Search: “models”

DriveMotion: A Large-Scale Multi-Source Benchmark for Driver Motion Sequence Modeling and Forecasting

arXiv:2609.08117v1 Announce Type: new Abstract: Driver motion can provide cues to ongoing behavior, attention, and near-term driving intent. However, most existing driver-centric datasets focus on rec

9 Sept 2026

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Research

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

DGX agent

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

researcharxiv-cs-cv

9 Sept 2026

Local Ai

Model-Adaptive and Risk-Constrained Frequency Hopping Against Predictive Jammers

arXiv:2609.06514v1 Announce Type: new Abstract: Adaptive frequency hopping against predictive jamming must address both model uncertainty and policy exposure: the context-loss relationship may vary ac

local-aiarxiv-cs-lg

9 Sept 2026

Towards Vision-Language Geo-Foundation Model: A Survey

arXiv:2406.09385v3 Announce Type: replace Abstract: Vision-Language Foundation Models (VLFMs) have made remarkable progress on various multimodal tasks, such as image captioning, image-text retrieval,

9 Sept 2026

Does the Selected Object Reach the Reader? Auditing Identity Handoffs in Grounded Language-Model Pipelines

arXiv:2609.04579v1 Announce Type: new Abstract: Grounded language-model pipelines can be divided into three stages: selecting an object, retrieving passages for it, and using that evidence to answer.

Hardware

GEPARD - Generative, Prosody-aware, Autoregressive text-to-speech model for Realtime Dialogue

arXiv:2609.04222v1 Announce Type: cross Abstract: We present GEPARD (Generative, Prosody-aware, Autoregressive text-to-speech model for Realtime Dialogue), a streaming text-to-speech model for real-ti

hardwarearxiv-cs-cl

MultihopSpatial: Multi-hop Compositional Spatial Reasoning Benchmark for Vision-Language Model

arXiv:2603.18892v2 Announce Type: replace-cross Abstract: Spatial reasoning is foundational for Vision-Language Models (VLMs), particularly when deployed as Vision-Language-Action (VLA) agents in phys

MZ-Rain: Moisture-Budget-Guided Zero-Inflated Model for Station-Level Precipitation Nowcasting

arXiv:2609.04864v1 Announce Type: new Abstract: Accurate station-level precipitation nowcasting is critical for agriculture, water resource management, and disaster prevention, which typically is form

Tutorials

TSMini: A Simple Yet Highly Effective Trajectory Similarity Learning Model

arXiv:2502.00285v3 Announce Type: replace-cross Abstract: Trajectory similarity is fundamental to many spatio-temporal data mining applications. Recent studies propose deep learning models to approxim

tutorialsarxiv-cs-cv

Applications

PrivateHub: Contrastive Diffusion Model for Private Sensor-Intensive Environment Data Generation

arXiv:2609.02958v1 Announce Type: cross Abstract: Sensor-intensive environments enable many intelligent services by inferring user applications from heterogeneous data streams. However, not all applic

applicationsarxiv-cs-ai

4 Sept 2026

VisCAD: A Foundation Model Suite with Multimodal Industrial CAD Intelligence

arXiv:2609.03811v1 Announce Type: cross Abstract: AI-assisted computer-aided design (CAD) for industrial products involves two challenging phases. Part-level generation maps diverse forms of user inte

4 Sept 2026

FUSE: An Evaluating Framework for Dangerous Capabilities of LLMs

arXiv:2609.02168v1 Announce Type: new Abstract: Fragmented safety evaluation undermines the governance of dangerous AI capabilities. We present a modular framework that evaluates each model through th

3 Sept 2026

Interpretable Symptom Vectors for Depression in a Large Language Model

arXiv:2609.01832v1 Announce Type: cross Abstract: Patients with depression present with diverse symptom profiles, yet clinical practice routinely reduces this variation to a single severity score. Lar

3 Sept 2026

Local Ai

MeanField Surrogate Modeling for Scalable Runtime Scheduling of Concurrent Heterogeneous AI Inference on Shared GPUs

arXiv:2609.02109v1 Announce Type: cross Abstract: Deploying heterogeneous AI models concurrently on a shared GPU introduces resource contention that complicates runtime scheduling. While surrogate mod

local-aiarxiv-cs-ai

3 Sept 2026

Hardware

A Composable Evaluation System for Reproducible Omni-Modal Foundation Model Evaluation

arXiv:2609.01315v1 Announce Type: new Abstract: Building an omni-modal foundation model means evaluating it across text, image, video, and audio. Excellent evaluation toolkits exist for each modality,

hardwarearxiv-cs-ai

Measuring consistency via ensemble margin and local prediction variability: Auditing decision systems in the presence of predictive multiplicity

arXiv:2609.01397v1 Announce Type: cross Abstract: The Rashomon effect is a machine learning phenomenon where equally accurate models produce different predictions for the same inputs (predictive multi

