research

Robust Global Structure-from-Motion via View Graph Pruning

arXiv:2608.22054v1 Announce Type: new Abstract: Structure-from-Motion (SfM) aims to estimate camera poses and reconstruct 3D structures from a collection of unordered images. Compared with incremental

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Robust Lightweight Deep Learning Models for Oral Cancer Screening

DGX agent

arXiv:2608.21583v1 Announce Type: new Abstract: Oral cancer is a leading cause of mortality in low-to-middle-income countries, where a shortage of specialists delays diagnosis. While point-of-care scr

researcharxiv-cs-ai

25 Aug 2026

Robustness of IR Models to Collection Growth

arXiv:2608.23419v1 Announce Type: cross Abstract: Information Retrieval (IR) systems seek to identify relevant documents within a collection. In practical applications, collections are dynamic, with d

RSTGCN: Railway-centric Spatio-Temporal Graph Convolutional Network for Train Delay Prediction

arXiv:2510.01262v2 Announce Type: replace-cross Abstract: Accurate prediction of train delays is critical for efficient railway operations. While earlier approaches have largely focused on forecasting

SA-RSQ: A Versatile Sparse Representation Framework for Multi-modal Recommender Systems

arXiv:2608.22979v1 Announce Type: new Abstract: Deploying high-dimensional multimodal features in industrial recommender systems incurs substantial storage and latency overhead. Hard quantization is c

SANE: State Anomaly Neutralization for Stable Extreme-Context Delta-Rule Models

arXiv:2608.22354v1 Announce Type: cross Abstract: Delta-Rule recurrent models maintain a fixed-size state, enabling O(1) inference memory but potentially becoming unstable under extreme-context extrap

SAS: Segment Anything Small for Ultrasound -- A Non-Generative Data Augmentation Technique for Robust Deep Learning in Ultrasound Imaging

arXiv:2503.05916v2 Announce Type: replace-cross Abstract: Accurate segmentation of anatomical structures in ultrasound (US) images, particularly small ones, is challenging due to noise and variability

SAVER: Selective Auditing of Verbal Evidence for Error Recovery in VLM Change Reasoning

arXiv:2608.22857v1 Announce Type: new Abstract: Vision-language models (VLMs) frequently fail at visual change reasoning, even when their vision encoders contain sufficient information. We observe tha

Scalable quantum simulation of continuous-time generative models via tensor networks

arXiv:2608.21700v1 Announce Type: cross Abstract: Continuous-time flow and diffusion models are widely used across many application domains, from large-scale deployment in computer vision and protein

Search Broadly, Seek Evidence on Both Sides, Decide Narrowly: Evidence-Admissible GraphRAG for Longitudinal Clinical Event Verification

arXiv:2608.22062v1 Announce Type: new Abstract: Longitudinal clinical event-relation verification determines whether a patient record supports a specified relation among two or more clinical events. T

Seismic Acoustic Impedance Inversion Framework Based on Conditional Latent Generative Diffusion Model

arXiv:2506.13529v2 Announce Type: replace-cross Abstract: Seismic acoustic impedance plays a crucial role in lithological identification and subsurface structure interpretation. However, due to the in

Selection of Heart Sound Segments for Synchronous Classification of Multi-channel Heart Sounds

arXiv:2608.21499v1 Announce Type: cross Abstract: Cardiac auscultation remains the most cost-effective screening procedure for cardiovascular diseases, and requires listening at the four main ausculta

Selective Cross-View Consistency for World Action Models: Held-Out Viewpoint Robustness Without Test-Time Camera Information

arXiv:2608.21402v1 Announce Type: cross Abstract: World action models (WAMs) jointly denoise future video frames and robot actions, and the video prior is expected to generalize their control. Camera

SelFusion: Self-distillation for Diffusion Language Models

arXiv:2608.22898v1 Announce Type: new Abstract: Diffusion language models (DLMs) alleviate the inherent latency bottleneck of autoregressive (AR) large language models (LLMs), but their degraded gener

Semantic Reconstruction and 3-D Detection via Learned Multi-Pair Fusion in RF Imaging

arXiv:2608.23249v1 Announce Type: new Abstract: We consider a multistatic radio-frequency imaging problem with anisotropy, in which the reflection from a point depends on the positions of the transmit

