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On the Fragility of Self-Improving Agents: Variance, Task Order, and Underspecification

arXiv:2608.18066v1 Announce Type: new Abstract: Memory-based self-improving agents--those that learn from an online stream of tasks and improve over time by maintaining a textual memory bank--have sho

agentsarxiv-cs-ai

On the Pseudo-Mixing of Kac's Walk

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DGX agent

arXiv:2608.17374v1 Announce Type: cross Abstract: Motivated by a conjecture of Vaikuntanathan and Zamir, we study the pseudo-mixing of Kac's walk on SO(n): whether short trajectories are indistinguish

researcharxiv-cs-lg

19 Aug 2026

One Pipeline, Many Transformers: Pattern-Specific Imputation Specialists for Tabular Missing Data

arXiv:2510.02625v5 Announce Type: replace Abstract: Missing data in tabular datasets forces practitioners into a hard choice: deploy a general-purpose imputer that may perform poorly for the problem a

Online Generalized Sparse Regression: How Does Overparametrization Help?

arXiv:2608.17466v1 Announce Type: cross Abstract: Regularized sparse regression has been extensively studied in the offline setting, but online formulation remains relatively under-explored. This gap

OOD Detection for EEG-based Machine Learning in High-Risk Environments

arXiv:2608.17620v1 Announce Type: new Abstract: Machine learning models for electroencephalography (EEG) analysis show great promise across a wide range of applications, but their deployment in high-r

Optimal control of a swimming robot based on Purcell's microswimmer model

arXiv:2608.17455v1 Announce Type: cross Abstract: Purcell's swimmer is a well-known planar model of a swimming microorganism, governed by low Reynolds number hydrodynamics, which is comprised of three

researcharxiv-cs-ro

Optimize Your Sampling: Tuned Diffusion Sampling with Bayesian Optimization

arXiv:2608.18040v1 Announce Type: cross Abstract: Sampling from a diffusion model typically requires many forward passes through a large neural network, making generation computationally expensive. Wh

Optimizing Container Loading and Unloading through Dual-Cycling and Dockyard Rehandle Reduction Using a Hybrid Genetic Algorithm

arXiv:2406.08534v4 Announce Type: replace-cross Abstract: This paper addresses the NP-hard problem of optimizing container handling at ports by integrating Quay Crane Dual-Cycling (QCDC) and dockyard

OraclePhys: A Systematic Framework for LLM Fine-Tuning on Structural Mechanics

arXiv:2608.17162v1 Announce Type: new Abstract: What a language model internalizes from fine-tuning is usually diagnosed after the fact. We make it an experimental variable. OraclePhys is a systematic

ORPA: Online Residual Policy Adaptation for Robot Manipulation Control with Human Feedback

arXiv:2608.17323v1 Announce Type: cross Abstract: Robotic manipulation policies trained via imitation learning, such as Action Chunking with Transformers (ACT), can achieve strong performance under id

ORViT-DR: Ordinally-Robust Hybrid ViT for Low-Resolution Diabetic Retinopathy Grading

arXiv:2608.16958v1 Announce Type: cross Abstract: Diabetic retinopathy (DR) is one of the main causes of impaired vision. A good and reliable automated grading system can make the screening process sa

OV3D-Bench: A Diagnostic Benchmark for Open-Vocabulary Monocular 3D Detection

arXiv:2608.17110v1 Announce Type: new Abstract: Open-vocabulary monocular 3D detectors report strong in-domain performance, but each evaluates under a different protocol, several rely on per-image cat

Applications

OVIP-SG: Open-Vocabulary Instance-Preserving Scene Graphs for Mapping and Retrieval of Small, Fine-Grained Objects

arXiv:2608.17633v1 Announce Type: new Abstract: Integrating open-vocabulary perception into object-level 3D scene graphs is a double-edged sword. While vision-language detectors recover long-tail cate

applicationsarxiv-cs-ro

PACE: Policy-Attested Contract Execution for Safe AI Agents in Decentralized Finance

model-releasesarxiv-cs-ai

arXiv:2608.17220v1 Announce Type: cross Abstract: Autonomous AI agents are emerging as interfaces for decentralized finance (DeFi) actions such as swaps, lending operations, and yield management. Beca

Hardware

Parallel Branch Model Predictive Control on GPUs

arXiv:2506.13624v2 Announce Type: replace-cross Abstract: We present a GPU-based solver for trajectory planning problems using branch Model Predictive Control. Building on iterative LQR methods, we ad

hardwarearxiv-cs-ro

Parametric Knowledge in RAG-SFT for Domain-Specific Document Generation

arXiv:2603.23047v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) fine-tuning has shown substantial improvements over vanilla RAG, yet most studies target document questio

