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Neuro-Causal Factor Analysis

arXiv:2305.19802v2 Announce Type: replace-cross Abstract: Factor analysis (FA) is a statistical method for explaining how mutually dependent observed variables can be represented in terms of mutually

NoTB: Oracle-Free Triage of LLM-Generated RTL via Cross-Model Formal Consensus

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arXiv:2608.21962v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate register-transfer-level (RTL) designs from natural-language specifications. However, as

researcharxiv-cs-ai

25 Aug 2026

OmicSync: Reliability-Aware Spatial Multi-Omics Clustering with Evidence-Constrained LLM Reasoning

arXiv:2608.22785v1 Announce Type: new Abstract: Spatial multi-omics technologies jointly profile gene expression, surface proteins, and histology at each tissue spot, yet most spatial domain discovery

On Tensor-Based PDEs and their Corresponding Variational Formulations with Application to Color Image Denoising

arXiv:2608.22302v1 Announce Type: new Abstract: The case when a partial differential equation (PDE) can be considered as an Euler-Lagrange (E-L) equation of an energy functional, consisting of a data

On the Convergence of Single-Loop Stochastic Bilevel Optimization with Approximate Implicit Differentiation

arXiv:2602.23633v2 Announce Type: replace Abstract: Stochastic Bilevel Optimization has emerged as a fundamental framework for meta-learning and hyperparameter optimization. Despite the practical prev

On the Role of Citations in Preference Data

arXiv:2608.21376v1 Announce Type: cross Abstract: Many NLP tasks require systems to provide attribution in their outputs--i.e. citations to grounding sources. Attribution serves as a bulwark against m

On the Threat Model of Weird Generalization and Emergent Misalignment

arXiv:2608.23476v1 Announce Type: new Abstract: Narrow fine-tuning on small, domain-specific datasets can produce broad and surprising changes in model behavior-a phenomenon called weird generalizatio

researcharxiv-cs-cl

Opportunities and Challenges of Natural Language Processing for Low-Resource Senegalese Languages in Social Science Research

arXiv:2601.09716v2 Announce Type: replace Abstract: Natural Language Processing (NLP) is rapidly transforming research methodologies across disciplines, yet African languages remain largely underrepre

researcharxiv-cs-cl

Optimize Surgical Triplet Recognition: A Knowledge-Driven Mixture-of-Experts Solution

arXiv:2608.22972v1 Announce Type: new Abstract: Surgical action triplet recognition constitutes a critical task in context-aware robot-assisted surgery, facilitating automatic surgical action percepti

Optimizer choice matters for the emergence of Neural Collapse

arXiv:2602.16642v4 Announce Type: replace Abstract: Neural Collapse (NC) refers to the emergence of highly symmetric geometric structures in the representations of deep neural networks during the term

Ordinal Diffusion Models for Color Fundus Images

arXiv:2602.24013v2 Announce Type: replace Abstract: Generative image models such as diffusion models can improve performance on clinically relevant tasks by offering deep learning models supplementary

PatchGate: Narrowing the Verbalization Gap with Intrinsic Object Inventories in Frozen Vision-Language Models

arXiv:2608.21819v1 Announce Type: cross Abstract: Reliable image captioning in Vision-Language Models (VLMs) requires captions to be both precise and complete, avoiding unsupported object mentions whi

Photorealistic Novel View Synthesis of Human Faces using Next-Scale Transformers

arXiv:2608.23410v1 Announce Type: new Abstract: Photorealistic novel view synthesis of people remains challenging at high spatial resolutions and across multiple target cameras, where preserving ident

PhysECD: A Physics-Constrained E(3)-Equivariant Framework for Electronic Circular Dichroism Spectrum Prediction

arXiv:2608.21892v1 Announce Type: cross Abstract: The electronic circular dichroism (ECD) spectrum is a primary experimental probe for assigning the absolute configuration of chiral molecules, yet int

Physics-Constrained Deep Learning Model for Contactless Blood Pressure Monitoring from Triaxial Bodyseismography

arXiv:2608.23562v1 Announce Type: cross Abstract: Ballistocardiography (BCG) is promising for unobtrusive long-term blood pressure (BP) monitoring in laboratory settings, but traditional BCG signals a

Physics-Knowledge-Guided Hybrid Neural Learning for Arctic Sea Ice Concentration Evolution and Short-Range Prediction

arXiv:2608.21767v1 Announce Type: new Abstract: Accurate modeling of sea ice concentration (SIC) evolution is essential for polar climate assessment and short?range sea ice prediction. Numerical and d

