Search: “models”

CoLMbo-SV: A Grounded Language Model for Explainable Speaker Verification

arXiv:2609.33212v2 Announce Type: replace Abstract: Speaker verification systems achieve high accuracy but provide little account of the acoustic evidence behind their judgments. Making these systems

researcharxiv-cs-cl

5 Oct 2026

Applications

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A Hybrid Approach to Malware Detection: Integrating Few-Shot Model-Agnostic Meta-Learning with Autoencoders

DGX agent

arXiv:2610.01949v1 Announce Type: cross Abstract: Ransomware has emerged as a major cybersecurity threat, with incidents increasing in frequency and impact across critical sectors. These attacks are t

applicationsarxiv-cs-ai

2 Oct 2026

Discrete Wasserstein Flows for One-Step Generative Modeling

arXiv:2610.01355v1 Announce Type: cross Abstract: We introduce a new framework for one-step generative modelling on finite state spaces. To extend drifting beyond continuous domains, we use discrete W

2 Oct 2026

Tools

Day 2 at @AIconference with my favorite @FireworksAI_HQ team 🎆 come talk to our team about model inference, training, and more 🙌

Sophia Yang posted that she was attending Day 2 of the AIconference with the FireworksAI_HQ team. She highlighted discussions on model inference and training among other AI topics. The tweet received

toolsfireworks-ai--x

Experimental Experience Modeling for Autonomous Research

arXiv:2609.39392v1 Announce Type: new Abstract: Autonomous research agents can generate hypotheses and conduct experiments, but experimentation remains a major source of computational cost. A fundamen

agentsarxiv-cs-ai

Linear Recurrent Memory Suffices to Distil a World-Model Policy for Robot Air Hockey

arXiv:2609.39151v1 Announce Type: cross Abstract: Does memory-dependent control need nonlinear recurrent dynamics? We study simulated air-hockey defence under temporary loss of puck tracking. A Dreame

The Missing Coefficients: Bayesian Pairwise Merging for Model Personalization

arXiv:2609.39055v1 Announce Type: new Abstract: How can we personalize a shared expert library from a user's pairwise choices? Prior work can realize different reward trade-offs by merging reward-spec

Boundary-State Control for Tool-Using Language-Model Agents: Commit-Time Consistency under State Drift

arXiv:2609.37475v1 Announce Type: new Abstract: Tool-using language-model agents can decide that an action is permissible and execute it only after security-relevant state has changed. We study this p

safetyarxiv-cs-ai

Can a Cacheable Decision Model Follow Rules?

arXiv:2609.37832v1 Announce Type: new Abstract: Certo is a small non-generative decision model (Qwen3-4B): it scores candidate actions from their text and returns a probability, instead of generating

Developing an OCR model for Extracting Information from Invoices with Korean Language

arXiv:2609.35796v1 Announce Type: new Abstract: Invoices are commercial documents that contain various pieces of information, including the purchased items, time, and total money. Making the extractio

researcharxiv-cs-cl

DiffReID: Discriminative Diffusion Model for Object Re-Identification

arXiv:2609.36894v1 Announce Type: new Abstract: As a fundamental image processing task, object Re-Identification (ReID) aims to retrieve objects across non-overlapping cameras. Recently, with the deve

tutorialsarxiv-cs-cv

DSWM: Decomposed Spatio-Temporal World Model for Demand-Driven UAV Base Station Repositioning

arXiv:2609.36845v1 Announce Type: cross Abstract: Uncrewed aerial vehicle base stations (UAV-BSs) are expected to cover traffic demand that shifts across space and time, yet most repositioning schemes

agentsarxiv-cs-ai

GRFBrain: Graph-Structured Rectified Flows for EEG Dynamic Modeling

arXiv:2609.37934v1 Announce Type: new Abstract: Forecasting time-varying functional connectivity from electroencephalography (EEG) requires modeling both history-dependent trends and structured variab

Industry

OpenAI says individuals associated with Moonshot AI played a significant role in a coordinated model-distillation campaign that began in early July (Maggie Eastland/Bloomberg)

Maggie Eastland / Bloomberg: OpenAI says individuals associated with Moonshot AI played a significant role in a coordinated model-distillation campaign that began in early July — OpenAI accused its Ch

industrytechmeme

Stein-based Optimization of Sampling Distributions in Model Predictive Path Integral Control

arXiv:2511.02015v3 Announce Type: replace Abstract: This paper introduces a method for Model Predictive Path Integral (MPPI) control that optimizes sample generation towards an optimal trajectory thro

A Visual Classification Dataset and Model Evaluation for Historical Manuscript Illustrations

arXiv:2609.33449v1 Announce Type: new Abstract: Historical manuscript illustrations preserve rich visual evidence of past cultures. They depict people, animals, plants, diagrams, music notations, and

