Search: “research”

SIMANF: Sample Free Learning of Unnormalized Distributions via Simulated Annealing in Normalizing Flows

arXiv:2609.32279v1 Announce Type: new Abstract: Efficiently learning and sampling from high dimensional, multimodal unnormalized distributions without target samples remains a challenging problem. Alt

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Simple Diffusion Language Models Are More Effective Few-Step Generators Than Reported

DGX agent

arXiv:2609.33947v1 Announce Type: cross Abstract: Diffusion language models (DLMs) promise fast parallel generation, yet high-quality samples often require large number of refinement steps, which dimi

researcharxiv-cs-lg

29 Sept 2026

Simplex Diffusion Models

arXiv:2609.35553v1 Announce Type: new Abstract: Diffusion models have revolutionized generative modeling for continuous data through the gradual refinement of a belief state. This iterative refinement

Simulating Robotic Locomotion in Sand: Resistive Force Theory in an Open-Source Physics Engine

arXiv:2606.19504v2 Announce Type: replace Abstract: Recent advancements in Resistive Force Theory (RFT) enable approximation of ground reaction forces for locomotion in sand without the computational

researcharxiv-cs-ro

Simulation-Free Learning of GP-SDEs from Irregular Observations

arXiv:2609.33112v1 Announce Type: new Abstract: Gaussian process stochastic differential equations (GP-SDEs) provide a flexible Bayesian model for unknown continuous-time state dynamics with uncertain

SincDPNet: Interpretable Raw-Waveform Bathroom Activity Recognition for Assistive Living

arXiv:2609.34907v1 Announce Type: cross Abstract: Bathroom acoustic-event recognition can support ambient assisted living in settings where continuous video monitoring is undesirable. However, practic

Sliced Orlicz-Wasserstein

arXiv:2609.32847v1 Announce Type: cross Abstract: We propose sliced Orlicz-Wasserstein (SOW) distance which is a generalization of sliced Wasserstein (SW) distance. SOW replaces the L^p norm in SW wit

Small transformers track Bayesian evidence for latent common causes via a context-invariant mechanism

arXiv:2609.35161v1 Announce Type: new Abstract: We present an in-depth investigation of how a form of Bayesian reasoning about common causes can emerge as a cross-contextual generalization in small, t

Smoothing the Semantic Landscape: Generalizable AI-Generated Image Detection via Text-Induced Flatness

arXiv:2603.00717v3 Announce Type: replace Abstract: Recent advances in generative models have exposed a fundamental weakness of image fake detectors: they often fail to generalize to unseen synthesis

SNaP: One-Step Posterior Sampling for Noisy Inverse Problems

arXiv:2609.34071v1 Announce Type: new Abstract: Diffusion and flow-matching models can produce high-quality posterior samples for inverse problems, but typically require tens to thousands of network e

SocialHumanoid: Towards Expressive Humanoid Behavior via One-Step Co-Speech Motion Generation

arXiv:2609.33311v1 Announce Type: cross Abstract: Humanoid robots are increasingly expected to serve as embodied social agents that communicate naturally with humans through face-to-face interaction.

Source Anchoring for Physical Consistency in Flow Matching Models

arXiv:2609.33510v1 Announce Type: new Abstract: Deep generative models are used to solve partial differential equations and model distributions of physical system states, but ensuring that the generat

Sparsity by Default: The Theory and Practice of ARD in Gaussian Process Regression for Variable Selection

arXiv:2609.33550v1 Announce Type: cross Abstract: Automatic relevance determination (ARD) is the standard device for input selection in Gaussian process (GP) regression. By giving the covariance kerne

SpatialSkill: Self-Evolving Skills for Cross-View Spatial Reasoning

arXiv:2609.34124v1 Announce Type: new Abstract: Cross-view spatial reasoning requires a model to align different viewpoints into a coherent spatial representation, yet this ability remains challenging

SpecRegMatch: Robust Semi-Supervised Regression for Vehicle Interior Noise Prediction

arXiv:2609.34111v1 Announce Type: cross Abstract: The rapid advancement of artificial intelligence has observed increased application in predicting vehicle interior noise levels within the automotive

Spectral Super-Resolution using Spatial-Spectral Residual Operator Networks

arXiv:2609.35410v1 Announce Type: new Abstract: Spectral super-resolution of multispectral satellite images can enable high temporal- and spatial-resolution hyperspectral satellite imagery at a modest