Local Ai

Risk-Aware Decision-Making for Autonomous Overtaking: A World Model-Based Mixture-of-Experts Framework

arXiv:2609.00385v1 Announce Type: cross Abstract: Autonomous highway overtaking demands foresighted decision-making to handle complex interactions, stochastic traffic evolution, and temporal risk accu

local-aiarxiv-cs-ai

SARTM: Segment Any RGB Thermal Model with Language aided Distillation

arXiv:2505.01950v2 Announce Type: replace-cross Abstract: The recent Segment Anything Model (SAM) demonstrates strong instance segmentation performance across various downstream tasks. However, SAM is

Training-Free Inpainting Across Domains with a Frozen Text-to-Image Diffusion Model

arXiv:2609.00862v1 Announce Type: new Abstract: We show that a frozen generic text-to-image diffusion model can perform conditional inpainting across three evaluated natural-image domains with one fix

Tutorials

FoundDiff: Foundational Diffusion Model for Generalizable Low-Dose CT Denoising

arXiv:2508.17299v2 Announce Type: replace Abstract: Low-dose computed tomography (CT) denoising is crucial for reduced radiation exposure while ensuring diagnostically acceptable image quality. Despit

tutorialsarxiv-cs-cv

Hyper-Fold: Exploring the Expressive Limit of Sequence-Geometry Learning for Proteins via Hypergraph Modeling

arXiv:2608.29207v1 Announce Type: new Abstract: Protein structure modeling rests on a single computational primitive: the interaction between what a residue is (sequence content) and where it sits (th

Label Semantic Expansion via Label Guided Neural Topic Modeling

arXiv:2608.30216v1 Announce Type: cross Abstract: Topic models are widely used for content analysis, where users often analyze corpora around predefined labels rather than unordered latent topics. Exi

safetyarxiv-cs-ai

Off-Manifold Refinement: Guiding Video Generators with a Frozen World Model

arXiv:2608.29904v1 Announce Type: new Abstract: Modern video generators routinely fail at physical dynamics: objects float, trajectories violate gravity, contacts vanish. Standard denoising and flow-m

sRGB Real Noise Modeling via Noise-Aware Sampling with Normalizing Flows

arXiv:2608.29038v1 Announce Type: new Abstract: Noise poses a widespread challenge in signal processing, particularly when it comes to denoising images. Although convolutional neural networks (CNNs) h

Unleashing the Potential of Mamba: Boosting a LiDAR 3D Sparse Detector by Using Cross-Model Knowledge Distillation

arXiv:2409.11018v3 Announce Type: replace Abstract: The LiDAR 3D object detector that balances accuracy and speed is crucial for achieving real-time perception in autonomous driving. However, many exi

safetyarxiv-cs-cv

VeriCam: A Verification Baseline for the Classification of Unknown Data

arXiv:2608.31107v1 Announce Type: new Abstract: The advent of foundation models have enabled a new era in zero-shot classification. Yet, key challenges persist. Despite their impressive generalization

Ada-TokenCom: Rate-Adaptive Token Communications via Large-Model-Driven Token Compression and Generation

arXiv:2608.28086v1 Announce Type: cross Abstract: Token Communications (TokenCom) has recently emerged as a new paradigm in which tokens serve as unified units for communication and computation, enabl

AIM: Anchor Identity Features, Then Match for Multimodal Large Language Model Unlearning

arXiv:2608.28312v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) can memorize identity-specific facts about people in their fine-tuning data, creating privacy risks when a pe

First Make It Playable, Then Make It Good: Staged Interaction Learning for Small Dialogue-Game Agents

model-releasesarxiv-cs-cl

arXiv:2608.27672v1 Announce Type: new Abstract: We present Qwen-GuidePlay-2B, a 2B-parameter language model for dialogue-game interaction. We fine-tune Qwen3.5-2B using three steps: a) SFT on only suc

Prompts Without Evidence: How Neuroimaging Mentions Shift Clinical Vision-Language Model Predictions

arXiv:2603.28387v3 Announce Type: replace-cross Abstract: Trustworthy clinical AI must use real evidence and avoid relying on surface-level artifacts. We evaluate 12 open-weight vision-language models

safetyarxiv-cs-lg

Dependency-Aware Revocable Decoding for Efficient Diffusion Large Language Model Inference

arXiv:2608.26574v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) offer a promising alternative to autoregressive generation by decoding multiple tokens in parallel through itera

28 Aug 2026

4DStreamCtrl: Interactive Video Generation with Online 4D Control

arXiv:2608.25479v1 Announce Type: new Abstract: Generative video models now synthesize footage nearly indistinguishable from reality. Their promise as interactive tools hinges on fine-grained control

