Search: “models”

arXiv:2508.20705v3 Announce Type: replace Abstract: Recent advances in self-supervised learning for EEG representation have largely relied on masked reconstruction, where models are trained to recover

local-aiarxiv-cs-lg

17 Apr 2026

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SeedPrints: Fingerprints Can Even Tell Which Seed Your Large Language Model Was Trained From

DGX agent

arXiv:2509.26404v2 Announce Type: replace-cross Abstract: Fingerprinting Large Language Models (LLMs)is essential for provenance verification and model attribution. Existing fingerprinting methods are

model-releasesarxiv-cs-ai

15 Apr 2026

BadSkill: Backdoor Attacks on Agent Skills via Model-in-Skill Poisoning

arXiv:2604.09378v1 Announce Type: cross Abstract: Agent ecosystems increasingly rely on installable skills to extend functionality, and some skills bundle learned model artifacts as part of their exec

13 Apr 2026

Adaptive Duration Model for Text Speech Alignment

arXiv:2507.22612v3 Announce Type: replace-cross Abstract: Speech-to-text alignment is a critical component of neural text to speech (TTS) models. Autoregressive TTS models typically use an attention m

safetyarxiv-cs-ai

GeoState: Learning View-Decoupled Geometry States for 3D World Modeling

arXiv:2610.22343v1 Announce Type: cross Abstract: Recent 3D world models increasingly use features from geometry foundation models (GFMs) as predictive world states, benefiting from their rich geometr

safetyarxiv-cs-ai

Research

The Blume-Capel Model as a phi^6 Field Theory: A Monte Carlo and Flow Model Study

arXiv:2610.20982v1 Announce Type: cross Abstract: We report Monte Carlo simulations of a continuous spin variant of the Blume-Capel model. We compute the phase diagrams in the crystal-field-temperatur

researcharxiv-cs-lg

Witness Overlap: Directional Provenance Inside Open-Weight Model Families

arXiv:2609.31784v2 Announce Type: replace Abstract: Open-weight models are often released, fine-tuned, aligned, merged, and re-released, making provenance audits ask not only whether checkpoints are r

Delegating Earth science model calibration to knowledge-guided LLM agents

arXiv:2610.18378v1 Announce Type: new Abstract: Applying process-based Earth science models to new sites and questions often requires expert calibration decisions. Reliable delegation to language-mode

FedGraph: Defending Federated Large Language Model Fine-Tuning Against Backdoor Attacks via Graph-Based Aggregation

arXiv:2610.18430v1 Announce Type: cross Abstract: Federated fine-tuning of large language models (LLMs) allows multiple clients to collaboratively adapt models without sharing raw data, offering stron

FlowWise: Stateful Fast-Slow Model Serving for Streaming Traffic Intelligence

arXiv:2402.03694v3 Announce Type: replace-cross Abstract: Network traffic analysis in cloud and internet service provider (ISP) networks increasingly relies on machine learning (ML) models, as encrypt

What the Model Cannot See: Covert and Provable Text Invisibility in LLMs

arXiv:2610.15883v1 Announce Type: cross Abstract: Text wrapped in a trigger can be made behaviorally invisible to a language model: omitted from summaries and quotations, ignored in question answering

Applications

1Step-WAM: Your World Action Model but Faster using 1-Step Action Generation

arXiv:2610.15625v1 Announce Type: new Abstract: World Action Models (WAMs) unify visual world modeling and action generation, yet their real-world deployment is heavily bottlenecked by iterative actio

applicationsarxiv-cs-cv

Bridging Risk Approximation Gaps in Model Predictive Task Sampling via In-Context Modeling

arXiv:2610.14913v1 Announce Type: cross Abstract: Reinforcement learning (RL) is essential for adaptive decision-making, e.g., robust Meta-RL and domain randomization (DR), and efficient post-training

safetyarxiv-cs-lg

CrossMean: Model Merging by Pairing Merged and Expert Activations

arXiv:2610.14762v1 Announce Type: new Abstract: Model merging combines fine-tuned experts into one network without retraining, and closed-form methods compute each merged layer from statistics of its

Esports World Model Dataset

arXiv:2610.16166v1 Announce Type: new Abstract: Interactive world models must capture how multiple participants jointly change a shared environment while observing different parts of it. Competitive g

safetyarxiv-cs-cv

PGSB: Pretrained-Guided Shared Basis for LoRA Model Merging

arXiv:2610.14558v1 Announce Type: new Abstract: Large pretrained models have achieved remarkable success across diverse domains, yet adapting them to multiple downstream tasks remains challenging: ful

