Search: “model-releases”

SepRQ : Self-Supervised Speech Mixture Representation Learning via Mask-Free, Multi-Scale Source Separation

arXiv:2610.04690v1 Announce Type: cross Abstract: Self-supervised learning (SSL) is standard for speech representation learning, but mainstream models are designed around single-speaker audio, limitin

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SFlexRCA: Lightweight, Scalable, and Flexible Root Cause Analysis for IIoT Edge Systems

DGX agent

arXiv:2610.04893v1 Announce Type: new Abstract: Industrial Internet of Things (IIoT) systems generate high-dimensional sensor telemetry from interconnected components, where faults can propagate acros

model-releasesarxiv-cs-lg

6 Oct 2026

Shapley-based Structural Analysis of Neural Calibration for Stochastic Volatility Models

arXiv:2610.03076v1 Announce Type: cross Abstract: Neural network-based approaches have emerged as efficient alternatives to traditional optimization-based procedures for the calibration of stochastic

Singular parameters and missing limits in neural PDE solvers

arXiv:2610.06770v1 Announce Type: cross Abstract: Neural solvers for partial differential equations (PDEs) can approach an accurate solution while their parameters grow without bound. In such cases, t

SkillScriptBench: Benchmarking Self-Evolution of Executable Agent Skill Packages Beyond Markdown

arXiv:2610.04008v1 Announce Type: cross Abstract: Executable Agent Skills combine natural-language instructions and scripts into reusable packages for LLM agents, and revising them requires fixing err

SoccerTrack v2: A Full-Pitch Panoramic Video Dataset for Game State Reconstruction and Ball Action Spotting

arXiv:2508.01802v2 Announce Type: replace Abstract: Soccer analytics draws on two kinds of information: spatio-temporal data describing where players and the ball are, and event data describing what t

Soft Strategy Selection for Batch-Mode Active Learning

arXiv:2610.05544v1 Announce Type: new Abstract: Real-world deployment of active learning typically forces practitioners to choose an acquisition strategy before any data is labeled. This is a daunting

Sparse-View 4D Gaussian Splatting via Spatiotemporal Priors and Generative Assistance

arXiv:2610.04606v1 Announce Type: new Abstract: We present a 4D Gaussian Splatting framework for the Sparse-View Track of the SIGGRAPH Asia 2026 Volumetric Video Challenge, which requires dynamic scen

SpatialChain: A Benchmark for Auditing Spatial Reasoning Faithfulness in VLMs

arXiv:2610.06413v1 Announce Type: new Abstract: Thinking-enabled vision-language models (VLMs) report ever-higher accuracy on spatial benchmarks, yet final-answer scores cannot reveal whether a correc

Specific Algorithmic Interpretability of Neural Networks: A Case Study on Textures

arXiv:2610.04413v1 Announce Type: new Abstract: We develop a principled framework for constructing neural networks whose specific parameter realizations admit an explicit algorithmic interpretation. E

StageVLN: Spatial and Trajectory Auxiliary Guidance for Efficient Vision-Language Navigation

arXiv:2610.05664v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) policies increasingly benefit from strong semantic priors provided by large vision-language models (VLMs). However,

StagQ: Constraint-Driven Multi-Precision Weight Quantization for LLMs

arXiv:2610.05977v1 Announce Type: new Abstract: Serving a large language model (LLM) across a fleet of deployments requires several weight-precision operating points. Multi-precision formats serve the

Stochastic Adaptive Fourier Decomposition for Operator Learning

arXiv:2610.04241v1 Announce Type: new Abstract: Fourier Neural Operators (FNOs) offer an efficient paradigm for solving partial differential equations (PDEs). However, FNOs rely on a fixed Fourier bas

Sven: Singular Value Descent as a Computationally Efficient Natural Gradient Method

arXiv:2604.01279v2 Announce Type: replace Abstract: We introduce Sven (Singular Value dEsceNt), a new optimization algorithm for neural networks that exploits the natural decomposition of loss functio

TAPDreamer: Transferable Adversarial Patches for World Action Models

arXiv:2610.06814v1 Announce Type: new Abstract: World models learn to predict how their environment will evolve, making them an important foundation for general-purpose robotic control. Yet world acti

