Search: “research”

Differentially Private Model-X Knockoffs via Johnson-Lindenstrauss Transform

arXiv:2508.04800v2 Announce Type: replace-cross Abstract: We introduce a novel privatization framework for high-dimensional controlled variable selection. Our framework enables rigorous False Discover

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Research

Diffuse2Seg: Diffusion Models Can Segment Anything Without Supervision

DGX agent

arXiv:2609.06491v1 Announce Type: new Abstract: Open-world entity segmentation aims to predict masks for arbitrary objects across domains and at multiple granularities, from parts to whole objects. In

researcharxiv-cs-cv

9 Sept 2026

Diffusion Model in Latent Space for Medical Image Segmentation Task

arXiv:2512.01292v4 Announce Type: replace Abstract: Medical image segmentation is crucial for clinical diagnosis and treatment planning. Traditional methods typically produce a single segmentation mas

Diffusion models for eye-gaze trajectory generation using position and velocity representations

arXiv:2609.05522v1 Announce Type: new Abstract: Eye-tracking data are expensive to collect, requiring specialized hardware and controlled laboratory conditions, and difficult to share because of priva

Directed mixed membership stochastic blockmodel

arXiv:2101.02307v4 Announce Type: replace-cross Abstract: Mixed membership modeling for undirected networks has been extensively explored in network science over the past few years. Despite the substa

Discovering Natural Transformation Vulnerabilities in Black-Box Vision Models

arXiv:2609.07110v1 Announce Type: new Abstract: Natural adversarial examples (NAEs) reveal that vision models can fail under realistic semantic changes beyond norm-bounded perturbations. However, gene

Disentangling Steering Vectors

arXiv:2609.07037v1 Announce Type: new Abstract: Activation steering has emerged as a lightweight, inference-time approach to control the behavior of Large Language Models (LLMs). However, traditional

Distribution-free inference on the number of changepoints

arXiv:2609.08234v1 Announce Type: cross Abstract: Suppose we are given an ordered sequence of independent data whose distribution changes K times at unknown locations, for some unknown K geq 0. In thi

DL^3M: A Vision-to-Language Framework for Expert-Level Medical Reasoning through Deep Learning and Large Language Models

arXiv:2512.13742v3 Announce Type: replace Abstract: Medical image classifiers detect gastrointestinal diseases well, but they do not explain their decisions. Large language models can generate clinica

Do Reasoning Representations Help Humans Evaluate LLM Outputs?

arXiv:2609.09038v1 Announce Type: new Abstract: Reasoning representations are increasingly used as explanations for large language model outputs. Yet they are typically evaluated with model-centric cr

Dreaming in Flow: Generative Grounding Feedback for Self-Evolving Unified Multimodal Models

arXiv:2609.08282v1 Announce Type: new Abstract: Unified multimodal models integrate visual understanding and generation within a single network, yet the two capabilities are commonly optimized as sepa

DRIFT: Removing Diffusion Watermarks by Deflecting the Generative Trajectory

arXiv:2609.08213v1 Announce Type: cross Abstract: Diffusion watermarking embeds verifiable signals into the generative process and commonly verifies them by recovering trajectory-dependent evidence, m

DrugReason: Dynamic Multi-View Reasoning over Knowledge Graph and Language Evidence for Drug Repurposing

arXiv:2609.06779v1 Announce Type: new Abstract: Drug repurposing aims to identify new therapeutic uses for existing compounds and, compared with de novo drug discovery, offers a faster and more cost-e

Dynamic-Programming-Guided Hierarchical BPE and Empirical Analysis of Vocabulary Pruning

arXiv:2609.06898v1 Announce Type: cross Abstract: Byte Pair Encoding (BPE) constructs vocabularies through greedy pair merging, but the resulting merge order does not necessarily allocate a fixed mode

Dynamical stability for dense patterns in attractor neural networks

arXiv:2507.10383v5 Announce Type: replace-cross Abstract: Recurrent neural networks are canonical models of biological memory. In these models, memories are represented by distributed patterns of neur

ECHO: Dyadic 3D Facial Motion Generation with Asymmetric Deterministic Articulation and Stochastic Reaction

arXiv:2609.05506v1 Announce Type: cross Abstract: We propose ECHO for dyadic 3D facial motion generation under a strict dual-stream audio-only setting, formulating the problem as an asymmetric task in

