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arXiv:2608.20025v1 Announce Type: new Abstract: Probabilistic forecasting models are widely used for time series forecasting in domains such as energy systems, finance, medicine, and transportation. I

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Clustering and Token Denoising for Faster and More Robust VLMs

DGX agent

arXiv:2608.19285v1 Announce Type: new Abstract: Recent Visual-Language Models (VLMs) have enhanced the capabilities of pre-trained LLMs by adding vision tokens alongside text, with approaches like LLa

applicationsarxiv-cs-cv

21 Aug 2026

Complementary, Not Cumulative: Interaction Effects in Physics-Informed Neural Networks for Navier-Stokes Vortex Shedding

arXiv:2608.19632v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) embed governing partial differential equations directly into the training loss, offering a promising alternativ

Concentrated Liquidity Provision: a Reinforcement Learning Perspective

arXiv:2608.19389v1 Announce Type: cross Abstract: Automated market makers (AMMs) are a cornerstone of decentralised finance (DeFi). Constant product markets with concentrated liquidity, such as Uniswa

Daedalus-150M: A Convolution-Attention Hybrid Designed for CPU Inference

arXiv:2608.20210v1 Announce Type: cross Abstract: Small language models are usually built like large ones and then squeezed onto a CPU afterwards. We did the opposite: we fixed the target first, one u

Local Ai

DARS: Dual-Level Credit Assignment RL with Structured Reasoning for Instruction-Based Image Editing

arXiv:2608.20161v1 Announce Type: new Abstract: Instruction-based image editing uses a planner-renderer pipeline: a vision-language model (VLM) first converts the instruction into an edit plan, and a

local-aiarxiv-cs-ai

Applications

DecoVAE: a Lightweight Interpretable Trend-Seasonal VAE Framework for Efficient Probabilistic Time Series Forecasting

arXiv:2608.20052v1 Announce Type: new Abstract: Probabilistic time series forecasting remains challenging, largely because modeling distinct trend and seasonal dynamics requires specialized approaches

applicationsarxiv-cs-lg

DICS: Data-Informed Centroid Splitting for Decision Tree Classifiers

arXiv:2608.20258v1 Announce Type: new Abstract: Decision tree-based models are widely used in machine learning due to their interpretability and strong empirical performance. However, training decisio

DIFFCZSL: Compositional Zero-Shot Learning Regularized by Diffusion Representations

arXiv:2608.19871v1 Announce Type: new Abstract: Compositional Zero-Shot Learning (CZSL) aims to recognize unseen attribute-object compositions by leveraging knowledge of primitive concepts learned fro

Tutorials

DPC-Net: Dual-Prior Collaborative Network for All-in-One Image Restoration

arXiv:2608.20141v1 Announce Type: new Abstract: All-in-One Image Restoration (AiOIR) aims to handle diverse degradations within a unified model. However, existing methods often overlook image semantic

tutorialsarxiv-cs-cv

DreamHand: Repurposing Video Diffusion Models for Occlusion-Robust Egocentric 3D Hand Motion Recovery

arXiv:2608.20308v1 Announce Type: new Abstract: Egocentric video offers scalable manipulation data for embodied AI, yet recovering metric 3D hand trajectories remains challenging due to severe object

researcharxiv-cs-cv

Empirical Characterization of Learning Geometry in Hybrid Quantum Forecasting Models

arXiv:2608.19497v1 Announce Type: new Abstract: We characterize the learning dynamics of a compact hybrid quantum forecasting model through comparison with a structurally aligned classical baseline. U

safetyarxiv-cs-lg

Enforcing LLM Safety through DMD-based Classification of Prompt-Response Embedding Dynamics

arXiv:2608.19579v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in high-stakes applications, yet their tendency to generate toxic, harmful, or policy-violating c

EnvHarness: Awakening Static Worlds for Agent Learning

arXiv:2608.19880v1 Announce Type: new Abstract: LLM agents learn by interacting with environments, yet these environments are hand-built and static: blind to an agent's weaknesses, and quickly left be

safetyarxiv-cs-ai

Evaluating Neural Cartographic Relief Shading for Urban Environments: A Downtown Calgary Study Using High-Resolution DEM and DSM Data

arXiv:2608.20149v1 Announce Type: new Abstract: This article explores the performance of analytical and neural-based hillshading methods in a dense urban environment using high-resolution digital elev

Evidence Before Expansion: Reuse, Spawn, or Defer in Lifelong Expert Pools

arXiv:2608.19888v1 Announce Type: cross Abstract: Streaming systems that maintain a pool of expert models must repeatedly decide whether to reuse an existing expert for arriving data, spawn a new one,