Task Vector Descent: Learning from Non-IID Batches

arXiv:2610.05402v1 Announce Type: new Abstract: A central challenge in continual learning is to acquire new knowledge without forgetting what the model has already learned. This challenge appears in l

The Llama 3 Herd of Models

arXiv:2407.21783v3 Announce Type: cross Abstract: Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It i

The sublevel Flood bifiltration: towards scalable 2-parameter persistent homology

arXiv:2610.05441v1 Announce Type: cross Abstract: Multiparameter persistent homology is a rapidly developing branch of topological data analysis that improves the robustness of single-parameter persis

The Surrogate Is Not the Reward: Post-Surrogate Primary-Outcome Acquisition in Contextual Bandits

arXiv:2610.06610v1 Announce Type: cross Abstract: We study contextual bandits in which a surrogate is observed after the action but before the learner decides whether to acquire the primary outcome th

The Universal Weight Subspace Hypothesis

arXiv:2512.05117v3 Announce Type: replace-cross Abstract: We show that deep neural networks trained across diverse tasks exhibit remarkably similar low-dimensional parametric subspaces. We provide the

THYME: Temporal Hierarchical-Cyclic Interactivity Modeling for Video Scene Graphs in Aerial Footage

arXiv:2507.09200v2 Announce Type: replace Abstract: The rapid proliferation of video in applications such as autonomous driving, surveillance, and sports analytics necessitates robust methods for dyna

TIGER: Time-Series Classification with In-Context-Learning Gated Ensemble of Representations

arXiv:2610.06156v1 Announce Type: new Abstract: A representation family is a distinct way of extracting features from time series. Ensemble algorithms that combine several representation families rema

TIRMamba: A Thermal-Prior-Modulated State-Space Network for Sub-Million-Parameter Infrared Image Super-Resolution

arXiv:2610.05182v1 Announce Type: cross Abstract: Infrared image super-resolution is currently led by Mamba-based networks with 26 to 37 million parameters, which are difficult to deploy on the airbor

Toward Reliable Infant Pose Estimation: A Training-Dynamics Approach to Noisy Annotation Detection

arXiv:2610.06423v1 Announce Type: new Abstract: Spontaneous movement analysis in preterm infants relies increasingly on markerless pose estimation (PE) to derive clinically relevant motion biomarkers

Training-Free Transformer Merging via Sequential Local Operator Alignment

arXiv:2610.06415v1 Announce Type: new Abstract: Training-free model merging aims to combine multiple fine-tuned models into a single model without further optimization on labeled data. Yet, in transfo

Trajectory-Derived Confidence for Reliable, Resource-Aware Clinical Text-to-SQL Agents

arXiv:2610.04156v1 Announce Type: cross Abstract: LLM agents for clinical text-to-SQL applications reason autonomously over multiple steps but cannot assess whether their own reasoning or outputs can

TreeWalker: Partial Evaluation for Grouped Tree-Ensemble Inference

arXiv:2610.03939v1 Announce Type: new Abstract: Many inference workloads evaluate a trained tree ensemble on row groups that share feature values: discrete-time survival models expand each patient int

Two-Sample Testing via Path-based Inference

arXiv:2610.05684v1 Announce Type: cross Abstract: Modern deep generative models are primarily studied for their ability to generate realistic samples, yet the generative dynamics they learn can also s

ufakzeka-karar: An Open Turkish Typed-Decision Model with Order-Invariant Option Scoring

arXiv:2610.06744v1 Announce Type: cross Abstract: ufakzeka-karar is an open Turkish decision model with 182,494,466 parameters. Given a Turkish text and questions of a fixed answer type (a choice, a l

UltraDub: Towards Authentic Dubbing by Unifying Visually-Steered Flow Learning and Trajectory Guidance

arXiv:2610.05932v1 Announce Type: new Abstract: Visual voice cloning requires intelligible, speaker-consistent speech synchronized with visible articulation. However, sequential multimodal conditionin

UnAct: Gradient-Free Unlearning via Targeted Activation Intervention

arXiv:2610.04426v1 Announce Type: cross Abstract: Machine unlearning seeks to remove the influence of designated training data from a trained model without retraining from scratch. Retrain-free method

Understanding Clustering in Slot Attention via Particle Dynamics

arXiv:2610.04493v1 Announce Type: cross Abstract: Studying attention through the lens of interacting particle dynamics has shown how token clustering can emerge from the underlying dynamics. We extend