PathoArgus: Advancing Evidence-Grounded Long-Context Visual Reasoning across Gigapixel Whole-Slide and Multi-Slide Case Contexts

arXiv:2608.17607v1 Announce Type: new Abstract: Whole-slide pathology reasoning requires models to integrate gigapixel-scale visual evidence across complete case-linked slides, yet current question-an

Pathology Transport: Optimal-Transport Explanations for Clinical Data, and When Their Heatmaps (Fail to) Localize Disease

arXiv:2608.17370v1 Announce Type: new Abstract: Generative models promise a route to explainable clinical AI: rather than probe a classifier, model the distributions of healthy and diseased patients a

PDDL-ART: Autonomous Symbolic Abstraction From Demonstration For Long-Horizon Robotic Manipulation Using Vision-Language Models

arXiv:2608.17146v1 Announce Type: new Abstract: Symbolic planning with PDDL offers a principled framework for long-horizon robot manipulation, but constructing accurate PDDL domain and problem descrip

agentsarxiv-cs-ro

PerFact: Perception-Derived Fact Prompting for 3D Brain MRI Report Generation

arXiv:2608.17926v1 Announce Type: new Abstract: Radiology report generation has matured almost entirely on 2D chest radiographs, where the default route to better reports is a larger backbone or a pre

Pessimistic Meta-Induction and Its Limits: Lessons from Frequentist Statistics and Machine Learning Theory

arXiv:2608.17213v1 Announce Type: new Abstract: This paper challenges the pessimistic meta-inductive argument against scientific realism by undermining its inductive step rather than its historical pr

researcharxiv-cs-lg

Applications

Physics-Informed and Hybrid Machine Learning in Additive Manufacturing: Application to Fused Filament Fabrication

arXiv:2608.17246v1 Announce Type: new Abstract: This article investigates several physics-informed and hybrid machine learning strategies that incorporate physics knowledge in experimental data-driven

applicationsarxiv-cs-lg

Physics-Informed Sliding-Window Particle Filtering for Tactile-Only In-Hand 6-DoF Object Pose Refinement

arXiv:2608.17601v1 Announce Type: new Abstract: This paper studies tactile-only 6-DoF pose refinement and belief maintenance for grasped objects in static and short quasi-static in-hand configurations

safetyarxiv-cs-ro

Hardware

Picard Proximal Monte Carlo for Parallel Bayesian Imaging with Score-Based Generative Priors

arXiv:2608.17666v1 Announce Type: new Abstract: Bayesian imaging inverse problems often require sampling from high-dimensional posterior distributions. While recent score-based and diffusion models pr

hardwarearxiv-cs-lg

Picture the Epsilon: Pursuing Identity-Level Privacy Guarantees for Images

arXiv:2608.17147v1 Announce Type: cross Abstract: Image-to-image face generators are widely used, and visual dissimilarity between their outputs and source images is sometimes treated as evidence of p

PlanPO: Group Planning-Aware Policy Optimization for Multi-Turn Agentic LLMs

arXiv:2608.17289v1 Announce Type: new Abstract: Group-relative policy optimization has emerged as a key paradigm for training agentic large language models (LLMs) on multi-turn interactive tasks. Howe

Plug-and-Play Traffic Element Awareness for End-to-End Autonomous Driving

arXiv:2608.18035v1 Announce Type: new Abstract: Traffic elements such as traffic lights and road signs play a fundamental role in human driving decisions and should naturally influence end-to-end driv

Polaris: Learning to Generate Table Descriptions from Retrieval Feedback

arXiv:2608.17171v1 Announce Type: new Abstract: Many table-centric NLP tasks such as NL2SQL first retrieve relevant tables from large collections using keyword search. Recent work uses LLMs to generat

researcharxiv-cs-cl

Policy-Invariant Reward Shaping from LLM Feedback: A Framework for Hybrid RL Agents

arXiv:2608.18008v1 Announce Type: cross Abstract: Combining large language models with reinforcement learning is increasingly explored, yet the theoretical status of LLM-derived reward signals is ofte

Policy Optimization and Statistical Inference for Online Contextual Matrix Games

arXiv:2608.17173v1 Announce Type: cross Abstract: Online decision making often requires navigating a landscape shaped by both dynamic contexts and strategic interactions. In competitive pricing, for e

Population Health-Based Machine Learning Reveals Associations Between Psychosocial Factors and Chronic Kidney Disease

arXiv:2608.17174v1 Announce Type: new Abstract: Chronic kidney disease (CKD) progresses silently and severely undermines quality of life, making early detection critical for improving patient outcomes

researcharxiv-cs-lg

Position: Fairness Failure in Generative Models is an Evaluation Problem

arXiv:2608.16974v1 Announce Type: cross Abstract: Despite groundbreaking advancements in generative models during the last decade, concerns about their lack of fairness, reinforcing societal inequalit

