Search: “model-releases”

Spectral Costs of Multinomial and Residual Resampling in High-Dimensional Particle Ensembles: A Free-Probability Analysis

arXiv:2610.16680v1 Announce Type: cross Abstract: Resampling is the standard remedy against weight degeneracy in particle filters, yet its effect on the spectrum of the particle second-moment matrix i

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Model Releases

Squeeze-Aware-YOLO: Early Channel Recalibration and Multi-Scale Fusion for Real-Time Traffic Sign Detection

DGX agent

arXiv:2610.15604v1 Announce Type: new Abstract: Traffic sign detection plays a vital role in intelligent transportation systems, supporting the safe operation of advanced driver assistance systems and

model-releasesarxiv-cs-cv

14 Oct 2026

SSM-Attack: Learning Where to Perturb for Black-Box Face Privacy

arXiv:2610.17323v1 Announce Type: new Abstract: Face recognition systems are deployed widely enough that a photograph shared online can be matched without its subject's consent. Generator-based protec

ST-GRU PredRNN-V2: A GRU-Based Reformulation of PredRNN-V2 for Video Prediction

arXiv:2610.18645v1 Announce Type: new Abstract: Video prediction requires models to capture complex spatiotemporal dependencies and to retain relevant information over long sequences. PredRNN and its

Steertuning Policies from a Few Human Videos

arXiv:2610.18711v1 Announce Type: new Abstract: Current recipes for robot learning require massive amounts of robot demonstrations to obtain robust and adaptive policies. In this work, we introduce St

Stereo-Planner: Learning Stereo-to-Trajectory Planning for Zero-Shot Sim-to-Real Quadrotor Navigation

arXiv:2610.15560v1 Announce Type: new Abstract: Existing navigation systems commonly rely on dedicated depth sensors or explicit depth reconstruction, while learning to generate trajectories directly

Stochastic Difference-of-Convex Optimization with Momentum

arXiv:2510.17503v2 Announce Type: replace Abstract: We study the online stochastic difference-of-convex (DC) program min_{x in R^n} F(x) = G(x) - H(x) + r_1(x) - r_2(x), which covers sparse learning w

Streamline pathology foundation model by cross-magnification distillation

arXiv:2509.23097v4 Announce Type: replace Abstract: Foundation models (FM) have transformed computational pathology but remain computationally prohibitive for clinical deployment due to their massive

Successful but Unsafe: An Analytical Benchmark for Revealing Collisions in Vision-and-Language Navigation

arXiv:2610.14682v1 Announce Type: new Abstract: Vision-and-language navigation (VLN) agents are typically evaluated by whether they reach a target and how efficiently they follow an instructed route,

SyncReward: Human-Aligned Synchronization Reward for Audio-Visual Generation

arXiv:2610.16338v1 Announce Type: new Abstract: Recent years have witnessed rapid progress in joint audio--visual generation. However, audio--visual synchronization remains a challenge, as generated s

Taming Softmax at the Limits of Muon: A Unified Approach through Hilbert Geometry

arXiv:2610.17588v1 Announce Type: new Abstract: Muon controls weight updates through the RMS movement of a linear layer's output. This implicitly treats the linear output as a proxy for the full modul

Tanawpamana: Benchmarking Vision-Language Models on Philippine Cultural Heritage Sites

arXiv:2610.17596v1 Announce Type: new Abstract: Vision-language models are increasingly used to identify and describe places, yet their recognition and knowledge of specific cultures remain poorly und

TempoKV: Predictive KV Cache Quantization for Autoregressive Video Generation

arXiv:2610.15324v1 Announce Type: new Abstract: Autoregressive (AR) video diffusion models enable streaming generation of long videos but suffer from significant memory overhead due to the rapidly gro

Tev: Scaling Long-Horizon Agentic Environments with Dense Progress Rewards

arXiv:2610.18868v1 Announce Type: cross Abstract: Long-horizon agents have drawn growing attention for their ability to work autonomously -- from hours to days -- on economically valuable tasks, a cap

Text-Guided Medical Image Segmentation via Residual Aggregation and Dense Alignment Representations

arXiv:2610.14944v1 Announce Type: new Abstract: Specifying segmentation targets with natural language provides flexible semantic conditioning for medical image segmentation. However, existing methods

