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arXiv:2511.02200v2 Announce Type: replace Abstract: The emergence of multi-agent systems powered by large language models (LLMs) has unlocked new frontiers in complex task-solving, enabling diverse ag

agentsarxiv-cs-ai

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Research

Optimal Mixture-of-Experts Model Averaging for Conditional Generative Models

DGX agent

arXiv:2607.04360v1 Announce Type: cross Abstract: Conditional generative models have emerged as powerful tools for sampling from target conditional distributions, driving substantial advances across a

researcharxiv-cs-lg

7 Jul 2026

Optimality-Informed Neural Networks for Lunar Landing Trajectory Optimization

arXiv:2607.02741v1 Announce Type: cross Abstract: This paper develops an Optimality-Informed Neural Network (OINN) approach for the energy-optimal, free-final-time powered descent of a lunar lander fr

safetyarxiv-cs-lg

Optimizing Large Language Models for Causality Assessment in Pharmacovigilance: Developing a Performance Metric as Objective for Bayesian Hyperparameter Optimization

model-releasesarxiv-cs-cl

arXiv:2607.03704v1 Announce Type: new Abstract: Background: Growing individual case safety report (ICSR) volumes have intensified demand for scalable automated causality assessment. Large Language Mod

Optimizing ML Workload Partitioning between CPUs and CIM Accelerators for Heterogeneous Computing

arXiv:2607.05240v1 Announce Type: cross Abstract: Computing-in-Memory (CIM) accelerators execute Matrix-Vector Multiplications (MVMs) in memory, making them a compelling solution for Machine Learning

Order-based Causal Discovery for Multistage Processes

arXiv:2607.03971v1 Announce Type: cross Abstract: Causality has become an increasingly important tool for gaining a deeper understanding of complex systems. Among various causal analysis methods, caus

Agents

Organizational Memory for Agentic Business Process Execution

arXiv:2607.03228v1 Announce Type: new Abstract: LLM-based agents offer new opportunities for automating business process execution beyond the limits of rule-based systems. However, general-purpose LLM

agentsarxiv-cs-ai

OrthoReg: Orthogonal Regularization for Hybrid Symbolic-Neural Dynamical Systems

arXiv:2606.19145v2 Announce Type: replace-cross Abstract: Dynamical systems are fundamental to modeling the natural world, yet modeling them involves a persistent trade-off: manually prescribed mechan

OSF: On Pre-training and Scaling of Sleep Foundation Models

arXiv:2603.00190v2 Announce Type: replace-cross Abstract: Polysomnography (PSG) provides the gold standard for sleep assessment but suffers from substantial heterogeneity across recording devices and

Ossetic-COT: Designing a morphologically annotated corpus and morphological analyzer for Ossetic

arXiv:2607.04895v1 Announce Type: new Abstract: In this work we present the first morphologically annotated corpus for Iron Ossetic that conforms to the Universal Dependencies schema. The corpus inclu

researcharxiv-cs-cl

Out-of-Distribution Detection in Molecular Complexes via Diffusion Models for Irregular Graphs

arXiv:2512.18454v3 Announce Type: replace Abstract: Predictive machine learning models generally excel on in-distribution data, but their performance degrades on out-of-distribution (OOD) inputs. Reli

Out-of-Distribution Generalization of Risk Aversion in Language Models

arXiv:2607.02755v1 Announce Type: cross Abstract: Training AIs to be risk-averse in resources could offer a failsafe in the event that AIs turn out misaligned. Misaligned but risk-averse AIs would ten

Out-of-distribution Neural Inference in Dynamical Ising Models

arXiv:2607.03039v1 Announce Type: new Abstract: Neural networks are increasingly used to infer hidden physical structure from dynamical observations, yet it remains unclear whether their out-of-distri

Overloading Large Vision-Language Models for Jailbreaking

arXiv:2607.02961v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) exhibit remarkable vision-language capabilities and are increasingly deployed in real-world applications such as pe

safetyarxiv-cs-cv

Oyster-II: Reinforcement Learning for Constructive Safety Alignment in Large Language Models

arXiv:2607.02914v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable capabilities across diverse applications, yet ensuring their simultaneous safety, helpfulness,

safetyarxiv-cs-ai

Applications

P^3: Toward Versatile Embodied Agents

arXiv:2508.07033v2 Announce Type: replace Abstract: Embodied agents have shown promising generalization capabilities across diverse physical environments, making them essential for a wide range of rea

applicationsarxiv-cs-ro

PAGE: Towards Practical Human-level Gaze Target Estimation

arXiv:2607.04860v1 Announce Type: new Abstract: Gaze target estimation, the task of predicting where a person is looking in a scene, is crucial to understanding human attention and intent. It is a cha