Piecewise Linear Equivariant Maps for Compact Groups

arXiv:2608.21645v1 Announce Type: cross Abstract: Motivated by equivariant neural networks, we study piecewise linear equivariant maps between finite-dimensional real representations of compact groups

Pixel-Space Diffusion via Observation Operators

arXiv:2608.21885v1 Announce Type: new Abstract: Pixel-space diffusion models directly model image distributions but remain difficult to optimize. Recent methods alleviate this challenge through target

Poisson Subspace Clustering: Focusing on the Essentials in Count Data

arXiv:2608.23287v1 Announce Type: new Abstract: Count data represented as a matrix of non-negative integer values, such as contingency tables, are prevalent across diverse domains. When clustering suc

PolyChirp: Multi-Species Birdsong Classification Using TinyML on Low-Power Acoustic Sensors

arXiv:2608.23101v1 Announce Type: cross Abstract: Recent progress in the field of TinyML has demonstrated that low-power hardware based on microcontrollers can achieve bird species monitoring in real

Polynomial-Time Mistake-Bounded Language Generation

arXiv:2606.16077v2 Announce Type: replace-cross Abstract: In this paper, we introduce a polynomial-time version of the mistake-bounded language generation (MBLG) framework due to Kleinberg, Peale, and

POOL: Propagated Uncertainty Over Lookalikes

arXiv:2608.23086v1 Announce Type: new Abstract: Black-box large language models need confidence scores that can separate likely-correct from likely-incorrect outputs, enabling systems to prioritize hu

Position: Robot Privacy as Embodied Boundary Work. Connecting Capabilities, Contexts, and Design Responses in Everyday Robotics

arXiv:2608.21410v1 Announce Type: new Abstract: Robots are increasingly entering everyday environments where privacy is shaped not only by data practices, but also by spatial, bodily, social, and rela

researcharxiv-cs-ro

Power-Performance Characterization of TinyML Systems

arXiv:2608.21646v1 Announce Type: cross Abstract: TinyML systems are enabling machine learning (ML) inference at the edge. However, there is little quantitative analysis of such systems. This paper pr

Precision-Aware Variable Bit Processing Elements for Hardware-Efficient Systolic Array Designs

arXiv:2608.22378v1 Announce Type: cross Abstract: Systolic arrays (SAs) have emerged as prominent hardware accelerators for matrix operations in deep learning, while floating point number formats enab

Predicting Early Functional Decline from Longitudinal Laboratory and Vital Sign Trajectories: A Large-Scale Study Using the All of Us Research Program

arXiv:2608.21589v1 Announce Type: new Abstract: Functional decline in older adults is typically recognized only after falls or observable gait impairment, closing the window for prevention. We investi

Predicting Multiple Clinical Outcomes Related to Functional Recovery and Social Isolation Among Older Adults After Lower-Limb Fracture or Hip Replacement

arXiv:2608.23531v1 Announce Type: new Abstract: Older adults recovering after lower-limb fracture or hip replacement may experience complex recovery trajectories. Most of the time, these clinical aspe

presto: Efficient, Training-free, and Open-world Object Placement via Imaginary Search

arXiv:2608.21543v1 Announce Type: cross Abstract: Object placement is critical in image composition, requiring spatially and semantically coherent positioning of objects within diverse scenes. Existin

Pretreatment DCE-MRI Resolves Response Quality Within Pathologic Endpoints in Neoadjuvant Breast Cancer

arXiv:2608.22097v1 Announce Type: cross Abstract: Pathologic complete response (pCR) is a strong neoadjuvant endpoint, yet 5-15% of complete responders recur and clinical/genomic variables do not reli

Primal--Dual Alternating Neural Learning for Timely Classification with Performance Guarantees

arXiv:2608.23480v1 Announce Type: cross Abstract: Timely risk classification is essential in many clinical monitoring settings, where decisions must balance the benefit of classifying patients early f

ProBel: Propaganda Detection with Techniques, Spans, and Explanations

arXiv:2608.22388v1 Announce Type: cross Abstract: Propaganda detection includes several related prediction levels, ranging from sentence-level decisions to technique classification and span identifica

Procedural Knowledge Extraction from Industrial Troubleshooting Guides Using Vision Language Models

arXiv:2601.22754v2 Announce Type: replace-cross Abstract: Industrial troubleshooting guides encode diagnostic procedures in flowchart-like diagrams where spatial layout and technical language jointly