Semantic Slots for Video Object-Centric Learning

arXiv:2608.21636v1 Announce Type: new Abstract: Video Object-Centric Learning (OCL) has traditionally focused on refining the encoder architecture to ensure temporal consistency. In this paper, we arg

SGHA: A Single-Loop Fully First-Order Algorithm for Nonconvex-Strongly-Convex Bilevel Optimization

arXiv:2608.23211v1 Announce Type: cross Abstract: In this work, we study the oracle complexity of finding an epsilon-stationary point for nonconvex-strongly-convex (NC-SC) bilevel optimization using o

Sharp Barron Regularity Results for Coulombic Many-Electron Wave Functions

arXiv:2608.22252v1 Announce Type: cross Abstract: We establish sharp Barron regularity for Coulombic many-electron wave functions after extraction of the universal cut-off Jastrow factors. Following t

ShotVerse: Advancing Cinematic Camera Control for Text-Driven Multi-Shot Video Creation

arXiv:2603.11421v2 Announce Type: replace Abstract: Text-driven video generation has democratized film creation, but camera control in cinematic multi-shot scenarios remains a significant block. Impli

Sigmoid Attention as a Better Substrate for Learned KV Cache Eviction

arXiv:2608.23296v1 Announce Type: cross Abstract: Learned KV-cache eviction often faces a soft-to-hard mismatch: during training, differentiable gates typically attenuate token contributions, whereas

SlotMem: Character-Addressable Internal Memory for Narrative Long Video Generation

arXiv:2607.15772v2 Announce Type: replace Abstract: Maintaining recurring character identities across scene transitions and long temporal gaps is a central challenge in narrative long video generation

Soft Label PU Learning

arXiv:2405.01990v2 Announce Type: replace Abstract: PU learning refers to the classification problem in which only part of positive samples are labeled. Existing PU learning methods treat unlabeled sa

Software Frameworks for Explainable AI in Time Series Classification: A Systematic Review

arXiv:2608.21449v1 Announce Type: new Abstract: Time series arise in a wide range of application domains and are analyzed using machine learning in decision-critical settings. Time series classificati

Sorting from Counterexamples

arXiv:2608.21579v1 Announce Type: new Abstract: Consider the following problem of learning an unknown linear order on n items. In each round, the learner guesses a complete ordering of the items and r

SpatialDiff: 3D-Aware Object Movement via Implicit Spatial Modeling

arXiv:2608.21776v1 Announce Type: new Abstract: Recent advances in image editing allow impressive manipulation of objects, existing methods still struggle to handle spatial movement in complex scenes,

Spatiotemporally Decoupled Autoregressive Diffusion Model for Human Motion Generation

arXiv:2608.23279v1 Announce Type: new Abstract: Text-driven human motion synthesis has made substantial development with two core modules of motion representation and generative architecture. For repr

Spectral partitioning for k-block averaging kernels of finite Markov chains

arXiv:2608.21466v1 Announce Type: cross Abstract: We develop spectral algorithms for selecting state-space partitions that define averaging kernels for finite, ergodic and reversible Markov chains. Fo

Spectrum-Aware Bounds on Invertibility for Privacy-Enhancing Instance Encoding

arXiv:2608.23382v1 Announce Type: new Abstract: Instance encoding is a popular empirical technique for privacy enhancement when sharing data to an untrusted server. It transforms sensitive data throug

Spinning Quadrotor: Hover Thrust Augmentation with Passive Lifting Surfaces

arXiv:2608.23163v1 Announce Type: new Abstract: Conventional multirotor aerial vehicles actively suppress yaw rotation during hover, expending power to maintain a fixed heading despite the fact that y

researcharxiv-cs-ro

SSDi8: Accurate and Efficient 8-bit Quantization for State Space Duality

arXiv:2608.21952v1 Announce Type: new Abstract: Recent advances in sequence modeling have highlighted Mamba as a state space architecture offering efficient long-range dependency modeling and providin

StereoDiffuer: Diffusion-based Progressive Geometry Modeling with Saliency Attention Perception for Stereo Matching

arXiv:2608.21710v1 Announce Type: new Abstract: With the advance of deep neural networks, the quality of disparity maps obtained through stereo matching has steadily improved. However, existing stereo

Stochastic Separability of Embedding Manifolds

arXiv:2608.22874v1 Announce Type: cross Abstract: Neurobiological studies and representation learning have observed that representations of objects belonging to the same category in high-dimensional n

