synthetic training data has stayed a fixed pipeline that you hand-tune and then freeze. Autodata casts an A…

New research from Meta. Building synthetic training data has stayed a fixed pipeline that you hand-tune and then freeze. Autodata casts an AI agent as a data scientist that builds training and evaluat

agentsdair-ai--x

Optimizing Abstractive Summarization With Fine-Tuned PEGASUS

arXiv:2606.25462v1 Announce Type: new Abstract: Abstractive text summarization is the technique of generating a short and concise summary comprising the salient ideas of a source text without making a

Overview of HIPE-2026: Person-Place Relation Extraction from Multilingual Historical Texts

arXiv:2606.25935v1 Announce Type: new Abstract: Was this person ever at that place, and if so, when? Answering such questions from noisy, multilingual historical documents is the central challenge of

Power-Budgeted Underwater Vehicle Control via Constrained Reinforcement Learning

arXiv:2606.25680v1 Announce Type: new Abstract: Underwater vehicles operate from a fixed onboard energy budget that propulsion rapidly depletes, so a controller that completes its task while drawing l

safetyarxiv-cs-ro

Privacy Vulnerabilities of Attention Layers in Tabular Foundation Models and Protection of High-Risk Queries

arXiv:2606.26021v1 Announce Type: cross Abstract: Tabular foundation models are commonly assumed to present limited privacy concerns as they are often pre-trained on large collections of synthetic dat

researcharxiv-cs-ai

Probabilistic Agents in Deterministic Audits: Evaluating Multi-Agent Systems for Automated Audits Based on the German IT-Grundschutz

arXiv:2606.25622v1 Announce Type: cross Abstract: The NIS-2 Directive mandates robust Risk Management from thousands of small and medium enterprises. To ensure compliance, companies rely on establishe

agentsarxiv-cs-ai

PVF:Understanding AI Vulnerability Against SDCs

arXiv:2405.01741v4 Announce Type: replace-cross Abstract: Reliability of AI systems is a fundamental concern for the successful deployment and widespread adoption of AI technologies. Unfortunately, th

RAVEN: Long-Horizon Reasoning & Navigation with a Visuo-Spatio-Temporal Memory

arXiv:2606.25206v1 Announce Type: cross Abstract: Long-term robot deployment requires a compact and scalable memory that preserves fine-grained visual semantics, grounds observations in space and time

agentsarxiv-cs-cl

Recursive QLSTM with Dynamic Variational Quantum Circuit Adaptation

arXiv:2606.24932v1 Announce Type: cross Abstract: Recent advances in quantum computing and machine learning have motivated the development of quantum models for sequential data processing. In this pap

researcharxiv-cs-lg

RigPI: Dynamic Parameter Identification of Rigid Body via VLM-Seeded Differentiable Simulation

model-releasesarxiv-cs-ro

arXiv:2606.25212v1 Announce Type: new Abstract: Accurate physical parameter identification of manipulated objects is fundamental to advanced robotic manipulation and the construction of faithful digit

RN-D: Discretized Categorical Actors for On-Policy Reinforcement Learning

arXiv:2601.23075v2 Announce Type: replace Abstract: On-policy Reinforcement Learning (RL) remains a dominant paradigm for continuous control, yet standard implementations rely on Gaussian actors and r

Safe Learning Control with Optimality and Stability Guarantees

arXiv:2501.15373v2 Announce Type: replace-cross Abstract: Merely pursuing performance may adversely affect safety, while a conservative policy for safe exploration will degrade the performance. How to

Sample complexity of unbalanced entropic OT

arXiv:2606.24987v1 Announce Type: cross Abstract: Optimal transport (OT) has become a central language for comparing probability measures, but exact balanced OT is often both too rigid for data with m

researcharxiv-cs-lg

Securing Time Integrity in Energy IoT Against Clock Drift and Y2K38 Failures

arXiv:2601.23147v2 Announce Type: replace Abstract: The integrity of time in distributed Internet of Things (IoT) devices is crucial for reliable operation in energy cyber-physical systems, such as sm

researcharxiv-cs-lg

SEMIR: Topology-Preserving Graph Minors for Thin-Structure Segmentation

arXiv:2606.24935v1 Announce Type: new Abstract: Thin-structure segmentation--power lines, cracks, lane markings at 1-3 pixel width--requires preserving connectivity that standard representations precl

Shift Variant Image Degradation and Restoration Using Singular Value Decomposition

arXiv:2606.25818v1 Announce Type: new Abstract: Shift-variant image degradation is frequently encountered in practical imaging systems where the point spread function (PSF) varies across the image fie

Silent Failures in Physics-Informed Neural Networks: Parameter Poisoning and the Limits of Loss-Based Validation

arXiv:2606.25151v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) embed governing equations in their loss function, enabling mesh-free solutions to partial differential equation