Paired Uterine Whole-Slide Images and Pathology Reports for Multimodal Computational Pathology

arXiv:2607.04020v1 Announce Type: new Abstract: Uterine diseases represent an important category of gynecologic pathology and require accurate histopathological assessment for diagnosis and treatment

Panorama: Fast-Track Nearest Neighbors

arXiv:2510.00566v4 Announce Type: replace-cross Abstract: Approximate Nearest-Neighbor Search (ANNS) pipelines for high-dimensional neural embeddings spend the bulk of their query time in candidate ve

Parallelized Autoregressive Decoding for Omni-Modal Dense Video Captioning

arXiv:2607.02963v1 Announce Type: cross Abstract: Dense video captioning aims to generate temporally grounded descriptions of video events, benefiting both event-level video understanding and generati

Parameter Efficient Multimodal Instruction Tuning for Romanian Vision Language Models

arXiv:2512.14926v2 Announce Type: replace-cross Abstract: Focusing on low-resource languages is an essential step toward democratizing generative AI. In this work, we contribute to reducing the multim

Tutorials

Parametric Memory Decoding for Zero-Shot Routing in LoRA-Based External Parametric Memory

arXiv:2607.04118v1 Announce Type: cross Abstract: With the rise of parametric memory, LoRA-based External Parametric Memory (EPM) has emerged as a modular solution, but existing routing methods often

tutorialsarxiv-cs-ai

ParEVO: Synthesizing Code for Irregular Data: High-Performance Parallelism through Agentic Evolution

model-releasesarxiv-cs-lg

arXiv:2603.02510v2 Announce Type: replace Abstract: The transition from sequential to parallel computing is essential for modern high-performance applications but is hindered by the steep learning cur

Parity-Aware Byte-Pair Encoding: Improving Cross-lingual Fairness in Tokenization

arXiv:2508.04796v3 Announce Type: replace-cross Abstract: Tokenization is the first -- and often least scrutinized -- step of most NLP pipelines. Standard algorithms for learning tokenizers rely on fr

safetyarxiv-cs-ai

PAST-TIDE: Prototype-Anchored Statement Tuning with Topic-Invariant Normalization for Stance Detection

arXiv:2607.04690v1 Announce Type: new Abstract: We introduce PAST-TIDE, our stance detection system addressing both subtasks of the StanceNakba Shared Task at NakbaNLP@LREC-COLING 2026. The main idea

researcharxiv-cs-cl

Pathways of Visual Information Flow in Vision-Language Models

arXiv:2607.03358v1 Announce Type: cross Abstract: We study how visual information is routed in vision-language models (VLMs). Using causal patching on controlled synthetic and natural datasets, we fin

researcharxiv-cs-cl

PCA of probability measures: Sparse and Dense sampling regimes

arXiv:2602.02190v2 Announce Type: replace-cross Abstract: A common approach to perform PCA on probability measures is to embed them into a Hilbert space where standard functional PCA techniques apply.

PDEFlow: Autonomous Agentic PDE Pipelines for Neural Operator Learning and Solver-Free Inference

arXiv:2607.05134v1 Announce Type: cross Abstract: We present PDEFlow, an autonomous agentic framework that turns user-level ODE and PDE descriptions into solver-backed neural-operator pipelines. The w

PDFBench: A Benchmark for De novo Protein Design from Function

arXiv:2505.20346v3 Announce Type: replace-cross Abstract: Function-guided protein design is a crucial task with significant applications in drug discovery and enzyme engineering. However, the field la

Applications

PedestrianDiffusion: Multimodal Generative Denoising and Dense State Estimation for Inertial Navigation

arXiv:2607.03349v1 Announce Type: cross Abstract: The accuracy of consumer-grade inertial navigation is bottlenecked by the stochastic noise of Micro-Electro-Mechanical Systems (MEMS). Traditional det

applicationsarxiv-cs-ai

Hardware

PEEK: Predictive Queue-Informed KV Cache Management for LLM Serving

arXiv:2607.02525v1 Announce Type: cross Abstract: We present PEEK, a lightweight scheduling and eviction framework for both online (streaming) and offline (batch) LLM serving; this paper focuses on th

hardwarearxiv-cs-ai

Perceiving Better Moments: Cover Frame Reselection and Enhancement for Live Photos with the Live2K Dataset

model-releasesarxiv-cs-cv

arXiv:2607.04151v1 Announce Type: new Abstract: Modern smartphones capture Live Photos, short video bursts surrounding a still image, offering a dynamic and engaging photographic experience. However,

Perceptual Flow Matching for Few-Step Generative Modeling

arXiv:2607.03524v1 Announce Type: new Abstract: We propose Perceptual Flow Matching (PFM), a simple yet effective framework for few-step generation in flow-matching models. Rather than performing velo

