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PerturbPFN: Probing the Limits of Synthetic Priors in Drug Perturbation Modelling

arXiv:2607.23447v1 Announce Type: new Abstract: Predicting cellular responses to unseen chemical perturbations is challenging due to unknown targets and mechanisms, high-dimensional expression respons

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Photonic reservoir computing with complex networks

DGX agent

arXiv:2607.23285v1 Announce Type: cross Abstract: Photonic reservoir computing has attracted increasing attention as a fast and low-cost approach for time-series prediction. Photonic reservoir computi

researcharxiv-cs-lg

28 Jul 2026

Physics-Guided Generative AI for Property-Targeted 3D Porous Media Design

arXiv:2607.24274v1 Announce Type: cross Abstract: Inverse design of three-dimensional porous media is central to applications in filtration, catalysis, energy storage, fuel cells, thermal management,

Physics-Informed Neural Networks for Predicting Nitrous Oxide Flux

arXiv:2607.23880v1 Announce Type: cross Abstract: Nitrous oxide (N_2O) is the dominant ozone-depleting substance emitted in the 21st century, and the third largest contributor to anthropogenic greenho

Physics Transformer: Tailoring Transformer for General PDE Prediction

arXiv:2607.24513v1 Announce Type: new Abstract: Transformer architectures have attracted increasing attention for solving partial differential equations (PDEs), owing to their flexibility in handling

PointCHR: Point Cloud Analysis via Curvature-Aware Hyperbolic Rectification

arXiv:2607.24052v1 Announce Type: new Abstract: High-curvature regions in 3D point clouds encapsulate critical fine-grained geometric semantics yet exhibit a distinct long-tail sparsity in their spati

Pose-Aware Modeling to Mitigate Pose-Related Artifacts in Tactile Gloves

arXiv:2607.22964v1 Announce Type: new Abstract: Tactile gloves digitize contact and force during hand-object interactions, enabling robotics applications in dexterous manipulation, teleoperation, and

researcharxiv-cs-ro

Post-Operative Glioma Segmentation via Loss Stabilization, Normalization and Subspace Attention

arXiv:2607.22749v1 Announce Type: cross Abstract: Tracking residual tumor after surgery is essential for catching recurrence early, but automating post-operative glioma segmentation remains a difficul

PRESTO: Prefix-Aligned Tree Drafting for Diffusion Speculative Decoding

arXiv:2607.22634v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to autoregressive (AR) LLMs, generating tokens in parallel. This makes t

Procedural Content Generation via Generative Artificial Intelligence

arXiv:2407.09013v2 Announce Type: replace Abstract: The attempt to utilize machine learning in PCG has been made in the past. In this survey paper, we investigate how generative artificial intelligenc

PTStore (Prefix Tensor Store): Distributed Prefix Caching and Replication for High Throughput Inference Serving

arXiv:2607.22648v1 Announce Type: new Abstract: Inspired by the design of client caching in Content Delivery Networks (CDNs), PTStore distributes and replicates popular tensors that form reusable KV c

pyALDIC: A Python Implementation of Augmented Lagrangian Digital Image Correlation with a GUI, Adaptive Meshing, and Mask-Aware Subset Splitting

arXiv:2607.22755v1 Announce Type: cross Abstract: pyALDIC is an open-source Python implementation of augmented Lagrangian digital image correlation (AL-DIC) for full-field displacement and strain meas

PYPM-GGD: Pitman-Yor Process Mixture with Generalized Gaussian Density using ADAM

arXiv:2607.24583v1 Announce Type: new Abstract: Large scale Bayesian nonparametrics (BNP) learner such as Stochastic Variational Inference (SVI) can handle datasets with large class number and large t

Quality-Adaptive Multi-UAV 3D Reconstruction with Sparse Workload Redistribution

arXiv:2607.24233v1 Announce Type: new Abstract: 3D reconstruction of unknown environments is a key application in robotics but is severely limited by the computational and energy capabilities of curre

researcharxiv-cs-ro

Quantum-Inspired Evolutionary Neighborhood Search for Arrival-Departure Track Utilization Adjustment under Short-Term Disturbances

arXiv:2607.24049v1 Announce Type: new Abstract: Short-term disturbances at major passenger railway stations alter train arrival and departure times as well as the release sequence of station resources

Queryable Self-Organizing Maps: A Database Abstraction for Topology-Driven Data Exploration

arXiv:2607.22843v1 Announce Type: cross Abstract: Self-Organizing Maps (SOMs) have long been used as exploratory tools for high-dimensional data: they organize objects into a two-dimensional topology