MobileWorldBench: Towards Semantic World Modeling For Mobile Agents

arXiv:2512.14014v2 Announce Type: replace Abstract: World models have shown great utility in improving the task performance of embodied agents. While prior work largely focuses on pixel-space world mo

9 Oct 2026

A Positive Case for Faithfulness: LLM Self-Explanations Help Predict Model Behavior

arXiv:2602.02639v2 Announce Type: replace-cross Abstract: LLM self-explanations are often presented as a promising tool for AI oversight, yet their faithfulness to the model's true reasoning process i

8 Oct 2026

Beyond the Sycophancy Score: How Task, Model, and Pressure Shape LLM Yielding

arXiv:2610.08840v1 Announce Type: new Abstract: Large language models (LLMs) often abandon a correct answer, or endorse a user's position, once the user pushes back. This behavior, called sycophancy,

safetyarxiv-cs-cl

8 Oct 2026

3D-DefectBench: A Controlled Factorial Study of Vision-Language Model Evaluation Pipelines for Fine-Grained 3D Generation Defects

arXiv:2607.10826v2 Announce Type: replace-cross Abstract: Automated evaluation is essential for scaling generative 3D systems, where exhaustive human review is costly and slow. Yet the reliability of

An Information-Theoretic Evaluation Framework for Benchmark and Model Diagnosis in Knowledge Tracing

arXiv:2610.06988v1 Announce Type: new Abstract: Knowledge tracing (KT) models are predominantly evaluated using aggregate metrics such as area under the curve (AUC) and accuracy. However, these global

Dynamics Modeling of a Multi-UAV Slung Load System Using a Discrete-Link Cable Approach

model-releasesarxiv-cs-ro

arXiv:2610.07456v1 Announce Type: new Abstract: A common assumption to simplify the problem of controlling a multi-UAV slung load system (MUSLS) is that the flexible cables can be modeled as massless

Even Small Reasoners Should Quote Their Sources: Introducing the Pleias-RAG Model Family

arXiv:2504.18225v2 Announce Type: replace Abstract: We introduce a new generation of small reasoning models for RAG, search, and source summarization. Pleias-RAG-350m and Pleias-RAG-1B are mid-trained

DreamFormer: Dream Imitation with a Transformer World Model for Language-Conditioned Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2610.04540v1 Announce Type: new Abstract: We introduce DreamFormer, a model-based agent that acquires language-conditioned, multi-task skills by imitating expert demonstrations within the latent

6 Oct 2026

MatrixFormer: A Foundation Model for Matrix Completion

arXiv:2610.06751v1 Announce Type: new Abstract: Matrix completion underlies problems from tabular imputation to causal inference, yet existing tabular foundation models treat it as entry-by-entry pred

6 Oct 2026

Adaptive Spectral-Koopman Dynamics Modeling for Temporal Domain Generalization

arXiv:2610.02822v1 Announce Type: cross Abstract: Temporal Domain Generalization (TDG) has emerged to address real-world streaming data with distribution shifts over time. However, existing methods ar

5 Oct 2026

Understanding Trajectory Heterogeneity in Federated World Model Learning

arXiv:2610.02957v1 Announce Type: cross Abstract: World models learn state evolution from trajectories, making access to temporal context a central training requirement. Federated learning can use dis

5 Oct 2026

WebFovea: When the Model Is Right but the Click Is Wrong -- Reliable Round Trips for Vision-Based Web Agents on Live Websites

arXiv:2610.03036v1 Announce Type: cross Abstract: We present WebFovea, a vision-based web agent that placed 2nd in the WebRetriever Challenge 2026 with a final score of 57.0 out of 100. The challenge

5 Oct 2026

Modeling The Object Representations Underlying Human Physical Reasoning

arXiv:2602.12486v2 Announce Type: replace-cross Abstract: Humans appear to represent objects when reasoning about physics with coarse, volumetric 'bodies' that smooth concavities, trading fine visual

safetyarxiv-cs-ai

2 Oct 2026

Permutation-Robust Decision Modeling with Candidate-Independent Block-Causal Attention

arXiv:2610.01601v1 Announce Type: cross Abstract: Decision models often score a variable-sized set of candidate actions encoded in a single sequence. This setting is increasingly relevant for System 1

2 Oct 2026

Exploring Heterogeneous Model Merging Approach for Complex Knowledge Transfer

arXiv:2609.39369v1 Announce Type: new Abstract: Specialized models encode task-oriented behavior, but transferring that behavior to a general language model usually requires training, distillation, or