FAR-DPO: Feasibility-Aware and Robust Direct Preference Optimization for Cyclic Peptide Design

arXiv:2608.19808v1 Announce Type: new Abstract: Cyclic peptides are emerging as promising molecular scaffolds in drug discovery due to their high binding affinity and structural stability. However, ex

Far from the Crowd: Scalable Self-Supervised Learning via Geographic Isolation

arXiv:2608.19766v1 Announce Type: new Abstract: Self-supervised pretraining on remote sensing imagery typically treats all samples as equally informative, despite large variability in geographic and v

researcharxiv-cs-cv

Fine-Tuning VLAs with Self-Demonstrated Generative Control for Multi-Task Manipulation

model-releasesarxiv-cs-cv

arXiv:2608.19490v1 Announce Type: cross Abstract: State-of-the-art vision-language-action (VLA) models such as pi_{0.5} exhibit strong semantic understanding, instruction following and task behavior.

Gallileo-4D: Frozen Backbone Ensemble for Dynamic 4D Reconstruction

model-releasesarxiv-cs-cv

arXiv:2608.19743v1 Announce Type: new Abstract: We describe our entry to the PhysAI Dynamic 4D Reconstruction Challenge, which placed third of 27 teams at 0.58356 APD on the final leaderboard, without

GridCodex: A RAG-Driven AI Framework for Power Grid Code Reasoning and Compliance

arXiv:2508.12682v2 Announce Type: replace Abstract: The global shift towards renewable energy presents unprecedented challenges for the electricity industry, making regulatory reasoning and compliance

researcharxiv-cs-ai

Interpretable Feature Learning for RF Fingerprinting via Polar MKANs

arXiv:2608.19881v1 Announce Type: cross Abstract: Radio frequency (RF) fingerprinting authenticates wireless devices from hardware-induced I/Q impairments, typically with deep learning feature extract

Learning piecewise-smooth dynamical systems

arXiv:2608.19785v1 Announce Type: cross Abstract: Discovering dynamical systems from trajectory data is a central problem in applied mathematics and engineering. Whilst recent advances in machine lear

Learning When to Think: Adaptive Reasoning for Test-Time Compute Allocation

arXiv:2608.20256v1 Announce Type: new Abstract: Reasoning language models trained with reinforcement learning typically operate under a fixed token budget rather than an explicitly adaptive one, which

safetyarxiv-cs-ai

Tutorials

Listening Forward: Next Patch Embedding Prediction Enables Scalable Audio Learners

arXiv:2608.19863v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has driven substantial progress in audio representation learning, though existing methods have increasingly relied on e

tutorialsarxiv-cs-ai

LoRA-GA^2: Low Rank Adaptation with Multi-step Gradient Adaptive Alignment

arXiv:2608.19800v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) is a prominent fine-tuning method for large models, achieving competitive performance with reduced memory overhead. However

Manifold Drift in Flow Preference Optimization: A Root Cause of Reward Hacking

arXiv:2608.20011v1 Announce Type: new Abstract: Preference optimization is a standard alignment method for generative models, yet extending it to continuous-time dynamics remains non-trivial. In flow

MOSAIC: Modality-agnostic Spectral Alignment for Federated Image-level Weakly Supervised Tumor Segmentation under Client-specific Missing Modalities

arXiv:2608.19788v1 Announce Type: cross Abstract: Trustworthy multimodal fusion in clinical settings requires handling incomplete and heterogeneous modality subsets across institutions, where privacy

Multi-Source Wasserstein Distributionally Robust Graph Learning

arXiv:2608.19914v1 Announce Type: new Abstract: Network topology inference from graph signals is central to graph signal processing with applications in neuroscience, sensor, and social networks. In p

safetyarxiv-cs-lg

Pandora's AI Model Routing Box: Efficient Allocation with Costly Value Estimation

arXiv:2608.20316v1 Announce Type: new Abstract: Heterogeneous AI systems composed of multiple models, architectures, harnesses, or inference-time settings can improve quality and efficiency by routing

PEA-DPO: Perception-Enhanced Alignment Direct Preference Optimization for MLLMs Alignment

arXiv:2608.19598v1 Announce Type: cross Abstract: Direct Preference Optimization (DPO) has emerged as an effective approach for aligning large language models (LLMs) with human preferences. However, i

safetyarxiv-cs-ai

PETA:Parameter-Efficient Test-Time Adaptation for Virtual Screening

arXiv:2608.19906v1 Announce Type: new Abstract: Accurately ranking active ligands for a target protein pocket from massive chemical libraries remains a central challenge in virtual screening. DrugCLIP