Adjoint-based shape optimization of a ship hull using a Conditional Variational Autoencoder (CVAE) assisted propulsion surrogate model

arXiv:2602.14907v3 Announce Type: replace-cross Abstract: Adjoint-based shape optimization of ship hulls is a powerful tool for addressing high-dimensional design problems in naval architecture, parti

AeroJEPA: Learning Semantic Latent Representations for Scalable 3D Aerodynamic Field Modeling

arXiv:2605.05586v2 Announce Type: replace Abstract: High-fidelity CFD is essential for aerodynamic design, but repeated simulations are computationally expensive, motivating surrogate models for rapid

DS-VLA: A Dendritic-inspired Vision-Language-Action Model for Robust Action Control

arXiv:2609.32253v1 Announce Type: new Abstract: Vision-language-action (VLA) models have achieved strong performance in language-conditioned manipulation, yet success under nominal evaluation does not

Dynamic Model Identification and Gravity Compensation for the dVRK-Si Patient Side Manipulator

arXiv:2603.12099v2 Announce Type: replace Abstract: The da Vinci Research Kit (dVRK) has been widely used for research in robot-assisted surgery over the past decade, and its latest generation, the dV

Kernel-Based Steering of CLIP with Vision-Language Model Preferences

arXiv:2609.32203v1 Announce Type: new Abstract: Large vision-language models (VLMs) can judge visual similarity, but their judgments are not directly available as compact image embeddings for efficien

tutorialsarxiv-cs-cv

KoopCell: Koopman-Based Generative Model for Learning Single-Cell Dynamics from Distribution Snapshots

arXiv:2609.33350v1 Announce Type: new Abstract: Learning population dynamics from temporally sparse, unpaired distribution snapshots is a fundamental challenge in developmental biology. Recent approac

Model-Free Output Feedback Stabilization via Policy Gradient Methods

arXiv:2601.19284v3 Announce Type: replace-cross Abstract: Stabilizing a dynamical system is a fundamental problem that serves as a cornerstone for many complex tasks in the field of control systems. T

Modeling Whole-Slide Images as Dynamic Tumor Microenvironment Fields

arXiv:2609.34451v1 Announce Type: new Abstract: Due to the gigapixel-scale nature of whole-slide images (WSIs), weakly supervised WSI analysis is commonly formulated as a multiple instance learning (M

Pre-registered tests of solid-state-physics-inspired LLM compression: a cluster-level negative result at small-language-model scale

arXiv:2609.34292v1 Announce Type: cross Abstract: We report a three-month autonomous research-agent program testing five solid-state-physics-inspired compression mappings on pretrained language models

agentsarxiv-cs-lg

Robust and Efficient MuJoCo-based Model Predictive Control via Web of Affine Spaces Derivatives

arXiv:2512.21109v4 Announce Type: replace Abstract: MuJoCo is a powerful and efficient physics simulator widely used in robotics. One common way it is applied in practice is through Model Predictive C

Scalable In-Domain Self-Supervised Foundation Model for Dense Representation Transfer in High-Resolution Plant Imaging

arXiv:2609.32183v1 Announce Type: new Abstract: High-resolution plant imaging enables detailed characterization of plant morphology, but dense scientific analysis remains limited by costly pixel-level

Scanning While Imagining: A Scene-Graph World Model for Robotic Ultrasound Navigation

arXiv:2609.32837v1 Announce Type: new Abstract: Ultrasound (US) acquisition depends on the operator's ability to interpret anatomy and anticipate how the view will change with probe motion. Many robot

Towards Generalizable 3D Anomaly Detection via Relational Inconsistency Modeling

arXiv:2609.35059v1 Announce Type: new Abstract: 3D anomaly detection (3DAD) aims to identify defective regions in point cloud data, serving as a critical component in industrial inspection systems. Ex

What Should a Streaming Video Model Remember?

arXiv:2606.16353v2 Announce Type: replace Abstract: Streaming video understanding models must answer queries at any moment during an ongoing stream, using only what they have observed so far and under

tutorialsarxiv-cs-cv

AUWave: A Data-Driven Model for Reconstructing Significant Wave Heights Using Sparse Observations

arXiv:2509.19384v2 Announce Type: replace-cross Abstract: Reconstructing high-resolution regional significant wave height (SWH) fields from sparse buoy observations is a critical challenge for ocean m

Bridging LLM Agents and Data Spaces: An Architectural Mediation Approach using the Model Context Protocol

arXiv:2609.30341v1 Announce Type: new Abstract: Data Spaces enable sovereign and governed data sharing across organizational boundaries, but their integration with AI agents remains challenging due to

safetyarxiv-cs-ai

MoTop: Motion-Topological Model For Micro AU Detection

arXiv:2609.31285v1 Announce Type: new Abstract: Facial micro-expressions are spontaneous, brief, and subtle facial movements that reveal suppressed emotions in high-stakes environments. In contrast to