Quotient Tree Arithmetic: Deferred-Division Computation with Bounded Symbolic Depth and Cross-Subtree Cancellation

arXiv:2607.22612v1 Announce Type: cross Abstract: We introduce Quotient Tree Arithmetic (QTA), a computational substrate in which values are represented as deferred quotient pairs (N, D) whose ratio i

Reading Between the Signs: Predicting Future Suicidal Ideation from Adolescent Social Media Texts

arXiv:2509.03530v2 Announce Type: replace Abstract: Suicide is a leading cause of death, yet predicting it remains a significant challenge. Risk factors such as depression or substance use are commonl

Realizing Scaling Laws in Recommender Systems: A Foundation-Expert Paradigm for Hyperscale Model Deployment

arXiv:2508.02929v3 Announce Type: replace-cross Abstract: Scaling laws have been established for recommender systems, yet efficiently deploying foundation model (FM) across multiple recommendation sur

Reason-Mediated Behavioral Models for Auditing LLM Social Simulators

arXiv:2607.24649v1 Announce Type: new Abstract: Large language models are increasingly used as social simulators, including as synthetic survey respondents. Most evaluations ask whether simulated outc

Recycling computational processes of dynamic programming for combinatorial optimization problems: a reservoir computing approach

arXiv:2607.23009v1 Announce Type: new Abstract: Reusing previously computed results is a long-standing principle for reducing computational cost, but such reuse has largely been confined to a single p

Restoration Flow Matching-Based Channel Refinement and Equalization Correction for MIMO Semantic Communications

arXiv:2607.23615v1 Announce Type: new Abstract: In multiple-input multiple-output (MIMO) semantic communication, imperfect channel state information (CSI) and equalization mismatch can seriously degra

Rethinking the Generation Order of Block Diffusion Language Models

arXiv:2607.24306v1 Announce Type: new Abstract: Diffusion language models enable flexible arbitrary-order generation, but existing sampling methods are mostly designed for early masked diffusion model

Retrieval-Augmented Generation of Ontologies from Relational Databases

arXiv:2506.01232v2 Announce Type: replace-cross Abstract: Deriving OWL ontologies from relational database schemas supports semantic interoperability and downstream tasks such as knowledge graph popul

Reverso: Efficient Time Series Foundation Models for Zero-shot Forecasting

arXiv:2602.17634v2 Announce Type: replace-cross Abstract: Learning time series foundation models has been shown to be a promising approach for zero-shot time series forecasting across diverse time ser

Revitalizing Public Urban Places through Cultural and Political Memory: A Technological Approach with LLMs and Augmented Reality

arXiv:2607.22613v1 Announce Type: cross Abstract: This paper explores the intersection of memory, place, and identity, examining how new technologies, particularly Apple Vision Pro, can illuminate thi

RODR: Riemannian Orthogonally Decoupled Regularization for Disentangled Manifold Representation

arXiv:2607.23958v1 Announce Type: new Abstract: Point cloud denoising is essentially a geometric recovery task that aims to reconstruct the intrinsic structure of a smooth 2D Riemannian manifold embed

RoleMix: Unifying Sequential and Non-Sequential Features via Semantic Tokenization for Post-Click Conversion Rate Prediction

arXiv:2607.22700v1 Announce Type: new Abstract: Post-click conversion rate (PCVR) prediction is central to industrial recommendation, but remains challenged by the structural mismatch between sparse,

SADe: Sparse-Atom Support Decontamination for Few-Shot Segmentation with Weak Support Annotations

arXiv:2607.24706v1 Announce Type: new Abstract: Few-shot segmentation (FSS) commonly assumes clean pixel-level support masks, yet practical support supervision often uses boxes, scribbles, coarse mask

Same Predictions, Different Reasons: The Effect of Quantization on Model Explanations

arXiv:2607.22872v1 Announce Type: cross Abstract: Post-training quantization (PTQ) has become a practical solution for deploying deep learning models on resource-constrained edge devices by compressin

Same Question, Different Answers: Evaluating LLM Reliability Beyond Accuracy

arXiv:2607.22554v1 Announce Type: new Abstract: Large language models (LLMs) often achieve strong accuracy on benchmarks, yet it remains unclear how reliably they apply this knowledge when the same qu

SARATR-X-v2: Scale-Aware Structural Pre-Training for SAR Foundation Models

arXiv:2607.23238v1 Announce Type: new Abstract: Masked image modeling has become a dominant paradigm for SAR pre-training, yet the design of the reconstruction target remains fundamentally unsettled.