SPIDER: Multi-Layer Semantic Token Pruning and Adaptive Sub-Layer Skipping in Multimodal Large Language Models

arXiv:2609.34977v1 Announce Type: new Abstract: Multimodal Large Language Models face significant efficiency challenges that stem from two distinct yet coupled sources: data redundancy and computation

SpikeLite: Lightweight Spiking Neural Networks for Time-Series Forecasting

arXiv:2609.35097v1 Announce Type: new Abstract: Spiking neural networks (SNNs) offer an energy-efficient paradigm for time-series forecasting through spike-driven computation. However, recent SNN fore

SPINET: Sheaf Protein Inverse Folding Network

arXiv:2609.34153v1 Announce Type: new Abstract: Proteins change shape as they function, yet most inverse folding models predict amino acid sequences from a single, fixed backbone. A central challenge

Squeeze3D: Extreme Neural Compression with Latent Space Bridging

arXiv:2506.07932v2 Announce Type: replace-cross Abstract: We propose Squeeze3D, a novel framework that leverages implicit prior knowledge learnt by existing pre-trained encoders and decoders to compre

StarBOA: Real-Time Mamba State-Space Unrolling for Sparse Radar Micro-Doppler in ISAC Networks

arXiv:2609.33408v1 Announce Type: new Abstract: In Integrated Sensing and Communications (ISAC), radar sensing must operate under chirp subsampling with up to 90% missing data. An attention-based base

StatD2GAN: When Calibration Masks Generator Quality in Held-Out Evaluation of Synthetic Weather Sequences

arXiv:2609.33761v1 Announce Type: new Abstract: Generative models for multivariate weather series are routinely evaluated with pooled distributional metrics computed after marginal calibration. We sho

Statistical Learning of Contractive Dynamical Representations for Composite Adaptive Control

arXiv:2609.35758v1 Announce Type: cross Abstract: We present a representation-learning framework for composite adaptive tracking control under dynamically coupled disturbances. The framework connects

Statistical Testing for Multiple Instance Learning via Selective Inference with Applications to Computational Pathology

arXiv:2609.31712v1 Announce Type: new Abstract: Multiple instance learning (MIL) is widely used in computational pathology because it enables weakly supervised analysis of whole-slide images (WSIs) wi

Steering Language Model Goals with Value Transplant

arXiv:2609.34056v1 Announce Type: new Abstract: Reasoning models often act as if they pursue goals, but their efforts are not always directed toward what users intend, sometimes leading them to pursue

Still There, No Longer Seen: Exposing Compression-Induced Risk in Large Vision-Language Models

arXiv:2609.35002v1 Announce Type: new Abstract: Visual token compression reduces the inference cost of Large Vision-Language Models (LVLMs). However, aggregate robustness measures do not reveal whethe

Stringological sequence prediction I: efficient algorithms for predicting highly repetitive sequences

arXiv:2603.26852v2 Announce Type: replace-cross Abstract: We propose novel algorithms for sequence prediction based on ideas from stringology. These algorithms are time and space efficient and satisfy

Structure-Adaptive Tree Field Integrators

arXiv:2609.34025v1 Announce Type: cross Abstract: We present a new class of near-linear algorithms for efficiently integrating general tensor fields defined on trees with distance dependent kernels, t

Structured Latent Modeling for Supervised Multimodal Information Decomposition

arXiv:2609.35502v1 Announce Type: new Abstract: Multimodal prediction relies on diverse forms of evidence: information repeated across modalities, cues specific to a single source, and complex cross-m

Structured Neural SDEs for Functional Calibration

arXiv:2609.34831v1 Announce Type: new Abstract: Neural Stochastic Differential Equations (Neural SDEs) provide flexible continuous-time generative models, but generic neural drift and diffusion networ

Structuring Relations Among Learning Paradigms via Protocol--Objective--Resource Reductions

arXiv:2609.32766v1 Announce Type: new Abstract: Modern machine learning spans supervised, transfer, continual, meta-learning, and related regimes that often reuse the same hypothesis classes, architec

Sub-Model Short-Term Memory Convolutions for Keyword Spotting Systems on Device

arXiv:2609.35005v1 Announce Type: cross Abstract: Keyword Spotting (KWS) is becoming increasingly important as voice-controlled devices grow more widespread. While voice interaction with smartphones a