27 Aug 2026

A Statistical Audit of Physical AI Benchmark Redundancy

model-releasesarxiv-cs-ro

arXiv:2608.25940v1 Announce Type: new Abstract: Physical AI models are evaluated on suites of benchmarks that differ across model reports, leaving the model-by-benchmark matrix sparse and the relation

27 Aug 2026

Apples to Apples? Towards Comparable Crosslingual Language Model Evaluation

arXiv:2608.25089v1 Announce Type: new Abstract: Crosslingual evaluation of language models that enables fair comparisons remains a fundamental challenge in multilingual NLP. Existing studies adopt a v

27 Aug 2026

CytoNet: A Foundation Model for the Human Cerebral Cortex at Cellular Resolution

arXiv:2511.01870v3 Announce Type: replace-cross Abstract: Studying the cellular architecture of the human cerebral cortex is essential for understanding how the brain is organized from the micro to th

Is the Hard-Label Cryptanalytic Model Extraction Really Polynomial?

arXiv:2510.06692v3 Announce Type: replace Abstract: Deep Neural Networks (DNNs) have attracted significant attention, and their internal models are now considered valuable intellectual assets. Extract

researcharxiv-cs-lg

Metadata-Aware Adaptation of a Generative Foundation Model for Conditional CMR Synthesis

arXiv:2608.24342v1 Announce Type: cross Abstract: Synthetic image generation is a promising strategy to address data scarcity and the underrepresentation of clinically important phenotypes in medical

safetyarxiv-cs-ai

SonarLLM: A Native Sonar--Optical Multimodal Large Language Model for Underwater Perception

arXiv:2608.24325v1 Announce Type: new Abstract: Reliable underwater perception requires complementary sensing under variable visibility. Optical cameras capture appearance and semantics but degrade ra

Symbolic Classification-Enabled LHC Limits Online BSM Global Fits

model-releasesarxiv-cs-lg

arXiv:2605.22330v1 Announce Type: cross Abstract: Global fits of Beyond the Standard Model (BSM) physics often involve a two-way interplay between theory and experiment. Theoretical models provide gui

ADMIL: Attention-Distilled Multiple Instance Learning for Selective Foundation Model Inference in Pathology

arXiv:2608.22066v1 Announce Type: cross Abstract: Attention-based multiple instance learning (ABMIL) using pathology foundation model embeddings is effective for slide-level tasks, but exhaustive infe

AI Surrogate Modeling for Real-Time Tokamak Equilibrium Prediction: Benchmarking Neural Architectures and Validation on EXL-50U

arXiv:2608.23217v1 Announce Type: cross Abstract: Fast and reliable plasma equilibrium prediction is essential for real-time tokamak operation and control, but conventional Grad-Shafranov (GS) solvers

Agents

ATHENA: Knowledge-guided agentic neural architecture search for AutoFormer-based electronic health record modeling

arXiv:2608.21712v1 Announce Type: new Abstract: Transformer-based models are widely used for clinical prediction from electronic health records (EHRs), yet their architectures still require substantia

agentsarxiv-cs-ai

AudioNoisePrints: Model-free audio watermarking using spatial correlation in flow matching TTS

arXiv:2608.22186v1 Announce Type: cross Abstract: We present AudioNoisePrints, a training-free watermarking pipeline for flow matching and diffusion TTS models, which requires minimal extra computatio

Cascaded Learned Bloom Filter for Optimizing Model-Filter Size Balance and Fast Rejection

model-releasesarxiv-cs-lg

arXiv:2502.03696v2 Announce Type: replace-cross Abstract: Recent studies have demonstrated that learned Bloom filters (LBFs), which combine machine learning with the classical Bloom filter, can achiev

Agents

Correcting a learned physical invariant improves world-model rollouts

arXiv:2608.23526v1 Announce Type: new Abstract: World models can predict video without learning dynamics that they reliably preserve. We test whether a frozen DreamerV3 trained only on pendulum video

agentsarxiv-cs-ai

Dynamic Topic Modeling for Cross-Corpus Temporal Analysis

arXiv:2608.23284v1 Announce Type: new Abstract: Dynamic Embedded Topic Models (D-ETM) provide an interpretable framework for modeling temporal semantic evolution, but cross-corpus comparison remains d

safetyarxiv-cs-cl

Interpretable AI with Local Distillation

model-releasesarxiv-cs-lg

arXiv:2608.23538v1 Announce Type: cross Abstract: Modern AI models such as tabular foundation models and gradient-boosted ensembles can outpredict classical methods, but provide little basis for reaso

Applications

Towards Bitstream-corrupted Harsh Visual Understanding: Through Bitstream Language Modeling as Robust Semantic Priors

arXiv:2608.21837v1 Announce Type: new Abstract: Bitstream-corrupted Harsh Visual Understanding (BcHVU) aims to understand harshly degraded videos originally decoded from a severely corrupted bitstream

applicationsarxiv-cs-cv