Text-Vision Co-Instructed Image Editing

arXiv:2606.16767v2 Announce Type: replace Abstract: Existing image editing methods can be generally categorized into textual instruction-based and visual prompt-based ones. Textual instructions are se

The Last Remote Sensing Model Built by Humans? Casting Any Earth Observation Task as Recursive Self-Improvement

arXiv:2610.18845v1 Announce Type: new Abstract: Earth observation (EO) models are still built by hand. For each new task, experts design a training recipe and tune it against a benchmark. We show that

Through the PRISM: Preference Representation in Intermediate States of Video Diffusion Models

arXiv:2606.20310v2 Announce Type: replace Abstract: Video reward models are central to aligning video diffusion models with human preferences, yet existing ones are external vision-language models tha

TILE: Bridging LLMs and Table Foundation Models for Tabular Learning with Strings

arXiv:2610.17065v1 Announce Type: new Abstract: Real-world tables are often heterogeneous, combining numerical features with free-form string columns. Table foundation models (TFMs) excel on numerical

Time Window Optimization for Motor Imagery Classification via Temporal Structure Embedded Reinforcement Learning

arXiv:2610.16921v1 Announce Type: cross Abstract: Online motor imagery-based brain-computer interfaces (MI-BCIs) typically decode continuous EEG using fixed-length sliding windows that may be misalign

Tiny Recursive Message Passing

arXiv:2610.18649v1 Announce Type: new Abstract: Message passing neural networks have shown remarkable performance in algorithmic and constraint reasoning, due to their ability to encode the structure

To Defer or Not to Defer? Online Learning with LLMs and Congested Experts

arXiv:2610.15128v1 Announce Type: new Abstract: Modern AI systems increasingly combine large language models (LLMs) with human experts, using the LLM to handle routine queries while deferring uncertai

TopoPilot: Reliable Conversational Workflow Automation for Topological Data Analysis and Visualization

arXiv:2603.25063v2 Announce Type: replace-cross Abstract: Recent agentic systems demonstrate that large language models can generate complex codebases from natural language prompts. Despite this progr

Toward a Multimodal Foundation Model for Plasma State Reconstruction

arXiv:2610.15076v1 Announce Type: new Abstract: Plasma experiments observe coupled physical states through sparse, heterogeneous, and incomplete diagnostics. We present a proof of concept toward a mul

Toward Zero-Shot Point Cloud Registration Across Diverse Scales, Scenes, and Sensor Setups

arXiv:2601.02759v2 Announce Type: replace Abstract: Some deep learning-based point cloud registration methods struggle with zero-shot generalization, often requiring target-domain retraining, fine-tun

Towards a Systematic Study of Embodied System 2 over Full Task Execution Cycles

arXiv:2610.17657v1 Announce Type: new Abstract: An embodied brain, or System 2, must turn an abstract goal into actions while discovering relevant scene conditions and checking whether executed skills

Towards Dependable Optical Flow: Benchmarks for Real-World Spatiotemporal Corruptions

arXiv:2411.14865v2 Announce Type: replace-cross Abstract: Optical flow estimation is a fundamental task in dynamic scene understanding and computer vision. While recent deep models achieve impressive

Towards Green AI: Evaluating Energy Efficiency for Quantized LLM Inference

arXiv:2610.17531v1 Announce Type: new Abstract: While it is known that quantization of large language models (LLMs) reduces memory usage via lower-bit weights, studies quantifying the resulting impact

Towards Physically Grounded Articulated 3D Assets: A Multi-Agent Pipeline and Benchmark

arXiv:2610.13947v2 Announce Type: replace Abstract: In this paper, we study physically grounded articulated 3D asset generation---moving the goal from reproducing how objects look to capturing how the

Towards Universal Calibration for In-Context Classification

arXiv:2610.17096v1 Announce Type: new Abstract: In-Context Learning (ICL) has received a lot of interest recently due to its ability to improve classification accuracy for new tasks without having to

Training LLMs for Multi-Agent Collaboration with Verifiable Information Rewards

arXiv:2610.17893v1 Announce Type: cross Abstract: Effective collaboration among large language model (LLM) agents in multi-agent systems requires sharing relevant evidence, requesting missing informat

Truncation Samplers Are Nested: Comparing Decoding Rules Is a Measurement Problem

arXiv:2610.15570v1 Announce Type: cross Abstract: Settling one comparison between two truncation samplers has cost six thousand A100-hours, and nothing says in advance how far apart two samplers can b