Personalized Causal Recourse: A Human-In-The-Loop Approach

arXiv:2607.03425v1 Announce Type: new Abstract: Algorithmic recourse addresses the challenge of providing tailored recommendations to users affected by unfavorable machine learning decisions, in poten

pFedNavi: Structure-Aware Personalized Federated Vision-Language Navigation for Embodied AI

arXiv:2602.14401v2 Announce Type: replace-cross Abstract: Vision-Language Navigation VLN requires large-scale trajectory instruction data from private indoor environments, raising significant privacy

Local Ai

Phase-Preserving Trimodal Transformer for Tropical Forest Biomass Estimation Using Optical and PolInSAR Data

arXiv:2607.03663v1 Announce Type: cross Abstract: The accurate estimation of Above-Ground Biomass (AGB) in mature tropical forests remains a critical challenge in remote sensing, primarily due to the

local-aiarxiv-cs-ai

PhenoNEST: A Neuro-Symbolic Framework for Ontology-Aware Multimodal Plant Phenotyping and Trait Discovery

arXiv:2607.03245v1 Announce Type: new Abstract: High-throughput plant phenotyping generates valuable data that often remains trapped in unstructured text and isolated RGB images. To bridge this semant

Phi-SegNet: Phase-Integrated Supervision for Medical Image Segmentation

model-releasesarxiv-cs-cv

arXiv:2601.16064v2 Announce Type: replace-cross Abstract: Deep learning has substantially advanced medical image segmentation, yet achieving robust generalization across diverse imaging modalities and

Tutorials

Physically-Relevant Information Learning in High-Dimensional Time-Derivatives Spaces

arXiv:2607.05127v1 Announce Type: cross Abstract: Understanding the physics of many-body complex dynamical systems is typically non-trivial. High-dimensional analysis approaches are often deemed neces

tutorialsarxiv-cs-lg

Local Ai

Physics-Informed Domain-Invariant Feature Learning with Autoencoder-Driven Gaussian Clustering for Robust Non-line-of-Sight Scenarios

arXiv:2607.02537v1 Announce Type: cross Abstract: Jamming and spoofing pose significant threats to wireless and satellite navigation by disrupting radio-frequency (RF) signals and compromising availab

local-aiarxiv-cs-lg

Physics-Informed Graph Learning with Uncertainty Awareness for Open-Set Domain Generalization in Fault Diagnosis

arXiv:2607.04188v1 Announce Type: new Abstract: Intelligent industrial maintenance critically relies on reliable fault diagnosis of rotating machinery. However, it faces formidable challenges from unk

Physiological Noise Augmentation Improves Non-Invasive Brain-to-Speech

arXiv:2607.05165v1 Announce Type: new Abstract: Non-invasive brain-to-speech decoding aims to restore communication to patients suffering from neurodegenerative disease, without the risks of neurosurg

PhysMirror: Physics-Aware Mirror Object Generation

model-releasesarxiv-cs-cv

arXiv:2607.03470v1 Announce Type: new Abstract: Synthesizing physically accurate mirror reflections remains a fundamental challenge for modern text-to-image diffusion models, which are increasingly cr

Piecewise Dynamic Diffusion Regularization for Reconstruction of Cardiac Cine MRI

arXiv:2607.03299v1 Announce Type: cross Abstract: Real-time cardiac cine MRI enables visualization of the beating heart during free breathing, but severe undersampling and motion make reconstruction h

PIEFS: Physics-Informed Eigenfunction Features with Learnable Scaling

arXiv:2607.03692v1 Announce Type: new Abstract: Spectral methods are widely used to construct representations from the geometry of data, but they often rely on a fixed kernel, graph Laplacian, or manu

safetyarxiv-cs-lg

Piercing Gilbreath's Conjecture: From Deep Number Theory Insights to Fintech and Cybersecurity

arXiv:2607.04166v1 Announce Type: cross Abstract: I propose a new methodology to attack the fascinating Gilbreath's conjecture about prime numbers, first posted in 1878 and unsolved to this day. The p

PixCon: Clean-Positive Contrastive Learning for Foundation-Model Semi-Supervised Segmentation

arXiv:2607.03068v1 Announce Type: cross Abstract: Semi-supervised semantic segmentation (SSSS) has long turned on one question, which pseudo-labels to trust, and answered it with ever more careful con

PixelPilot: Scalable Vision-Language-Action Models for End-to-End Autonomous Driving

arXiv:2607.04637v1 Announce Type: new Abstract: Vision-Language-Action Models (VLAs), which leverage the advanced reasoning capabilities of Vision-Language Models (VLMs), show promising generalization

safetyarxiv-cs-cv