ECOKV: Geometry-Aware KV Cache Eviction via Complementary Diversity Metrics

arXiv:2609.06663v1 Announce Type: cross Abstract: Although multimodal Large Language Models (MLLMs) excel in diverse tasks, their scalability remains limited by the memory and computational overhead o

Effects of model architecture and learning strategies on deep learning-based recognition of activated sludge microscopic images and comparison with quantitative image analysis

arXiv:2609.08570v1 Announce Type: new Abstract: Microscopic image analysis has long been recognized as a promising approach for monitoring activated sludge. In recent years, deep learning-based image

Efficient Learning and Symmetry Discovery under Exact Invariances

arXiv:2609.07031v1 Announce Type: new Abstract: Learning with group invariances is central to many scientific and geometric learning problems, yet its computational foundations remain poorly understoo

EigenLI: Spectral Approximations to Late Interaction

arXiv:2609.07561v1 Announce Type: cross Abstract: Late-interaction models such as ColBERT achieve strong effectiveness by representing each document with many token-level vectors, but this expressivit

EMBLEM: Enhancing Multi-script Table Detection through Masking

arXiv:2609.08330v1 Announce Type: new Abstract: Table detection is a core task in document analysis, supporting downstream applications such as information retrieval, document reconstruction, and visu

EntropyPrune: Matrix Entropy Guided Visual Token Pruning for Multimodal Large Language Models

arXiv:2602.17196v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) incur substantial inference cost due to the processing of hundreds of visual tokens per image. Although tok

Equivariance Breaks the Learning Rate

arXiv:2609.08381v1 Announce Type: new Abstract: Equivariant networks are commonly trained with Adam, yet recent work reports that matrix-structured optimizers such as Muon can perform better on these

FaceLinkGen: A Re-evaluation of Identity Leakage in Privacy-Preserving Face Recognition and Face Anonymization Systems Using Simple Distillation

arXiv:2602.02914v3 Announce Type: replace Abstract: Privacy-preserving face recognition (PPFR) hides facial appearance while retaining machine recognition, whereas perception-preserving face de-identi

Fast PAC Global Optimization via Restarted Langevin: Exploration, Exploitation, and Degenerate Cooling

arXiv:2609.06196v1 Announce Type: cross Abstract: We study the computational effort required for global optimization of a smooth, possibly nonconvex objective Gamma:R^doR. An algorithm satisfies the (

Feature Superposition in Neural Networks: From Theory to Practice

arXiv:2609.06862v1 Announce Type: new Abstract: Superposition refers to neural networks representing more features than they have dimensions. It offers a possible explanation for polysemantic neurons

Federated Binary Gating with Server-Side Vision-Language Inference for Surveillance Anomaly Classification

arXiv:2609.07403v1 Announce Type: new Abstract: Privacy-sensitive surveillance systems could benefit from large vision-language models (VLMs), but such models typically require centralized access to r

FedGenSC: Federated Generative Semantic Communication with Channel-Aware Adaptation

arXiv:2609.08593v1 Announce Type: cross Abstract: Integrating generative adversarial networks (GANs) into federated semantic communication (SemCom) is a natural progression, as generative priors can r

FILT3R: Latent State Adaptive Kalman Filter for Streaming 3D Reconstruction

arXiv:2603.18493v2 Announce Type: replace Abstract: Streaming 3D reconstruction maintains a persistent latent state that is updated online from incoming frames, enabling constant-memory inference. A k

Fine-grained Distributed Backdoor Attacks in Federated Learning

arXiv:2609.07147v1 Announce Type: new Abstract: Federated learning, as a privacy-preserving distributed machine learning paradigm, faces significant threats from backdoor attacks. Compared to centrali

Fine-Grained Visual Preprocessing and Dual-Stream Temporal Modeling for Multimodal Sentiment Analysis on Social Media

arXiv:2609.07010v1 Announce Type: new Abstract: Multimodal sentiment analysis often remains text-dominant due to raw-video noise and insufficient temporal modeling. Using CH-SIMS v2.0S, this study pro

FineHOI: Part-Aware Dense Representations for Zero-Shot Human-Object Interaction Detection

arXiv:2609.05959v1 Announce Type: new Abstract: Human-Object Interaction (HOI) detection aims to localize humans and objects in images and classify their interactions. Zero-shot HOI focuses on recogni

