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arXiv:2602.18905v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated strong capabilities in complex reasoning tasks, yet their decision-making processes remain diff

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Model Releases

TSAQA: Time Series Analysis Question And Answering Benchmark

DGX agent

arXiv:2601.23204v2 Announce Type: replace Abstract: Time series data are integral to critical applications across domains such as finance, healthcare, transportation, and environmental science. While

model-releasesarxiv-cs-ai

8 Jun 2026

Tutorials

Twelve quick tips for designing AI-driven HPC workflows

arXiv:2606.07491v1 Announce Type: cross Abstract: High-performance computing (HPC) clusters remain the backbone of large-scale scientific computation, traditionally executing deterministic, linear pip

tutorialsarxiv-cs-ai

Twin: Tuning Learning Rate and Weight Decay of Deep Homogeneous Classifiers without Validation

arXiv:2403.05532v2 Announce Type: replace-cross Abstract: We introduce Tune without Validation (Twin), a simple and effective pipeline for tuning learning rate and weight decay of homogeneous classifi

Uncertainty-Aware LLM-Guided Policy Shaping for Sparse-Reward Reinforcement Learning

arXiv:2606.06673v1 Announce Type: new Abstract: Sparse rewards and heterogeneous task sequences remain persistent challenges in Reinforcement Learning (RL), often resulting in slow convergence, weak g

Uncertainty-Guided Label Rebalancing for CPS Safety Monitoring

arXiv:2603.25670v3 Announce Type: replace Abstract: Safety monitoring is essential for Cyber-Physical Systems (CPSs). However, unsafe events are rare in real-world CPS operations, creating an extreme

Understanding Generative Recommendation with Semantic IDs from a Model-scaling View

arXiv:2509.25522v3 Announce Type: replace Abstract: Recent advancements in generative models have allowed the emergence of a promising paradigm for recommender systems (RS), known as Generative Recomm

Unified Geometry-Guided ML-FTLE for Tracking Transient Chaos from Scalar Time Series

arXiv:2606.07385v1 Announce Type: cross Abstract: Detecting transient chaos from scalar observations without governing equations represents a fundamental challenge in nonlinear dynamics. We propose a

researcharxiv-cs-lg

Unified Safe In-context Image Generation in Multimodal Diffusion Transformers via Restricting Unsafe Information Flows

arXiv:2606.06875v1 Announce Type: new Abstract: Diffusion transformers (DiTs) equipped with multimodal attention (MM-Attn) have become a dominant paradigm for image generation. However, preventing the

safetyarxiv-cs-cv

Uniform Stability and Generalization Error of GD and SGD on Fixed-Point Parameters

arXiv:2606.06934v1 Announce Type: new Abstract: We analyze generalization error, uniform stability, and uniform argument stability of gradient descent (GD) and stochastic gradient descent (SGD) over d

UniSHARP: Universal Sharp Monocular View Synthesis

arXiv:2606.07514v1 Announce Type: new Abstract: In this work, we focus on extending SHARP, the popular photorealistic view synthesis method, for universal monocular rendering across a continuum of cam

Universal consistency of the k-NN rule in metric spaces and Nagata dimension. III

arXiv:2512.17058v3 Announce Type: replace Abstract: We establish the last missing link allowing to describe those complete separable metric spaces X in which the k nearest neighbour classifier is univ

researcharxiv-cs-lg

Unmixing ATR-{mu}FTIR spectroscopic images of cross-sections of historical oil paintings

arXiv:2603.06673v2 Announce Type: replace Abstract: Spectroscopic imaging (SI) has become central to heritage science because it enables non-invasive, spatially resolved characterisation of materials

UnpredictaBench: A Benchmark for Evaluating Distributional Randomness in LLMs

model-releasesarxiv-cs-cl

arXiv:2606.06622v1 Announce Type: new Abstract: We introduce UnpredictaBench, an evaluation that tests the ability of large language models (LLMs) to capture true underlying distributions. As LLMs are

Unregistered Spectral Image Fusion: Unmixing, Adversarial Learning, and Recoverability

arXiv:2603.21510v3 Announce Type: replace-cross Abstract: This paper addresses the fusion of a pair of spatially unregistered hyperspectral image (HSI) and multispectral image (MSI) covering roughly o

Unsupervised Continual Clustering via Forward-Backward Knowledge Distillation

arXiv:2606.07474v1 Announce Type: new Abstract: Unsupervised Continual Learning (UCL) aims to enable neural networks to learn sequential tasks without labels or access to past data. A major challenge

