Search: “research”

Personalized Scorer Modeling: A Learning-Based Framework for Deriving Robust Sleep Stage Labels from Multiple Experts

arXiv:2608.12446v1 Announce Type: cross Abstract: Sleep stage classification is important for the diagnosis and management of sleep disorders, yet most automatic staging studies evaluate models agains

Research

Perturbation-based Regional Interpretability through Subtraction Mapping (PRISM): naming-error dissociations in language models and post-stroke aphasia

DGX agent

arXiv:2608.12717v1 Announce Type: cross Abstract: Mechanistic interpretability of large language models lacks spatially resolved, falsifiable tools for testing whether internal components are speciali

researcharxiv-cs-cl

14 Aug 2026

Physics-informed distribution of relaxation times estimation and latent-space condition monitoring of solid oxide fuel and electrolysis cells from electrochemical impedance spectroscopy

arXiv:2608.13305v1 Announce Type: cross Abstract: Estimating the distribution of relaxation times (DRT) fromelectrochemical impedance spectroscopy (EIS) is an ill-posed inverse problem that is highly

Physics-Informed Laplace Neural Operator for Solving Partial Differential Equations

arXiv:2602.12706v2 Announce Type: replace Abstract: Neural operators have emerged as fast surrogate solvers for parametric partial differential equations (PDEs). However, purely data-driven models oft

PixSDS: Why Latent SDS Makes Noisy Pixels

arXiv:2608.12997v1 Announce Type: new Abstract: Score Distillation Sampling (SDS) enables text-to-3D generation by optimizing rendered images with a pretrained diffusion prior, but latent SDS often pr

Prof-K: Probabilistic One-Pass Filtering for Efficient Top-k Selection

arXiv:2608.12573v1 Announce Type: new Abstract: Top-k selection is a fundamental computational primitive with applications spanning databases, information retrieval, signal processing, and modern mach

Prompts in the Wild: A Large Analyzed Collection of Transactional Prompts in Code

arXiv:2608.12905v1 Announce Type: new Abstract: The behavior of contemporary generative Large Language Models (LLMs) is directly shaped by prompts, unstructured texts that describe the desired output

PROVE-RT: Generating Mechanized Theorem Prover Scripts for Real-Time Systems using LLMs

arXiv:2608.12762v1 Announce Type: new Abstract: Schedulability analysis is essential for certifying real-time systems, but existing tests are often developed through pen-and-paper proofs that are diff

Query Timing Produces Opposite Positional Biases Between LLMs and Humans

arXiv:2608.12387v1 Announce Type: cross Abstract: Positional biases such as recency and primacy effects have been documented in large language models (LLMs), yet the underlying mechanism by which thes

QuISE: Defense against Typographic Attacks on VLMs via Query-Irrelevant Semantic Editing

arXiv:2608.13119v1 Announce Type: new Abstract: Typographic attacks pose a critical threat to vision-language models (VLMs) by injecting misleading text into images and causing models to rely on adver

RAGSieve: Self-Referenced Local Contrast for Knowledge-Poison Detection in Retrieval-Augmented Generation

arXiv:2608.13010v1 Announce Type: new Abstract: Retrieval-augmented generation treats an external corpus as inference evidence, allowing injected documents to promote attacker-chosen claims. Existing

ReconSpan: Reconstruction-Guided Adaptive Latent Tokenization

arXiv:2608.12756v1 Announce Type: new Abstract: Adaptive latent tokenization maps a fine-grained input to a shorter sequence of continuous representations associated with input-dependent spans. We int

Reconstructing Historical Manuscripts through MSI: The Potential of Contrast in Assessing Image Quality and Legibility

arXiv:2608.13381v1 Announce Type: new Abstract: Digital restoration of historical manuscript images aims to improve readability while preserving the authenticity of cultural heritage documents. Howeve

Reliability analysis for BraTS-GoAT segmentation: a controlled robustness study of deep-ensemble uncertainty

arXiv:2608.13223v1 Announce Type: new Abstract: Deep networks segment brain tumours accurately in-distribution, but can fail silently when the input differs from their training data. That risk is cent

Represent, Then Generate: Multimodal-Conditioned Time-Series Generation under Irregular Missingness

arXiv:2608.12592v1 Announce Type: new Abstract: Continuous physiological time series underpin modern clinical monitoring, yet many of the most informative signals are invasive, expensive, or simply un