UniBRep: Learning Unified Geometry and Topology for Image-conditioned B-Rep Generation

arXiv:2610.04092v1 Announce Type: new Abstract: Generating a boundary representation (B-rep) conditioned on a single image requires faithful reconstruction of geometry, valid topology, and support for

Uniform-in-time convergence bounds for Persistent Contrastive Divergence algorithms

arXiv:2510.01944v2 Announce Type: replace-cross Abstract: We propose a continuous-time formulation of a noisy persistent contrastive divergence (PCD)-like method for maximum likelihood estimation (MLE

UniSlider: Perceptually Uniform Sliders for Continuous Image Editing

arXiv:2610.06831v1 Announce Type: new Abstract: Sliders provide an intuitive interface for continuous image editing. In current generative approaches, however, the slider is simply a rescaling of the

Valid Stopping in Adaptive Generator-Verifier Loops

arXiv:2610.06432v1 Announce Type: cross Abstract: Numerous agentic workflows are based on a generator-verifier loop: a generator proposes candidates, a cheap verifier scores them, and the workflow ter

VERA: Verdict-Conditioned Reliability for Adaptive LLM Judges

arXiv:2610.05452v1 Announce Type: new Abstract: Accurately estimating judgment reliability is a central challenge in adapting LLM judges to newly verified feedback while preserving previously learned

Video Encoders Built on Image Representations

arXiv:2610.06616v1 Announce Type: new Abstract: The design of a video encoder determines when frames begin to interact and which frame-specific visual evidence remains accessible to the language model

Video2World: Benchmarking Coding Agents for Interactive World Modeling from Embodied Videos

arXiv:2610.04432v1 Announce Type: new Abstract: Building interactive simulators from real-world observations is a promising way to scale embodied data, but current pipelines still rely heavily on manu

VideoResearchAgent: Grounded Task Synthesis and Sim-to-Real RL for Open-Web Video Research

arXiv:2610.04911v1 Announce Type: cross Abstract: Existing deep research agents are designed primarily for text- and image-based web sources, while video reasoning systems typically assume that releva

VideoTapestry: Query-Adaptive Memory Refinement for Multi-Agent Long-Video Understanding

arXiv:2610.06672v1 Announce Type: new Abstract: Long-video understanding places substantial demands on memory, as answering questions often requires retrieving information distributed across extended

vMF Sentence LDA: A Spherical Topic Model over Sentence Embeddings

arXiv:2610.05095v1 Announce Type: cross Abstract: Latent Dirichlet Allocation (LDA) and models derived from it remain widely used topic models. LDA observes each document as a bag-of-words and models

Voltic: Distinguishing Volatility from Stochasticity in Recurrent Memory

arXiv:2610.05700v1 Announce Type: new Abstract: Recurrent sequence models must decide how strongly to overwrite their memory at each token. Read as Bayesian filtering, this write is the gain of a Kalm

WasserMan: Benchmark for Underwater Manipulation Policy Learning

model-releasesarxiv-cs-ro

arXiv:2610.04536v1 Announce Type: new Abstract: Underwater manipulation couples visual decisions, contact forces and a thruster-controlled floating base. We introduce WasserMan, to our knowledge the f

Watermarks and Fingerprints as Soft Bindings for Content Provenance: An Open-Licence Benchmark for Images, Audio and Video

arXiv:2610.04151v1 Announce Type: new Abstract: Content-provenance standards such as C2PA let a platform recover a stripped manifest through a soft binding: an invisible watermark read from the conten

Weave Mamba Fusion: Global Cross-Scale Interaction for Lightweight Face Detection

arXiv:2610.05865v1 Announce Type: new Abstract: Feature pyramid methods, from FPN to BiFPN, have achieved strong performance in face detection by fusing multi-scale features. However, detecting faces

Weight Decay and Neuron Condensation: A Three-Stage Analysis of Two-Layer ReLU Networks

arXiv:2610.04533v1 Announce Type: new Abstract: Weight decay is widely used as a regularization technique in neural network training, yet its role in neuron condensation (parameter direction alignment

What Do Verifiable Rewards Teach Video-Language Models About Time? A Controlled Multi-Model Study

arXiv:2610.03792v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has produced large reasoning gains in language models, and verifiable video benchmarks make it app