Local Ai

Prompt-Conditioned Channel Attention for Hierarchical Feature Modulation toward Anatomy-Agnostic Segmentation

arXiv:2608.20229v1 Announce Type: cross Abstract: Anatomically plausible segmentation remains challenging because of low contrast, ambiguous boundaries, and modality-specific artifacts. Interactive se

local-aiarxiv-cs-ai

ProteinZero: Self-Improving Protein Generation via Online Reinforcement Learning

arXiv:2506.07459v4 Announce Type: replace Abstract: Protein generative models have shown remarkable promise in protein design, yet their success rates remain constrained by reliance on curated sequenc

Quantum Gaussian processes for prediction of channel observations

arXiv:2608.19306v1 Announce Type: cross Abstract: Given a set of input states, we consider the task of predicting the expectation value of a Pauli observable at the output of an unknown quantum evolut

Reading Between the Pixels: An Inscriptive Jailbreak Attack on Text-to-Image Models

arXiv:2604.05853v3 Announce Type: replace Abstract: Modern text-to-image (T2I) models can now render legible, paragraph-length text, enabling a fundamentally new class of misuse. We identify and forma

ReCache: Efficient KV Cache Reuse and Compression for Tool-Augmented LLM Agents

model-releasesarxiv-cs-cl

arXiv:2608.19662v1 Announce Type: new Abstract: Agentic language models repeatedly encode tool and skill schemas that recur across requests in different combinations and orders, preventing standard pr

RecPFN: Prior-Fitted Networks for In-Context-Based Recommendations

arXiv:2608.19735v1 Announce Type: new Abstract: We introduce RecPFN, a prior-fitted network that brings in-context learning to sequential recommendation. RecPFN is pretrained entirely on synthetic cli

researcharxiv-cs-lg

Reliable Neural Collapse Approximation for Open-World Test-Time Adaptation

arXiv:2608.19890v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) methods aim to bridge the domain gap between the source and target domains. However, traditional TTA methods become ineffecti

researcharxiv-cs-lg

Rethinking the Evaluation and Optimization of LLM-Based Social Simulation

arXiv:2608.19689v1 Announce Type: new Abstract: LLM-based social simulation is a promising complement to traditional methods such as surveys and behavioral experiments. A core question is how to evalu

ReynoldsFlow: Physics-Inspired Spatiotemporal Flow Representation for Video Understanding

arXiv:2503.04500v3 Announce Type: replace-cross Abstract: Video understanding has largely relied on deep spatiotemporal architectures, including 3D convolutional networks and optical flow (OF) based m

researcharxiv-cs-ai

Tutorials

RIPE++: Reinforced Keypoint Learning from Positive Pairs Only

arXiv:2608.19693v1 Announce Type: new Abstract: Sparse keypoint extraction and matching underpin core tasks in geometric computer vision, including structure-from-motion, visual SLAM, augmented realit

tutorialsarxiv-cs-cv

ROBOSHACKLES: A Safety Dataset for Human-Injury Prevention in Embodied Foundation Models

model-releasesarxiv-cs-ro

arXiv:2606.18632v2 Announce Type: replace Abstract: Embodied Foundation Models (EFMs) integrate multimodal understanding, future-state reasoning, and executable robot actions. Yet their safety alignme

RoMAN-Flow: Taming Autoregressive Normalizing Flows for Offline Reinforcement Learning in Robotic Manipulation

arXiv:2608.20208v1 Announce Type: new Abstract: Offline reinforcement learning improves robotic policies using previously collected data without further environment interaction. Yet prevalent diffusio

Scaffolding Minds: Optimizing Latent Visual Target Representations for Multimodal Reasoning

arXiv:2608.19669v1 Announce Type: new Abstract: Latent reasoning has advanced multimodal reasoning through a two-stage training paradigm: (1) a helper image is encoded into latent tokens to teach visu

Scale-Aware Pretraining of Time Series Foundation Models via Multi-Patch Token Alignment and Hybrid Masking

arXiv:2608.20005v1 Announce Type: new Abstract: Pretraining time series foundation models across heterogeneous datasets necessitates effective handling of varying sampling frequencies. Current methods

safetyarxiv-cs-lg

Scale-Separated Conditioning for Style-Encoder-Free Diffusion Stylization

arXiv:2608.19719v1 Announce Type: cross Abstract: Reference-based diffusion stylization requires separating target geometry from transferable appearance. Existing tuning-based methods often rely on al

Separating Covariate Shift from Mechanism Change with Two Discriminators: CJSD, a Conditional Discrepancy with an Exact Covariate-Concept Decomposition

arXiv:2608.19885v1 Announce Type: cross Abstract: Streaming systems that maintain a pool of expert models must repeatedly decide whether to reuse an existing expert for arriving data, spawn a new one,