Subgroup Rank-1 Lattice for Practical High-dimensional Black-box Integral Approximation

arXiv:2609.35177v1 Announce Type: new Abstract: Estimating integrals of black-box, high-dimensional functions, from expectations and kernel mean embeddings to the softmax kernel in self-attention, is

SubjectAnchor: Subject-Aware Memory-to-Video for Multi-Shot Storytelling

arXiv:2609.34502v1 Announce Type: new Abstract: We present SubjectAnchor, a Subject-Aware Memory-to-Video paradigm for multi-shot storytelling in which the current shot is generated by conditioning on

SubRot: Signed Gradient Subspace Calibration for VLM Rotation Quantization

arXiv:2609.34884v1 Announce Type: new Abstract: Post-training quantization reduces the deployment cost of vision-language models (VLMs), but preserving multimodal capabilities at low bit widths remain

Suitable Measures for the Potential Operational Utility of AI NWP Rainfall Forecasts Over Africa

arXiv:2609.31775v1 Announce Type: cross Abstract: Artificial intelligence (AI)-based weather prediction is approaching the skill of physical numerical weather prediction (NWP) systems at a fraction of

Summarize Before Grounding: Query-Guided Chunk Condensation for Long-Video Temporal Grounding

arXiv:2609.34598v1 Announce Type: new Abstract: Video temporal grounding (VTG) aims to localize the video interval corresponding to a language query. Recent large vision-language models (LVLMs) show g

Superposed Inference for Hyperdimensional Computing

arXiv:2609.32320v1 Announce Type: new Abstract: Hyperdimensional computing (HDC) is attractive for efficient and robust learning, but conventional inference still encodes every query independently, re

SurgGMF: Fully Causal Gaussian Motion Forecasting for Anticipatory Surgical Scene Rendering

arXiv:2609.34733v1 Announce Type: new Abstract: Dynamic surgical scene modeling is essential for robotic perception, simulation, and decision support. Although existing neural rendering methods enable

Symmetric Composition of Anisotropic Operators for Global Subseasonal-to-Seasonal Climate Forecasting

arXiv:2602.15040v2 Announce Type: replace-cross Abstract: Accurate global Subseasonal-to-Seasonal (S2S) climate forecasting is critical for disaster preparedness and resource management, yet it remain

T-SNN: Temporal Simplicial Neural Network for EEG Decoding

arXiv:2609.34002v1 Announce Type: new Abstract: Decoding brain states requires models that capture both the evolution of neural activity and interactions among groups of brain regions. Existing EEG me

TACO: Training-free Sound Prompted Segmentation via Semantically Constrained Audio-visual CO-factorization

arXiv:2412.01488v4 Announce Type: replace-cross Abstract: Large-scale pre-trained audio and image models demonstrate an unprecedented degree of generalization, making them suitable for a wide range of

Tags for DAGs: Graph Refinement with Meta-Informed Relations

arXiv:2506.19459v2 Announce Type: replace Abstract: Causal discovery has shifted from data-centric methods to hybrid strategies that integrate semantic knowledge from experts or large language models

Taming the Greeks: Option Portfolios with Inductive Biases

arXiv:2609.33767v1 Announce Type: cross Abstract: We present an end-to-end deep learning framework for systematic options trading that directly embeds hedging behavior through explicit control of port

TANGO: Watermarking Masked Diffusion Language Models in Token Pairs

arXiv:2609.35224v1 Announce Type: new Abstract: Masked-diffusion language models fill in masked positions in parallel and in no fixed order. Most practical text watermarks assume left-to-right generat

Task-Aware Discretization of Differentiable Logic Gate Networks

arXiv:2609.33747v1 Announce Type: new Abstract: Differentiable logic gate networks (DLGNs) enable gradient-based training of highly efficient Boolean networks by relaxing discrete logic gates during t

TC-ADA: One-Shot Active Domain Adaptation for Semantic Segmentation

arXiv:2609.33432v1 Announce Type: new Abstract: Manual dense annotation remains a major obstacle to deploying semantic segmentation models in new driving environments. Active domain adaptation (ADA) s

Temporal-Attention Head Specialization During Video Diffusion Training

arXiv:2609.31654v1 Announce Type: new Abstract: Video diffusion transformers depend on temporal attention to coordinate information across frames, yet nearly everything known about this mechanism come