FIRE3D: Feed-forward Interactive 3D Scene Reconstruction Within A Minute

arXiv:2609.08848v1 Announce Type: new Abstract: We present FIRE3D, a unified framework that takes a single RGB image or casual RGB video and transforms it into simulation-ready 3D scene assets for gam

Fitting and Learning Basis-Restricted Propositional Formulas

arXiv:2609.08961v1 Announce Type: cross Abstract: For a finite set O of Boolean functions, we consider the class of propositional formulas built using the functions in O as connectives. We determine,

Flexible Motion Generation from Language and Style References

arXiv:2609.08032v1 Announce Type: new Abstract: We introduce FlexMoGen, a novel framework for flexible human motion synthesis conditioned on both natural language descriptions and motion style referen

Flexible Spectral-Normalized Neural Gaussian Process for Dynamic Aperture Prediction

arXiv:2609.08620v1 Announce Type: cross Abstract: We address the challenge of scalable uncertainty quantification in large-scale scientific applications, where complex state-of-the-art machine learnin

Forecasting the Winner of a Live Tennis Match

arXiv:2609.07617v1 Announce Type: new Abstract: With the rise of live sports betting in recent years, tennis forecasting has expanded from pre-match prediction to models that update win probabilities

Formal Bayesian Transfer Learning via the Total Risk Prior

arXiv:2507.23768v2 Announce Type: replace-cross Abstract: Existing methods for transfer learning struggle to deal with situations where the source datasets are limited and not guaranteed to be well-al

Formation of structural attractors in neuromorphic systems

arXiv:2609.06826v1 Announce Type: cross Abstract: This paper examines the theory of Invariant Structural Learning (ISL), which proposes a non-optimization approach to concept formation. Learning is in

FRAME: Factored Retrieval via Attribute Readouts for Object-Centric Scene Memory

arXiv:2609.08886v1 Announce Type: new Abstract: Language-guided robots need persistent scene memories to follow instructions, revisit objects, and resolve references to objects encountered over time.

FreqDoor: A Hidden Trojan in the Frequency Domain for Backdoor Attacks on Vision-Language Models

arXiv:2609.07048v1 Announce Type: new Abstract: Vision-language models (VLMs) have recently shown excellent progress in open-ended image-to-text generation. However, their multimodal nature makes them

From Explicit References to Scene Manifolds: Distributional Fidelity and Realism for Radiance Field Quality Assessment

arXiv:2609.07346v1 Announce Type: new Abstract: Radiance field representations such as 3D Gaussian Splatting (3DGS) enable high-quality novel view synthesis but can introduce complex, view-dependent a

From Human Labels to Literature: Semi-Supervised Learning of NMR Chemical Shifts at Scale

arXiv:2601.18524v2 Announce Type: replace Abstract: Accurate prediction of nuclear magnetic resonance (NMR) chemical shifts is fundamental to spectral analysis and molecular structure elucidation, yet

From Where to How: Continuous 4D Interaction Forecasting from Egocentric Video

arXiv:2609.08636v1 Announce Type: new Abstract: Egocentric 4D interaction forecasting aims to anticipate both where future interactions will occur in 3D and how the human body will move to realize the

FSAN: Flow State Attention Network for Aerodynamic Prediction

arXiv:2609.06660v1 Announce Type: new Abstract: Accurate aerodynamic prediction is critical for designing fuel-efficient and safe transportation systems such as aircraft and automobiles, yet tradition

Full-Page Optical Music Recognition of Handwritten Monophonic Scores

arXiv:2609.05662v1 Announce Type: new Abstract: Full-page end-to-end Optical Music Recognition seeks to transcribe entire music pages directly into symbolic notation, avoiding the limitations of tradi

Model Releases

GAN-Blot: A Controllable Structure-Style Synthesis Benchmark for Western Blot Forensics

model-releasesarxiv-cs-cv

arXiv:2609.06619v1 Announce Type: new Abstract: Western blot (WB) images are widely used as key evidence in biomedical research. Recent scientific misconduct cases reveal that WB imagery is increasing

Generalist Open-World Temporal Perception

arXiv:2609.06823v1 Announce Type: new Abstract: The next generation of artificial intelligence systems will likely be natively temporal and multimodal in both inputs and outputs: able to converse, per