Unsupervised Learning Based Focal Stack Camera Depth Estimation

arXiv:2203.07904v3 Announce Type: replace-cross Abstract: We propose an unsupervised deep learning based method to estimate depth from focal stack camera images. On the NYU-v2 dataset, our method achi

UrduMMLU: A Massive Multitask Benchmark for Urdu Language Understanding

arXiv:2606.07167v1 Announce Type: cross Abstract: Meaningful multilingual evaluation must test models in the target language and educational context. Urdu, spoken by more than 230 million people, lack

Applications

USU-Corn-WeedDB: A UAV RGB Image Dataset for Multi-Species Weed Detection in Forage Corn

arXiv:2606.06709v1 Announce Type: new Abstract: Weed pressure in forage corn production causes yield losses of up to 31.5%, yet site-specific weed management (SSWM) systems built on UAV imagery and de

applicationsarxiv-cs-cv

VALUEFLOW: Toward Pluralistic and Steerable Value-based Alignment in Large Language Models

arXiv:2602.03160v2 Announce Type: replace Abstract: Aligning Large Language Models (LLMs) with the diverse spectrum of human values remains a central challenge: preference-based methods often fail to

Varifold Moment Invariants for Sustainable and Explainable Contour Feature Extraction

arXiv:2606.07333v1 Announce Type: new Abstract: We introduce Varifold Moments Invariants (VMI) as a unifying framework for many previously introduced Moment Invariants. These invariants are deeply rel

VeriDrive: Verifiable Counterfactual Supervision for Cost-Efficient Vision-Language Planning

arXiv:2606.07338v1 Announce Type: new Abstract: Vision-language driving models increasingly use reasoning supervision to bridge perception, prediction, and planning, but existing driving rationales ar

Video-Based Prediction of In-Flight Particle Characteristics in Atmospheric Plasma Spraying

arXiv:2606.07416v1 Announce Type: new Abstract: Atmospheric plasma spraying (APS) is a widely used coating process in which in-flight particle temperature and velocity strongly influence coating quali

researcharxiv-cs-lg

VideoSEG-O3: A Multi-turn Reinforcement Learning Framework for Reasoning Video Object Segmentation

arXiv:2606.06819v1 Announce Type: new Abstract: Reasoning Video Object Segmentation (RVOS) demands a sophisticated integration of temporal dynamics, spatial details, and linguistic reasoning to achiev

Hardware

VIRTUS-FPP: Virtual Sensor Modeling for Fringe Projection Profilometry in NVIDIA Isaac Sim

arXiv:2509.22685v2 Announce Type: replace-cross Abstract: Fringe projection profilometry (FPP) is a high-precision structured-light sensing technique for 3D surface reconstruction, yet its practical d

hardwarearxiv-cs-cv

Watch, Remember, Reason: Human-View Video Understanding with MLLMs

arXiv:2606.07433v1 Announce Type: cross Abstract: Video understanding is being rapidly transformed by multimodal large language models (MLLMs), as research moves from short clips to long, multimodal,

WAV: Multi-Resolution Block Residual Routing for Deep Decoder-Only Transformers

arXiv:2606.06564v1 Announce Type: cross Abstract: Residual connections are central to training deep Transformers, but standard PreNorm residual streams aggregate sublayer updates with fixed unit weigh

What Do People Actually Want From AI? Mapping Preference Plurality

arXiv:2606.06674v1 Announce Type: new Abstract: Large Language Models (LLMs) are often fine-tuned through Reinforcement Learning from Human Feedback (RLHF) to align with people's preferences and value

safetyarxiv-cs-cl

What Is My Robot Thinking? Design Considerations for Transparent and Trustworthy Shared Autonomy

arXiv:2606.06870v1 Announce Type: new Abstract: Assistive robots operating under shared autonomy must balance user control with autonomous assistance. Because robot actions depend on internal intent i

safetyarxiv-cs-ro

What Matters When Cotraining Robot Manipulation Policies on Everyday Human Videos?

arXiv:2606.06627v1 Announce Type: cross Abstract: Human video datasets used for cotraining robot manipulation policies largely consist of curated demonstrations where motions are orchestrated to resem

What Your Posts Reveal: A Benchmark and Agentic Framework for User-Level Privacy Leakage on Social Media

arXiv:2606.06784v1 Announce Type: cross Abstract: Public social media posts can reveal private information through weak cues scattered across text, images, or metadata. Such leakage is often cumulativ

