Search: “models”

arXiv:2602.11139v2 Announce Type: replace Abstract: Tabular foundation models, such as TabPFNv2 and TabICL, have recently dethroned gradient-boosted trees at the top of predictive benchmarks, demonstr

hardwarearxiv-cs-lg

17 Sept 2026

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Research

Attention Mean Fields Predict Average Representation Dynamics and Reveal Context-Specific Computation

DGX agent

arXiv:2609.16382v1 Announce Type: cross Abstract: A language model's representation geometry is not predetermined; it evolves as the model runs. A faithful account of that geometry must capture that d

researcharxiv-cs-cl

16 Sept 2026

CBW: Towards Dataset Ownership Verification for Speaker Verification via Clustering-based Backdoor Watermarking

arXiv:2503.05794v4 Announce Type: replace-cross Abstract: Speaker verification models are trained on large-scale public datasets whose licenses usually prohibit unauthorized commercial use, yet such i

IRENE: A Convolutional GRU Ensemble Model for Radar Precipitation Nowcasting over Italy

arXiv:2609.17175v1 Announce Type: new Abstract: We present IRENE (Italian Radar Ensemble Nowcasting Experiment), a deep learning model for probabilistic short-range precipitation nowcasting over the I

ReDraft, Don't Just Distill: Reference-Driven Revision for Continual VLLM Post-Training

arXiv:2609.16639v1 Announce Type: new Abstract: Continual post-training of large multimodal models should add new capabilities while preserving those from pre-training, and the two goals pull in oppos

SceneBench: A Hierarchical Benchmark for Vision-Language Understanding of 3D Scenes

arXiv:2609.16233v1 Announce Type: cross Abstract: Vision-language models excel at 2D image understanding but remain limited in 3D spatial reasoning. Progress is hindered by limitations in current benc

Agents

sensVLA: Spatially-Grounded Vision-Language-Action Model for Autonomous Wheel Loader

arXiv:2609.17021v1 Announce Type: new Abstract: Autonomous wheel-loader control requires joint reasoning over task semantics, egocentric vision, proprioception, and 3D scene geometry. We present sensV

agentsarxiv-cs-cv

Style-Debiased DPO: Updating LLM Knowledge with Factuality-Aware Synthetic Preference Data

model-releasesarxiv-cs-cl

arXiv:2609.16532v1 Announce Type: new Abstract: Continued pretraining (CPT) with data augmentation such as paraphrasing can store inside a large language model (LLM) the knowledge of a small source co

Test-Time Unlearning via Sparse Autoencoder

model-releasesarxiv-cs-cl

arXiv:2609.16229v1 Announce Type: cross Abstract: Machine unlearning aims to remove specific knowledge from a trained large language model (LLM) without retraining from scratch. Existing methods modif

XPACE: Joint World and Action Modeling from Heterogeneous Experience

arXiv:2609.17372v1 Announce Type: new Abstract: A general-purpose robot needs to draw on diverse experience, choose actions, and anticipate how those actions will change the world. We introduce XPACE,

safetyarxiv-cs-ro

Tutorials

Certifying Model Upgrades with Slice-Wise Non-Regression and Incumbent Fallback

arXiv:2609.13714v1 Announce Type: new Abstract: An updated model can improve an aggregate metric while degrading a slice that matters to a downstream user. We study checkpoint selection subject to non

tutorialsarxiv-cs-lg

Agents

Confuse the Model, Control the Flow: Understanding and Mitigating Privacy Leakage from LLM Agents with Information Flow Control

arXiv:2609.14003v1 Announce Type: cross Abstract: Personal AI agents built on large language models (LLMs) are increasingly given access to a user's private data and communications in order to provide

agentsarxiv-cs-ai

Evaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks

arXiv:2609.12839v2 Announce Type: replace-cross Abstract: The proliferation of highly capable open-weight Small Language Models (SLMs) democratizes access to advanced cybersecurity capabilities, posin

Local Ai

Frequency-Guided Diffusion Model with Perturbation Training for Skeleton-Based Video Anomaly Detection

arXiv:2412.03044v3 Announce Type: replace Abstract: Video anomaly detection (VAD) is a vital yet complex open-set task in computer vision, commonly tackled through reconstruction-based methods. Howeve

local-aiarxiv-cs-cv

Learned Bow Control on a Measured Bowed-String Model: a Revised Minimum-Bow-Force Law, a Recurrent Controller, and the Domain of a Supervision Ceiling

arXiv:2609.14990v1 Announce Type: cross Abstract: A finite-difference bowed-string model with implicitly resolved Stribeck friction is presented, with a regime diagnostic, the Schelleng bow-force limi

Modeling, Scaling, and Decoding: Optimizing Controllable Speech Generation with Nonverbal Vocalizations

arXiv:2609.14231v1 Announce Type: cross Abstract: Controllable synthesis of nonverbal vocalizations (NVVs) is es- sential for natural and expressive speech, but remains challeng- ing due to their acou