Segmentation Robustness and Predictive Utility in Glioblastoma Radiomics: Evidence for a Trade-off in Survival Modelling

arXiv:2607.23626v1 Announce Type: cross Abstract: Radiomic biomarkers derived from magnetic resonance imaging (MRI) have been widely investigated as non-invasive tools for tumor characterization and p

Self-Attention Dynamics with Rotary Position Embeddings: Twisted States and Explicit Consensus Rates on the Sphere

arXiv:2607.24502v1 Announce Type: cross Abstract: Rotary position embeddings (RoPE) modify attention scores through position-dependent rotations, but their effect on normalized token dynamics is not c

Self-Distillation of Hidden Layers for Self-Supervised Representation Learning

arXiv:2603.15553v2 Announce Type: replace Abstract: The landscape of self-supervised learning (SSL) is currently dominated by generative approaches (e.g. MAE) that reconstruct raw low-level data, and

SHReg: Strictly Rotation-Equivariant Point Cloud Registration via Spherical Harmonics

arXiv:2607.23096v1 Announce Type: new Abstract: Point cloud registration critically depends on local features that are both distinctive and robust to arbitrary 3D rotations. Existing learning-based me

Similarity Is Not Logic: Factored Inference for Dual-Encoder Vision-Language Models

arXiv:2607.23052v1 Announce Type: cross Abstract: Dual-encoder vision-language models (VLMs) expose a similarity interface that enables zero-shot retrieval but fails compositional constraints: queries

Simple Language Normalization Wins: Cross-Lingual Speaker Verification for the TidyVoice 2026 Challenge

arXiv:2607.22923v1 Announce Type: new Abstract: Cross-lingual mismatch remains a key source of overall degradation in modern speaker verification. The TidyVoice2026 Challenge targets this setting with

SLAM-Former: Putting SLAM into One Transformer

arXiv:2509.16909v2 Announce Type: replace Abstract: We present SLAM-Former, a neural approach that integrates full SLAM capabilities into a single transformer. Similar to traditional SLAM systems, SLA

SMART: LLM-Augmented Hybrid Retrieval for Dynamic Product Ads

arXiv:2607.23121v1 Announce Type: cross Abstract: Dynamic Product Ads (DPA) require retrieving relevant items from multi-million product catalogs, balancing two competing objectives: retargeting (re-s

Soft-Constrained Optimization of Latent Space in Variational Autoencoders

arXiv:2607.23751v1 Announce Type: new Abstract: The usefulness of a variational autoencoder (VAE) depends on two properties of its latent space that are hard to obtain together: high encoding capacity

Sol-Attn: Accelerating Video Generation Inference via On-the-Fly Attention Sparsification

arXiv:2607.24027v1 Announce Type: new Abstract: Diffusion transformers are essential for high-fidelity video generation, but long token sequences make attention a dominant inference bottleneck. Traini

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects

arXiv:2607.24645v1 Announce Type: cross Abstract: The wide-scale use of sparse autoencoders (SAEs) as interpretability tools is limited by inconsistent links between SAE features and model behavior. F

Spatially-Aware Class-Agnostic Object Counting

arXiv:2607.16826v2 Announce Type: replace Abstract: Generalised object counting aims to estimate the number of instances of an arbitrary object category from a single image, but many recent methods ca

Spectral-Aware Analytic Class-Incremental Learning for Long-Tailed Distributions

arXiv:2607.22931v1 Announce Type: cross Abstract: Analytic Continual Learning (ACL) offers a computationally efficient alternative to gradient-based approaches. Recent ACL methods are based on Recursi

Speech Signals Complement LLMs for Predicting Interpersonal Attraction in Speed Dating

arXiv:2607.23037v1 Announce Type: new Abstract: Large language models (LLMs) can predict interpersonal attraction from conversation transcripts, but it remains unclear what a speech predictor can add

Stabilizing Deep Reconstruction Operators with Contractive Anchoring

arXiv:2607.23341v1 Announce Type: cross Abstract: Pretrained deep denoisers can be used to solve a wide range of model-based image reconstruction tasks via Plug-and-Play (PnP) and Regularization-by-De

Stacking the Deck: Tunable Trainability in Stacked LCUs

arXiv:2607.24686v1 Announce Type: cross Abstract: Variational quantum circuits have been central to many proposed near-term applications of quantum computing, but a growing body of evidence suggests t