Trust Before Autonomy: Rethinking Agentic Remote Sensing for Crisis Response

arXiv:2610.18789v1 Announce Type: new Abstract: Agentic remote sensing is evaluated on how many questions it can answer, whereas crisis response depends on whether its answers can be relied on and how

TSRL: Trigger-based Supervised Reinforcement Learning for Continual Agent Training

arXiv:2610.17726v1 Announce Type: new Abstract: Large language model (LLM) agents excel at complex, multi-step tasks but suffer from catastrophic forgetting during continual learning--acquiring new sk

TurnCost: Turns, Not Observations: Cache-Aware Loop Engineering for Coding Agents

arXiv:2610.15093v1 Announce Type: cross Abstract: AI coding agents operate in iterative loops: they modify code, run tools, inspect the results, and decide what to do next. We call the design of this

Two For The Price Of One: Curvature-Aware Pruning Preserves Influence Functions Too

arXiv:2610.18516v1 Announce Type: new Abstract: Post-training pruning enables efficient deployment, but conventional methods do not explicitly preserve internal-gradient alignment between sparse and d

UEPS: Robust and Efficient MRI Reconstruction

arXiv:2603.18572v2 Announce Type: replace-cross Abstract: Deep unrolled models (DUM) have become the state-of-the-art for accelerated MRI reconstruction, yet their robustness under domain shift remain

Understanding Hidden Spatial Preferences in Bayesian Optimization

arXiv:2610.14696v1 Announce Type: new Abstract: Bayesian optimization uses posterior uncertainty to decide where to explore, but this uncertainty is not spatially neutral. On bounded domains, Gaussian

UniDeblur: Unified Motion Deblurring via Fourier Convolution Learning

arXiv:2610.12941v2 Announce Type: replace Abstract: Image deblurring is a fundamental task in computer vision, yet existing methods mainly specialize in isolated scenarios. Consequently, the deblurrin

UniLAP: A Unified Latent Action Policy for Cross-Embodiment Manipulation

arXiv:2610.16969v1 Announce Type: cross Abstract: Latent Action Models (LAMs) can capture manipulation priors from action-free videos, but discrete latents usually impose a granularity bottleneck, lim

Universal Distributed Feature Extraction Complementary to Side Information via H-Score

arXiv:2610.16707v1 Announce Type: cross Abstract: This paper considers a distributed estimation system where edge nodes transmit averaged features to a center node for parameter estimation. A key chal

Unsupervised Domain Adaptation for Cardiac Segmentation: Towards Structure Mutual Information Maximization

arXiv:2204.09334v4 Announce Type: replace-cross Abstract: Unsupervised domain adaptation approaches have recently succeeded in various medical image segmentation tasks. The reported works often tackle

Value-Preserving Action Quantization

arXiv:2610.17252v1 Announce Type: cross Abstract: Search-based policy learning, such as Monte Carlo tree search (MCTS), offers the flexibility to trade runtime computation for data efficiency and adap

Variable Input Masked Autoencoders for Wrist-Worn Accelerometry

arXiv:2610.17383v1 Announce Type: new Abstract: Large-scale repositories of wearable sensor data have enabled the development of foundation models for human activities and behavior. However, existing

Video-Arena: A Scalable Agentic Video Benchmark for Spatiotemporal Capability

arXiv:2610.14158v1 Announce Type: new Abstract: Understanding and tracking a dynamic world are fundamental to visual intelligence. Existing video benchmarks provide limited insight into whether models

VideoEvoHarness: Self Evolving Agent Harness from Unlabeled Videos for Video Understanding

arXiv:2610.15389v1 Announce Type: new Abstract: Video understanding agents rely on a harness to acquire evidence, use tools, and reason, but improving it requires substantial effort. Recent self evolu

VIEWCRAFT: Evolving What Multimodal Agents See and How They Read It

arXiv:2610.15915v1 Announce Type: new Abstract: Reusable skills improve multimodal agents without updating model weights, but their effectiveness depends on both the evidence presented and the procedu

VisExMEM: Visual Evidence-Based Explainable Multimodal Evaluation Metric

arXiv:2610.16441v1 Announce Type: new Abstract: Current image-text evaluation often relies on a global score, which gives limited insight into which semantic details are supported by the image. Explai