STONIC: A Layered Measurement Contract for LLM Value Profiling

arXiv:2608.23411v1 Announce Type: new Abstract: LLM value studies often merge questionnaire ratings, pairwise choices, and values inferred from generated text into one profile. That merge assumes that

SuperMap: A Spatio-Temporal SLAM System for Visual-Language Navigation

arXiv:2608.22896v1 Announce Type: new Abstract: Robotic navigation in human environments requires a spatio-temporal semantic representation that can rec- oncile open-vocabulary perception with long-te

researcharxiv-cs-ro

Switched Turn-based Adaptive Source Seeking Strategy using Estimation and Information-driven Direction of Improvement

arXiv:2608.23068v1 Announce Type: new Abstract: Source seeking arises in applications such as gas leak localization, radiation monitoring, and environmental surveillance, where the origin of an unknow

researcharxiv-cs-ro

Symbolic Neural ODEs: Learning interpretable models from time-series data

arXiv:2608.22112v1 Announce Type: new Abstract: We present a machine learning framework for identifying sparse, interpretable models of dynamical systems directly from time-series data. Our approach p

SymmAdapt: Symmetrical Flow Matching for Source-Free Domain Adaptation in Medical Image Segmentation

arXiv:2608.22532v1 Announce Type: new Abstract: Domain shift across imaging modalities and acquisition sites remains a significant barrier to the clinical deployment of segmentation models. Source-fre

Tabular foundation models for non-tabular tasks

arXiv:2608.22594v1 Announce Type: new Abstract: Tabular foundation models (TFMs) have recently emerged as a promising paradigm for machine learning on tabular data, offering the ability to generalize

TANGO: Token-Aggregated Nonlinear Gating Operators for Natural and Formal Language Modeling

arXiv:2608.22117v1 Announce Type: cross Abstract: A standard Transformer block separates cross-token interaction in self-attention from a nonlinear feed-forward network applied independently at each p

Targeted Iterative Filtering

arXiv:2608.22299v1 Announce Type: new Abstract: The assessment of image denoising results depends on the respective application area, i.e. image compression, still-image acquisition, and medical image

Test-Time Adaptation for ECG Classification via SQI-Gated Self-Training and Beat-Rhythm Consistency

arXiv:2608.23347v1 Announce Type: new Abstract: Deep learning models for electrocardiogram (ECG) classification often suffer from significant performance degradation when deployed in unseen domains du

The Axiomatic Trader: Latent Regularity, Information Budgets, and the Canonical Form of a Quantitative Investment System

arXiv:2608.23416v1 Announce Type: new Abstract: Systematic trading rests on one article of faith: that regularities found in the past persist. We state it as a time-invariant mechanism driven by an un

The Chase Is the Curriculum, the Capture Anchors the Credit: Pursuit-Evasion Self-Play for Zero-Data LLM Reasoning

arXiv:2608.21871v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has become the dominant recipe for improving large language model reasoning, yet it presumes large human-

The Emergence of Relevance Through Axiomatic Attention Patterns During LoRA Fine-Tuning

arXiv:2608.23338v1 Announce Type: cross Abstract: LoRA fine-tuning is standard for adapting LLMs to reranking, but it remains unclear where in the network task-specific relevance behavior is learned a

The Geometry of Low-Resource Language Representations

arXiv:2608.23358v1 Announce Type: new Abstract: The performance gap between low- and high-resource languages in LLMs is widely known, but it remains unclear which internal model factors drive these di

The Measurement Revolution? Credible Measurement and Inference in the Age of AI

arXiv:2608.23524v1 Announce Type: cross Abstract: Artificial intelligence (AI) is transforming measurement in economics. AI models convert unstructured data, such as text and images, into structured v

The Multilingual FrameNet Corpus

arXiv:2608.23037v1 Announce Type: cross Abstract: This paper introduces the Multilingual FrameNet Corpus (mFNC), a novel resource that extends the English Berkeley FrameNet corpus by collecting and ha

The spatial anatomy of urban wildfire vulnerability: a spatially validated GeoAI framework reveals the roles of building density and vegetation moisture in structure loss during the 2025 Palisades Fire

arXiv:2608.22293v1 Announce Type: cross Abstract: Urban wildfire resilience depends on interactions among built form, vegetation condition, and extreme fire weather, yet city-scale risk models often o