Provably adaptive sampling with uniform and remasking discrete diffusion models

arXiv:2608.23554v1 Announce Type: new Abstract: Discrete diffusion models offer a promising alternative to autoregressive generation by enabling parallel updates, but their sampling efficiency can dep

Proxy reliance in large language model decisions is uncalibrated to predictive evidence

arXiv:2608.22887v1 Announce Type: new Abstract: Large language models (LLMs) are entering decisions in triage and lending, where task-relevant inference must be distinguished from impermissible proxy

Pruned Traffic Trees: Native Semantic Compression with a Protocol-Structured Model Family for Encrypted Traffic Classification

arXiv:2608.21874v1 Announce Type: cross Abstract: Deep learning has achieved strong performance in encrypted traffic classification (ETC), yet its computational cost limits deployment on resource-cons

Quantum-Inspired Hybrid Neural Networks for Neural Decoding: A Controlled Ablation Study of Learnable Quantum Sidecar Integration

arXiv:2608.22475v1 Announce Type: new Abstract: We study parameterized quantum circuits (PQCs) integrated as residual sidecar modules within a ResNet-50 backbone for 31-class neural population decodin

Random Hazard Forests

arXiv:2608.21597v1 Announce Type: cross Abstract: Clinical data sources such as electronic health records and wearable sensors record patient status repeatedly over follow-up, often at irregular times

Reaching the Tail: Calibration Diversity Drives Conformal Coverage under Data Scarcity

arXiv:2608.21591v1 Announce Type: new Abstract: Multi-horizon rare-event forecasting is hard under long macroeconomic series' data constraints: labeled events are scarce, and standard uncertainty quan

Reading the Room: Implicit Confusion Encoding in Recurrent World Model States

arXiv:2608.21582v1 Announce Type: new Abstract: World models built on the RSSM architecture, such as DreamerV3, keep a recurrent hidden state h_t trained only to reduce prediction error. We show this

Real-TurnTurk: A Multimodal Turkish Corpus for Turn-Taking Prediction

arXiv:2608.22071v1 Announce Type: cross Abstract: Turn-taking is a basic organizational feature of human conversation and remains difficult to model in natural, synchronous dialog systems. While exist

ReCoG: Reciprocal Co-Evolution for Multimodal Graph Learning

arXiv:2608.22786v1 Announce Type: new Abstract: Multimodal graph learning requires jointly training over graph structure and heterogeneous node attributes, yet existing methods largely decouple these

Region-Weighted Losses and Model Fusion for Cross-Modal PET Attenuation Correction

arXiv:2608.21881v1 Announce Type: new Abstract: We describe our approach to the Big Cross-Modal Attenuation Correction (BIC-MAC) challenge, which asks for a pseudo-CT in Hounsfield Units to be synthes

Relational Structural Causal Models

arXiv:2606.14892v2 Announce Type: replace Abstract: An artificial intelligence must have a model of its environment that is causal, supporting reasoning about interventions and counterfactuals, and al

Reliability- and Anatomy-Consistency-Aware Multimodal Learning for Robust Fracture Classification from Bangladeshi Radiographs

arXiv:2608.21482v1 Announce Type: cross Abstract: Background: Multimodal fracture classifiers may benefit from patient and anatomical metadata, but they can also become brittle when contextual informa

Results of the 1st Asynchronous CASTLE Challenge at the Joint Egocentric Vision Workshop in Conjunction with CVPR 2026

arXiv:2608.22914v1 Announce Type: new Abstract: This report summarizes the contributions and results of the 1st Asynchronous CASTLE Challenge at the Joint Egocentric Vision Workshop in conjunction wit

Rethinking Communication Metrics: How Should We Measure Meaning?

arXiv:2608.21626v1 Announce Type: new Abstract: Semantic communication shifts the objective of communication systems from accurate symbol reconstruction toward meaning preservation, task accomplishmen

Retrieval-Augmented Classification of Environmental Mitigations in Hydropower Licensing Documents

arXiv:2608.23241v1 Announce Type: cross Abstract: Identifying and classifying environmental mitigation obligations in Federal Energy Regulatory Commission hydropower licensing documents is a labor-int

Reviewing Model Collapse and Countermeasures

arXiv:2608.21366v1 Announce Type: new Abstract: Driven by massive amounts of web-scale data, generative AI (GenAI) has achieved remarkable progress, enabling various applications in diverse sectors. T