Rethinking Normalization Placement for LLMs: Post-Norm under Curriculum Depth Growing

arXiv:2608.13156v1 Announce Type: new Abstract: Pre-norm is the standard normalization placement in modern Transformers because it facilitates joint optimization of full-depth models. We ask whether t

RoutePack: Expert Placement and Attention-Aware Data Packing for MoE Reinforcement Learning

arXiv:2608.12146v1 Announce Type: cross Abstract: Training Mixture-of-Experts (MoE) models for reinforcement learning (RL) couples two load-balancing problems: sequence composition determines dense at

S2-HWM: Sparse Event-Structured Hierarchical World Model for Long-Horizon Surgical Robot Manipulation

arXiv:2608.13103v1 Announce Type: new Abstract: Long-horizon surgical robot manipulation is challenging because task rewards are sparse, while meaningful interaction changes occur at irregular interva

researcharxiv-cs-ro

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization

arXiv:2608.13538v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are proposed to extract numerous features from large language model (LLM) representations, yet explaining these features stil

SchemaLink: An Intelligent Web Editor for LinkML Schema Curation

arXiv:2608.12529v1 Announce Type: cross Abstract: Motivation: LinkML is a suitable language for the representation of the structural and content constraints of different kinds of biomedical data. Even

SCOPE: Subspace Clustering with Online Per-Head Top-K Estimation for Sparse Video Attention

arXiv:2608.12780v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) incur quadratic self-attention cost over spatiotemporal tokens. Existing training-free sparse attention methods often cons

Spa3R: Predictive Spatial Field Modeling for 3D Visual Reasoning

arXiv:2602.21186v2 Announce Type: replace Abstract: Vision-language models excel at 2D visual understanding but remain limited in 3D spatial reasoning. Existing approaches either depend on explicit 3D

SPARED: Reasoning-Based AI-Generated Image Detection via Adversarially Edited Data

arXiv:2608.12876v1 Announce Type: cross Abstract: Detecting AI-generated images is only half the task: a deployed detector must also justify its verdict, yet existing detectors inherit three failure m

Spatially-Grounded Text-to-Video Generation via Inference-Time Gradient-Free Optimization

arXiv:2608.13037v1 Announce Type: new Abstract: Diffusion Transformer Text-to-Video models have achieved remarkable synthesis quality, yet fine-grained spatial controllability remains a significant ch

Statistical Properties of Robust Learning under Distributional Shifts

arXiv:2608.13133v1 Announce Type: cross Abstract: Distributional shifts arise when the target deployment environment differs from the source environment that generated the training data. Robust learni

Stochastic Neural Networks for Quantum Devices

arXiv:2602.22241v2 Announce Type: replace-cross Abstract: This work presents a formulation to express and optimize stochastic neural networks as quantum circuits in gate-based quantum computing. Motiv

StorySpark: Module-wise Evolutionary Search for Story Premise Generation

arXiv:2608.12336v1 Announce Type: cross Abstract: A story premise is the creative spark from which a full narrative can grow. Yet LLM-based story generation has mostly emphasized later-stage planning,

StreamReason-Bench: Can Large Language Models Reason about Event-Time Stream-Processing Semantics?

arXiv:2608.12348v1 Announce Type: cross Abstract: Streaming systems increasingly hand work to large language models (LLMs) -- writing pipelines, triaging alerts, reading logs -- and all of it assumes

Structure-aware Riemannian Growth Fields for 4D Plant Modeling

arXiv:2608.13007v1 Announce Type: new Abstract: In this paper, we introduce a novel framework for 4D plant growth modeling that reconstructs the continuous geometric and topological evolution of plant

Structure-preserving uncertainty quantification for GENERIC dynamics

arXiv:2608.12624v1 Announce Type: new Abstract: Structure-preserving machine learning embeds physical structure directly into model architectures, yet uncertainty quantification (UQ) for such hard-con

Symmetry-Breaking De Novo Crystal Generation via Markovian Jump Diffusion

arXiv:2608.13457v1 Announce Type: new Abstract: Generating crystals has recently attracted significant interest due to their broad applications in materials science. However, existing generative model