Local Ai

Spatio-Temporal Retrieval-based Priors for Adaptive Computational Teaching in Driving

arXiv:2606.25224v1 Announce Type: new Abstract: Learning-based automated coaching systems for complex motor tasks such as high-performance driving remain limited in the ability to be adaptive by their

local-aiarxiv-cs-ro

Speech Codec Probing from Semantic and Phonetic Perspectives

model-releasesarxiv-cs-cl

arXiv:2603.10371v2 Announce Type: replace-cross Abstract: Speech tokenizers are essential for connecting speech to large language models (LLMs) in multimodal systems. Speech tokenizers are expected to

Tutorials

Stabilizing black-box algorithms through task-oriented randomization

arXiv:2606.25269v1 Announce Type: cross Abstract: As black-box models become foundational to modern research, ensuring their stability is paramount for the realization of trustworthy artificial intell

tutorialsarxiv-cs-lg

Stage-Aware and Roughness-Constrained Diffusion Policy for Multi-Stage Robotic Polishing

model-releasesarxiv-cs-ro

arXiv:2606.25754v1 Announce Type: new Abstract: Polishing is a critical finishing process in high-end manufacturing fields such as aerospace, where surface quality directly affects the service perform

StairMaster: Learning to Conquer Risky Hollow Stairs for Agile Quadrupedal Robots

arXiv:2606.25765v1 Announce Type: new Abstract: Climbing hollow stairs remains a challenging problem for quadruped robots due to the high risk of leg trapping, severe depth sparsity, and high-frequenc

safetyarxiv-cs-ro

Supervised Reinforcement Learning for the Coordination of Distributed Energy Resources

arXiv:2606.24947v1 Announce Type: new Abstract: The increasing integration of distributed energy resources (DERs) is crucial for power system decarbonization, yet unlocking DERs' flexibility is challe

SurveilNav: Collaborative Object Goal Navigation with Robot and Surveillance System

arXiv:2606.25119v1 Announce Type: new Abstract: With the growing deployment of surveillance systems in factories, offices, and homes, integrating them with robots offers a promising direction for coll

agentsarxiv-cs-ro

SwarmFly: A simulation platform for UAV swarm experiment design and validation

arXiv:2606.25146v1 Announce Type: new Abstract: The initial development phase of UAV swarms largely depends on simulation for experimental design and validation, yet existing open-source tools are oft

agentsarxiv-cs-ro

TACO: Towards Task-Consistent Open-Vocabulary Adaptation in Video Recognition

model-releasesarxiv-cs-cv

arXiv:2606.25478v1 Announce Type: new Abstract: Adapting CLIP for open-vocabulary video recognition necessitates a delicate balance between newly acquired video knowledge and the pretrained generaliza

The Tatoxa System for Text Detoxification in Low-Resource Languages: The Case of Tatar

arXiv:2606.26015v1 Announce Type: new Abstract: Text detoxification, the automated detection and mitigation of abusive and harmful content, is essential for ensuring the safety of online communities a

safetyarxiv-cs-cl

This has a lot in common with how controlled self-evolution works in Row-Bot. And that built on top on LangGraph too. Here's an article I wr…

This has a lot in common with how controlled self-evolution works in Row-Bot. And that built on top on LangGraph too. Here's an article I wrote about how it works a few days ago: https://x.com/i/statu

agentsharrison-chase--x

To View Transform or Not to View Transform: NeRF-based Pre-training Perspective

arXiv:2603.28090v2 Announce Type: replace Abstract: Neural radiance fields (NeRFs) have emerged as a prominent pre-training paradigm for vision-centric autonomous driving, which enhances 3D geometry a

agentsarxiv-cs-cv

Toward Low-Latency Vision-Language Models with Doubly-Correct Predictions in Egocentric Visual Understanding

model-releasesarxiv-cs-cv

arXiv:2606.25160v1 Announce Type: cross Abstract: The rapid rise of Vision-Language Models (VLMs) in egocentric visual understanding has made low-latency inference in human-robot collaborative (HRC) t

Towards a Dynamic and Fixed-budget Memory Bank for Efficient Streaming Video Understanding

arXiv:2606.25658v1 Announce Type: new Abstract: Currently, streaming video understanding is still a daunting task for existing multimodal large language models (MLLMs). Its difficulties not only lie i

Applications

Towards Continuous Power Forecasting: Practical Continual Learning for Real-World Energy Systems in Nonstationary Time Series

arXiv:2606.24955v1 Announce Type: new Abstract: Power forecasting models deployed in real-world energy markets must operate under nonstationary conditions, where data distributions continually evolve

applicationsarxiv-cs-lg

Towards Structuring an Arabic-English Machine-Readable Dictionary Using Parsing Expression Grammars

arXiv:2606.25231v1 Announce Type: new Abstract: Dictionaries are rich sources of lexical information about words that is required for many applications of natural language processing and human languag

Towards Understanding The Calibration Benefits of Sharpness-Aware Minimization

arXiv:2505.23866v2 Announce Type: replace Abstract: Deep neural networks have been increasingly used in safety-critical applications such as medical diagnosis and autonomous driving. However, many stu