Applications

Natural-Language to SysMLv2 Translation via Conformance-Driven Iterative Refinement

arXiv:2607.14162v1 Announce Type: cross Abstract: Model-Based Systems Engineering (MBSE) relies on formal system models as primary technical artifacts for representing requirements, structure, and beh

applicationsarxiv-cs-ai

Predictive Likelihood Ratios for Language Model Watermark Detection

arXiv:2609.15657v1 Announce Type: cross Abstract: Keyed watermark detection tests dependence between observed tokens and pseudorandom variables reconstructed from a secret key. Building on the pivotal

PU classification under Non-SCAR: clustering-assisted logistic model with oversampling enhancement

arXiv:2609.14675v1 Announce Type: cross Abstract: This study addresses the PU classification problem under violations of the SCAR assumption. We investigate logistic regression-based approaches, namel

What Does an LLM Learn from Reinforcement Learning? A Mechanistic Interpretability Perspective with Fixed-SAE Track

model-releasesarxiv-cs-lg

arXiv:2609.15064v1 Announce Type: new Abstract: Reinforcement learning (RL) is widely utilized in large language model training to improve targeted capabilities, yet how RL reshapes a model remains po

Agentic TCAD Calibration Workflow for Oxide Semiconductor Transistors

model-releasesarxiv-cs-lg

arXiv:2609.12184v1 Announce Type: cross Abstract: Experimental TCAD calibration is essential for predictive technology modeling of emerging oxide semiconductor transistors. However, it remains time-co

14 Sept 2026

Beyond Argmax: A Mechanistic Study of Semantic Retention in Frozen Foundation-Model Composition for Generalized Few-Shot 3D Segmentation

arXiv:2609.12099v1 Announce Type: new Abstract: Classical classifier-combination work distinguishes score-level fusion from hard decision-level voting. We revisit this distinction where independently

researcharxiv-cs-cv

14 Sept 2026

An Experimental Evaluation of Multimodal Prompt Injection Attacks on Agentic AI Frameworks

arXiv:2609.09404v1 Announce Type: cross Abstract: Agentic AI frameworks let a language model plan, keep memory, and call tools that reach real files, mail, and services. Most of these agents also read

11 Sept 2026

DR-LabStack: Design and Implementation of a Clinician-Facing Web System for Diabetic Retinopathy Prediction

arXiv:2609.10796v1 Announce Type: new Abstract: Pretrained diabetic retinopathy (DR) prediction models differ in their input fields, serialization formats, preprocessing requirements, and output seman

11 Sept 2026

Hardware

Understanding LoRA Rank Trade-offs in Diffusion Model Fine-Tuning

arXiv:2609.10656v1 Announce Type: cross Abstract: Selecting LoRA rank for diffusion fine-tuning requires balancing quality and compute cost. We present a controlled study on CIFAR-10 using a DDPM U-Ne

hardwarearxiv-cs-lg

11 Sept 2026

A convolutional autoencoder and neural ODE surrogate modeling framework applied to transient counterflow flames

arXiv:2603.15038v2 Announce Type: replace-cross Abstract: A novel convolutional autoencoder and neural ODE (CAE-NODE) framework is proposed for a reduced-order model (ROM) applied to transient 2D coun

A Unifying Perspective on Probabilities as Model Predictions

arXiv:2609.09855v1 Announce Type: cross Abstract: Although probabilistic statements are ubiquitous, foundational disagreements persist about their understanding, as exemplified by debates between Baye

safetyarxiv-cs-lg

ASDA: Automated Skill Distillation and Adaptation for Financial Reasoning

arXiv:2603.16112v2 Announce Type: replace-cross Abstract: Adapting large language models (LLMs) to specialized financial reasoning typically requires expensive fine-tuning that produces model-locked e

AstroSpecLM: A Spectrum-Language Model for Evidence-Grounded Astronomical Spectral Analysis

arXiv:2609.07102v1 Announce Type: cross Abstract: Astronomical spectra encode rich physical information, but drawing scientific conclusions from spectral features typically requires expert interpretat

Benchmark Scores Are Pipeline-Dependent: A Reliability Audit of Cybersecurity LLM Benchmarks

arXiv:2609.08765v1 Announce Type: cross Abstract: Large language model (LLM) benchmarks are often treated as fixed datasets with stable scores, yet their outcomes depend on configurable evaluation pip

Do Dynamic Routers Need Memory? HeRo: History-Aware Routing for Efficient LLM Inference

arXiv:2609.08189v1 Announce Type: new Abstract: Dynamic layer routing reduces the inference cost of Large Language Models (LLMs) by learning to skip layers for individual tokens. Existing methods, how