When Better Codebooks Are Not Enough: Predictive Performance and Behavioral Reliability in LLM Political Event Coding

arXiv:2606.06781v1 Announce Type: new Abstract: High accuracy does not necessarily make an LLM a faithful coder. This issue matters because many social-science studies rely on expert-written codebooks

researcharxiv-cs-cl

When CLIP Sees More, It Fights Back Harder: Multi-View Guided Adaptive Counterattacks for Test-Time Adversarial Robustness

arXiv:2606.06938v1 Announce Type: new Abstract: Vision-language models such as CLIP have achieved remarkable zero-shot recognition capabilities, yet their robustness against adversarial perturbations

Agents

When Does Multi-Agent Collaboration Help? An Entropy Perspective

arXiv:2602.04234v6 Announce Type: cross Abstract: Multi-agent systems (MAS) have emerged as a prominent paradigm for leveraging large language models (LLMs) to tackle complex tasks. However, the mecha

agentsarxiv-cs-ai

When is 3D Worth It? A Resource-Performance Frontier for CNNs and Transformers in Lung CT

arXiv:2606.06950v1 Announce Type: cross Abstract: Three-dimensional models are widely assumed preferable for volumetric medical imaging, yet their practical value depends on whether performance gains

When Large Language Models Fail in Healthcare: Evaluating Sensitivity to Prompt Variations

arXiv:2606.07237v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in healthcare for tasks such as clinical question answering, diagnosis support, and report summariz

When Recovery Matters: The Blind Spot of Surrogate Privacy in MLLM Editing

arXiv:2606.07171v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) enable flexible instruction-driven image editing, but privacy risks arise when user images expose diverse and u

When to Think Deeply: Inhibitory Deliberation for LLM Reasoning

model-releasesarxiv-cs-cl

arXiv:2606.06745v1 Announce Type: new Abstract: Reasoning Large Language Models can improve problem-solving performance through deliberative inference, but invoking slow reasoning for every input is c

Where Rectified Flows Leak: Characterising Membership Signals Along the Interpolation Path

arXiv:2606.07271v1 Announce Type: cross Abstract: Understanding what generative models retain from training data remains challenging, with implications for copyright and privacy. Beyond verbatim repro

Where to Touch, How to Contact: Hierarchical RL-MPC Framework for Geometry-Aware Long-Horizon Dexterous Manipulation

arXiv:2601.10930v3 Announce Type: replace Abstract: A key challenge in contact-rich dexterous manipulation is the need to jointly reason over global geometry and nonsmooth contact dynamics. End-to-end

safetyarxiv-cs-ro

Which Anatomy Matters Under Limited Labels? A Data-Efficient Anatomy-Aware Benchmark for Cardiac Pathology Prediction

arXiv:2606.06509v1 Announce Type: cross Abstract: Numerous medical imaging problems must be solved under limited labels and constrained compute, yet it remains unclear whether performance gains are dr

Whisper Hallucination Detection and Mitigation via Hidden Representation Steering and Sparse AutoEncoders

arXiv:2606.07473v1 Announce Type: cross Abstract: Whisper, a widely adopted ASR model, is known to suffer from hallucinations - coherent transcriptions generated for non-speech audio entirely disconne

Workflow-to-Skill: Skill Creation via Routing-Workflow-Semantics-Attachments Decomposition

arXiv:2606.06893v1 Announce Type: new Abstract: Large language model agents increasingly rely on Skills to encode procedural knowledge, yet high-quality Skills remain costly to hand-write. This paper

WorldBench: A Challenging and Visually Diverse Multimodal Reasoning Benchmark

arXiv:2606.06538v1 Announce Type: new Abstract: In real-world applications, models are expected to perform reliably across diverse settings. Yet, many existing multimodal benchmarks expand task types

Your UnEmbedding Matrix is Secretly a Feature Lens for Text Embeddings

arXiv:2606.07502v1 Announce Type: new Abstract: Large language models exhibit impressive zero-shot capabilities across a wide range of downstream tasks. However, they struggle to function as off-the-s

researcharxiv-cs-cl

Zero-Shot Embedding Drift Detection: A Lightweight Defense Against Prompt Injections in LLMs

arXiv:2601.12359v1 Announce Type: cross Abstract: Prompt injection attacks have become an increasing vulnerability for LLM applications, where adversarial prompts exploit indirect input channels such

Zero-Shot Polygon Matching with Pre-trained Models for Pose Estimation and Polygon Cloud from Challenging Stereo

arXiv:2511.05949v2 Announce Type: replace Abstract: While stereo matching has achieved maturity for 0D point and 1D line primitives, establishing correspondences for 2D polygons remains largely unexpl

Agents

2-Step Agent: A Framework for the Interaction of a Decision Maker with AI Decision Support