Potential of ChatGPT in predicting stock market trends based on Twitter Sentiment Analysis

arXiv:2311.06273v1 Announce Type: cross Abstract: The rise of ChatGPT has brought a notable shift to the AI sector, with its exceptional conversational skills and deep grasp of language. Recognizing i

Local Ai

Predicting Male Domestic Violence Using Explainable Ensemble Learning and Exploratory Data Analysis

arXiv:2403.15594v4 Announce Type: replace-cross Abstract: Domestic violence is commonly viewed as a gendered issue that primarily affects women, which tends to leave male victims largely overlooked. T

local-aiarxiv-cs-lg

Preference Is Not Intervention: The Structure and Stability Boundaries of Reader-Specific Evidence Utility

arXiv:2608.17781v1 Announce Type: new Abstract: ML systems increasingly condition decisions on downstream model identity, but this is useful only if model-specific differences form reusable structure

researcharxiv-cs-cl

Primitive-Driven Compositional Forensic Visual Prompting for Open-World Face Anti-Spoofing

arXiv:2608.17351v1 Announce Type: new Abstract: Open-world face anti-spoofing must address both covariate and semantic shifts: source and target domains differ in imaging conditions, while target doma

Primitive Representation Learning for Unsupervised Dynamic Contrast Enhanced MRI Reconstruction

arXiv:2608.18055v1 Announce Type: cross Abstract: Reliable quantitative analysis of dynamic contrast-enhanced MRI requires high-quality spatiotemporal reconstructions at high undersampling rates. Scan

Prism-GRPO: Faster VLA Policy Optimization via Splitting Same-outcome Groups

arXiv:2608.17423v1 Announce Type: new Abstract: GRPO is increasingly used for reinforcement learning of vision-language-action (VLA) policies because, unlike PPO, it does not require training a critic

safetyarxiv-cs-ro

PRISM: Precision and contact-rich Real-world Industrial Skill dataset with Multimodal sensing

model-releasesarxiv-cs-ro

arXiv:2608.17962v1 Announce Type: new Abstract: Recent progress in robotic learning has been fueled by large-scale datasets collected in everyday environments. However, most existing datasets emphasiz

PrivAct: Internalizing Contextual Privacy Preservation via Multi-Agent Preference Training

arXiv:2602.13840v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly deployed in personalized tasks involving sensitive, context-dependent information, where privacy

agentsarxiv-cs-cl

Proactive Road Safety Intervention in Australia: Predicting Risky Driving Hotspots from Connected Vehicle Data

arXiv:2608.16913v1 Announce Type: new Abstract: Road safety monitoring has historically been reactive, relying on crash-record analysis after fatalities and injuries have already occurred. Proactive i

safetyarxiv-cs-lg

PROBE: Manipulation-Grounded Visual Question Answering with VLM Agents

arXiv:2608.17129v1 Announce Type: new Abstract: Vision-language Models (VLMs) excel at 2D grounding, spatial reasoning and agentic tool-based planning in static scenes. However, consider asking a home

agentsarxiv-cs-cv

Probing Association Instability with Track-State Perturbations for Clip-Level Active Learning in Query-Propagation Multi-Object Tracking

arXiv:2608.17224v1 Announce Type: new Abstract: Training query-propagation end-to-end multi-object tracking (MOT) models requires dense bounding-box and identity annotations across video sequences, ma

Probing the Prefill: Detecting Code Vulnerabilities via Latent Activations

model-releasesarxiv-cs-ai

arXiv:2608.16970v1 Announce Type: cross Abstract: LLM-based code generation is now embedded in mission-critical pipelines, but defenses against vulnerable output remain post-hoc -- static analyzers, f

Procedural Content Metageneration via Program Search and Continual Abstraction Discovery

arXiv:2608.17947v1 Announce Type: new Abstract: Large language models can generate executable programs, which makes it possible to search directly over procedural content generators rather than indivi

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

model-releasesarxiv-cs-ai

arXiv:2608.17379v1 Announce Type: cross Abstract: We introduce PTXBench, a benchmark for evaluating and adapting large language models (LLMs) to use architecture-specific PTX for GPU kernel optimizati

Local Ai

PXDepth: Pixel-Space Modeling for Structure Preserving Monocular Depth Estimation

arXiv:2608.16984v1 Announce Type: cross Abstract: Recent monocular depth estimators achieve strong zero-shot generalization, yet often struggle to preserve fine-grained structures and object boundarie

local-aiarxiv-cs-ai

Q-Interference: Memory-Efficient Phase-Aware Quantum-Inspired Attention

model-releasesarxiv-cs-cl

arXiv:2608.17288v1 Announce Type: new Abstract: GPT attention measures token compatibility through dot-product similarity. This mechanism is simple, effective, and memory-efficient. But it does not ex