Agents

KVShareArena: KV-Cache Reuse Across Contexts and Model Checkpoints

arXiv:2609.10266v1 Announce Type: new Abstract: LLM serving systems already reuse KV caches, but only when the reused text sits at the very start of the prompt. Two growing workloads break this condit

agentsarxiv-cs-cl

ObGynLongBench: Revealing the Evidence-to-EHR Gap in Longitudinal EHR Decision-Making

arXiv:2609.07601v1 Announce Type: cross Abstract: The application of large language models (LLMs) to personalized medical assistants has garnered growing interest. However, existing medical benchmarks

On-Policy Distillation for Vision-Language Model Adaptation, an Effective Paradigm on Low-Quality Multimodal Data

arXiv:2609.10321v1 Announce Type: new Abstract: Knowledge distillation offers an efficient route to transfer a task-adapted vision-language teacher to a compact student. The training target in current

safetyarxiv-cs-cl

Rethinking Sign Language Translation: The Impact of Signer Dependence on Model Evaluation

arXiv:2609.07965v1 Announce Type: cross Abstract: Sign Language Translation has advanced with deep learning, yet evaluations remain largely signer-dependent, with overlapping signers across train/dev/

VFNet: Multi-View Spatio-Temporal Model for Void Fraction Estimation in Gas-Liquid Two-Phase Flow

model-releasesarxiv-cs-cv

arXiv:2609.09711v1 Announce Type: new Abstract: Void fraction, which quantifies the proportion of the fluid flow volume occupied by the gas phase, is a key parameter in the characterization of gas-liq

Local Ai

A Cloud-Based Hybrid Model for Real-Time Detection of BRTA-Approved Licence Plates Using YOLO Tiny and Haar Cascade

arXiv:2609.06507v1 Announce Type: new Abstract: Accurate vehicle license plate detection is essential for applications such as intelligent transportation systems, toll collection, parking management,

local-aiarxiv-cs-cv

Tutorials

A Joint 2D-3D Statistical Shape Model for Orthopedic Reconstruction

arXiv:2609.09010v1 Announce Type: new Abstract: Three-dimensional femoral reconstruction from radiographs supports surgical planning, implant sizing, and post-operative follow-up, but remains ill-pose

tutorialsarxiv-cs-cv

Tutorials

A Specialized Large Multimodal Model for Interpreting PET/CT in Head and Neck Cancer

arXiv:2609.05532v1 Announce Type: new Abstract: Background: Diagnosing head and neck cancer using PET/CT is clinically challenging and time-consuming due to the anatomical complexity of the region, mo

tutorialsarxiv-cs-cv

Bottom-up Modeling of Repeated Elements via Single Image Analysis-by-Synthesis

arXiv:2609.07939v1 Announce Type: new Abstract: We address the problem of discovering repeated elements from a single image. In contrast to existing approaches that depend on large annotated datasets,

safetyarxiv-cs-cv

Characterizing Privacy-Audit Alignment in Behavioral Audit of Machine Unlearning

model-releasesarxiv-cs-lg

arXiv:2606.14518v2 Announce Type: replace Abstract: The removal of learned data from Machine Learning models through Machine Unlearning (MU) has been widely studied; however, there is no agreed-upon s

GradeTrap: Authority Cues in Images Shift VLM Judgments Despite Explicit Instructions to Ignore Them

model-releasesarxiv-cs-cv

arXiv:2609.06058v1 Announce Type: new Abstract: As vision-language models (VLMs) become increasingly capable and are deployed in consequential real-world settings, they must evaluate evidence independ

Applications

HoneyRoute: Honeypot-Model Routing for Adversarial LLM Serving

arXiv:2609.08306v1 Announce Type: cross Abstract: We introduce HoneyRoute, an inference-serving layer that detects whether an incoming request is malicious and, if so, routes it to a dedicated honeypo

applicationsarxiv-cs-lg

Iterative Audio Separation with Mixture Consistency via MIMO Model Extension

arXiv:2609.07226v1 Announce Type: cross Abstract: This paper proposes a general framework for stable and effective iterative audio separation with mixture consistency by extending source separation mo

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

arXiv:2609.09140v1 Announce Type: new Abstract: The digitization of healthcare has generated vast, longitudinal, and multimodal patient records over a lifetime, yet fully exploiting these data to repr

safetyarxiv-cs-lg

NOVA: Normal-Side Modeling for Training-Free Zero-Shot Video Anomaly Detection

arXiv:2609.06360v1 Announce Type: new Abstract: Training-free zero-shot video anomaly detection (ZS-VAD) leverages vision-language models (VLMs) to localize anomaly instances from a predefined anomaly

safetyarxiv-cs-cv

One for All: Generalist Foundation Model for Cross-Sensor Skeleton Representation Learning

arXiv:2609.07078v1 Announce Type: new Abstract: For learning generalizable motion representations from large-scale unlabeled data, Self-supervised learning (SSL) has become a widely adopted methodolog

researcharxiv-cs-cv

Applications

OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining

arXiv:2609.07398v1 Announce Type: new Abstract: World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Ex

applicationsarxiv-cs-ro