Hardware

Gestalt: a meta-foundation model for astronomy

arXiv:2609.38312v1 Announce Type: cross Abstract: The Platonic Representation Hypothesis predicts that sufficiently scaled foundation models converge on a shared representation of the world. As each n

hardwarearxiv-cs-lg

Index-Translate: A Multilingual Translation Model Family -- Text, Speech, Controlled Dubbing, and Long-Document Translation

arXiv:2609.40181v1 Announce Type: new Abstract: We introduce Index-Translate, a multilingual translation model family that combines a shared multilingual foundation with specialized training for gener

UniEvo-VL: An On-policy Self-Distillation Training Recipe for Multimodal Model Self-improvement

arXiv:2609.38721v1 Announce Type: new Abstract: Modern multimodal models bring generation and understanding into a single unified system, which enables them to provide and learn from their own feedbac

Local Ai

HARISSA: Inference-Time Self-Checks for Efficient and Safe Local Language Model Deployment

arXiv:2609.38006v1 Announce Type: new Abstract: Running a language model locally offers advantages in privacy, latency, and cost, but local hardware fits only small models, which are less capable than

local-aiarxiv-cs-ai

LEMON-ZEST: Evolution-Informed Tokenization for Efficient Protein Language Modeling

arXiv:2609.37675v1 Announce Type: new Abstract: Protein Language Models (PLMs) have made remarkable progress following scaling laws established in natural language processing across sequence- and stru

PHASE: Multi-Regime Modeling of Incompressible Magnetohydrodynamics

arXiv:2609.37609v1 Announce Type: new Abstract: Magnetohydrodynamics (MHD) is central to plasma modeling in astrophysics, space science, fusion, and engineering, but resolving multiscale MHD dynamics

Spotter: Let the Embodied Model Lead, and the VLM Reflect for It

arXiv:2609.36808v1 Announce Type: cross Abstract: Current embodied models do not respond to their own failures, although what just went wrong could inform a small adjustment on the next attempt, the k

TabFM: A Zero-Shot Foundation Model for Tabular Data

arXiv:2609.37959v1 Announce Type: new Abstract: Tabular machine learning typically relies on per-dataset workflows, fitting tree ensembles or running AutoML searches from scratch for every task. We pr

Humanoid Loco-Manipulation With Discrete VLA Model

model-releasesarxiv-cs-ro

arXiv:2609.35709v1 Announce Type: new Abstract: Vision-language-action (VLA) models using discrete action tokens have proven effective for controling robotic arms on manipulation tasks. For a humanoid

Tutorials

Improving Generative Model Self-Training with Geometrically Modified Outputs

arXiv:2609.35512v1 Announce Type: new Abstract: Self-training generative models - the continued improvement of a model using its own outputs - is becoming increasingly important as high-quality traini

tutorialsarxiv-cs-lg

Research

The Judge Is Not Its Twin: Post-training makes a model's writing more predictable but barely moves its taste, as a judge, toward predictable writing

arXiv:2609.32196v1 Announce Type: cross Abstract: Language models are now routinely graded by other language models. If post-training makes a model's own writing more predictable, it may also teach th

researcharxiv-cs-lg

ViBR-WM: Visual Bayesian Regression for World Modeling

model-releasesarxiv-cs-cv

arXiv:2609.33844v1 Announce Type: cross Abstract: Modeling temporal dependence and uncertainty is central to forecasting with world models. The Visual Bayesian Regression World Model combines visual f

Research

World SLAM Model: Joint World Modeling for SLAM and Navigation

arXiv:2609.32626v1 Announce Type: cross Abstract: We introduce World SLAM Model (WSM), a unified framework that brings the SLAM paradigm directly into downstream navigation. Rather than treating SLAM

researcharxiv-cs-cv

User Model Extraction via Belief Self-Distillation

arXiv:2609.31603v1 Announce Type: cross Abstract: Large language models (LLMs) implicitly infer attributes of their users and adapt their behavior accordingly, yet these beliefs remain difficult to in

safetyarxiv-cs-cl

28 Sept 2026

WALT: Learning World-Model-Aligned Latent Trajectories for Autonomous Driving

arXiv:2609.30436v1 Announce Type: cross Abstract: Driving world models learn rich predictive representations of the surrounding environment from visual observations, yet accurate visual prediction doe

safetyarxiv-cs-cv

28 Sept 2026

Advancing Model Research in AgentX: Long-Horizon Autonomy for Industrial Recommender Systems

arXiv:2609.30001v1 Announce Type: new Abstract: Sustaining industrial recommendation research requires using the results of one experiment to decide what to investigate next. We present AgentX-Model,

25 Sept 2026

Modality-Gated Deep Adapters: Adding a Modality to a Frozen Embedding Model with Exact Preservation

arXiv:2609.26182v1 Announce Type: new Abstract: Multimodal embedding models are deployed at scale: retrieval indices, benchmark results, and behavioral audits all depend on the base model's exact outp