SynWeaver: Website-Prior Task and Trajectory Co-Synthesis for Web Agents

arXiv:2608.12429v1 Announce Type: cross Abstract: Web agents often struggle to generalize to unseen websites because they lack website-specific supervision. Recent exploration-based data synthesis met

TabSOM: A tabular-to-image encoding method based on self-organizing maps

arXiv:2608.13513v1 Announce Type: new Abstract: Tabular-to-image methods have emerged as novel approaches to leverage the high predictive performance of convolutional neural networks and vision transf

The AI Accountability Ecosystem in the Era of Language Models

arXiv:2608.12320v1 Announce Type: cross Abstract: This article reviews and updates the framework for accountability in AI based on account- ability ecosystems. We update the framework in light of the

The Boolean Power of ReLU

arXiv:2608.12617v1 Announce Type: new Abstract: We prove that, on finite simple undirected graphs equipped with a single Boolean node feature, the Boolean queries expressible in Sigma-MPLang, for any

The data geometry of masking diffusion: Certified-optimal schedules via unmasking growth complexity

arXiv:2608.13520v1 Announce Type: cross Abstract: We study masking diffusion for discrete sampling and introduce a path-resolved measure of data geometry called the unmasking growth complexity ({extsf

The Hidden Evolution of Disguised Visual Context inside the VLM

arXiv:2606.20077v2 Announce Type: replace-cross Abstract: Visual tokens enter Large Language Models (LLMs) as raw, foreign signals. How they are transformed into meaningful representations and interac

Thought-Aware KV Cache Compaction for Reasoning via Adaptive Attention Matching

arXiv:2608.12331v1 Announce Type: cross Abstract: Reasoning language models generate lengthy chain-of-thought (CoT) sequences whose key-value (KV) cache grows linearly and becomes a memory bottleneck

Towards Context-Aware Clinical Motion Understanding in Daily Living at Home: Freezing of Gait Detection with Egocentric Vision

arXiv:2608.13283v1 Announce Type: new Abstract: Understanding motion in daily living requires context beyond kinematics, because similar inertial patterns during activities of daily living (ADLs) can

Tracing Provenance and Detecting Tampering with Complementary LLM Watermarks

arXiv:2608.12713v1 Announce Type: cross Abstract: Watermarking LLM-generated text is an important task for tracing its provenance. Existing LLM watermarks preserve provenance under editing, but this s

Training and Benchmarking Code Generation for Physics-Inspired Animations

arXiv:2602.10840v2 Announce Type: replace Abstract: Large language models (LLMs) have been widely studied in areas such as mathematical reasoning, complex coding, and scientific problem solving. Howev

Training Under Challenge: Executable Certificates and Challenge-Closed Optimality for Neural Networks

arXiv:2608.12655v1 Announce Type: new Abstract: A flat training curve does not reveal whether a neural network has reached a global optimum, is locally trapped, is representation-limited, or is mismat

Trie Automata for Constrained Decoding over Large Finite Sets

arXiv:2608.12574v1 Announce Type: new Abstract: Large language models increasingly need to generate structured outputs that conform to predefined schemas, with one common constraint being selection fr

Uniform Herding: Exemplar Replay with Representation Refresh

arXiv:2608.13061v1 Announce Type: new Abstract: As the feature representation changes, replay must preserve the earlier classes. However, only a bounded active exemplar set can be replayed. We propose

Unifying Generative Models with Path Integrals

arXiv:2608.12438v1 Announce Type: new Abstract: We formulate generative modeling as a path integral in which flow-based, diffusion-based, variational, and adversarial models arise as different evaluat

Unsupervised training of keypoint-agnostic descriptors for flexible retinal image registration

arXiv:2505.02787v3 Announce Type: replace Abstract: Current color fundus image registration approaches are limited, among other things, by the lack of labeled data, which is even more significant in t

V-RAE: Rethinking Video Latent Spaces for Generation

arXiv:2608.13556v1 Announce Type: new Abstract: Latent video generation relies on autoencoders to define a compact space in which generative models operate. Although video autoencoder architectures ha

ViTOED: A Dataset for Target-Oriented Emotion Detection on Vietnamese Social Media Texts

arXiv:2608.12776v1 Announce Type: new Abstract: This paper introduces ViTOED, a novel dataset for target-oriented emotion detection in Vietnamese social media texts. The ViTOED comprises 10,985 user c