Retrainable physics-integrated neural differentiable modeling of sintering across material systems

arXiv:2609.31518v1 Announce Type: cross Abstract: Sintering is widely used to manufacture ceramics, but coupled densification and grain growth, material-dependent kinetics, and sparse measurements com

tutorialsarxiv-cs-lg

Applications

A Computational Framework for Modelling Organisation-Level Semantic Identity from Longitudinal Textual Data

arXiv:2609.29584v1 Announce Type: cross Abstract: Organisations continuously generate large volumes of textual data that capture how they communicate, evolve and differentiate themselves over time. Al

applicationsarxiv-cs-cl

CataOPD: Catalytic On-Policy Distillation for Large Language Model Reasoning

arXiv:2609.29518v1 Announce Type: new Abstract: Reinforcement learning (RL) and on-policy distillation (OPD) are two representative paradigms for improving large language model reasoning. However, whe

Certified Predictive Value-of-Advice Gating for Cost-Aware Language-Model Guidance in Reinforcement Learning

arXiv:2609.29548v1 Announce Type: new Abstract: Language-model advice can accelerate reinforcement learning, but calls are costly and returned actions may be stale or wrong. We formulate advice acquis

Coordinate-Independent Robot Model Identification

arXiv:2603.14656v2 Announce Type: replace Abstract: Robot model identification is commonly performed by least-squares regression on inverse dynamics, but existing formulations measure residuals direct

safetyarxiv-cs-ro

Lightweight Probabilistic Downscaling from a Deterministic Base Model

arXiv:2609.29383v1 Announce Type: new Abstract: Climate data downscaling is the task of increasing the spatial resolution of climate data, typically by generating fine-resolution regional climate data

Frozen Flows Forget: Diagnosing and Restoring Lost Motion in a Latent-flow World Model

arXiv:2609.28414v1 Announce Type: cross Abstract: Latent world models that integrate a flow in a frozen self supervised latent space train stably and cheaply, yet silently lose the property manipulati

Applications

InternW0: A Foundational Physical World Model for Efficient Real-World Interactions

arXiv:2609.27656v1 Announce Type: cross Abstract: Physical intelligence requires more than predicting how the world may evolve: predictions must remain actionable as the world continues to change. We

applicationsarxiv-cs-ai

predicting model uncertainty is a hard problem. perfectly 'calibrated' confidence scores are exact probability values on whether the output …

predicting model uncertainty is a hard problem. perfectly 'calibrated' confidence scores are exact probability values on whether the output is correct. this is extremely important for agentic decision

agentsjerry-liu--x

Retrieval Augmented (Knowledge Graph), and Large Language Model-Driven Design Structure Matrix (DSM) Generation of Cyber-Physical Systems

arXiv:2602.16715v2 Announce Type: replace Abstract: We explore the potential of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Graph-based RAG (GraphRAG) for generating Design

Ascent: An Agentic System over the Model Context Protocol for Real-World Clinical Data Analysis

arXiv:2609.24620v1 Announce Type: new Abstract: Answering epidemiological questions from real-world clinical data requires medical coding, schema-aware SQL, and validation of implicit choices about po

agentsarxiv-cs-ai

Local Ai

High-Order Liquid Evidence Modeling for Continuous and Subtle GNSS Spoofing Detection in Autonomous Driving

arXiv:2609.26231v1 Announce Type: new Abstract: Continuous and subtle GNSS spoofing poses a serious threat to autonomous vehicles because forged positions may remain locally plausible while gradually

local-aiarxiv-cs-lg

Higher-Order Approximation of Exit Functionals in Sampling-Based Stochastic Model Predictive Control

arXiv:2609.25257v1 Announce Type: cross Abstract: Safety evaluation in sampling-based stochastic model predictive control often requires numerical estimation of exit functionals. The approximation of

safetyarxiv-cs-ro

MSA-CITE: A Co-Adapted LoRA Specialist Ecology for Fixed-Budget Small-Model Inference

arXiv:2609.26217v1 Announce Type: new Abstract: Compact language models are typically deployed by retaining a single post-training checkpoint and sampling it repeatedly. In this work, we challenge thi

tutorialsarxiv-cs-lg

Point Diffusion Mamba: Unified Diffusion-State-Space Modeling for Single-View 3D Reconstruction under Data Scarcity

arXiv:2609.25538v1 Announce Type: new Abstract: While single-view 3D reconstruction has seen significant progress, extrapolating complex 3D structures from inherently ambiguous 2D observations remains