Search: “models”

Hierarchical SVG Tokenization: Learning Compact Visual Programs for Scalable Vector Graphics Modeling

arXiv:2604.05072v2 Announce Type: replace Abstract: Recent large language models have shifted SVG generation from differentiable rendering optimization to autoregressive program synthesis. However, ex

13 Apr 2026

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Research

Multi-task Just Recognizable Difference for Video Coding for Machines: Database, Model, and Coding Application

DGX agent

arXiv:2604.09421v1 Announce Type: cross Abstract: Just Recognizable Difference (JRD) boosts coding efficiency for machine vision through visibility threshold modeling, but is currently limited to a si

researcharxiv-cs-cv

13 Apr 2026

The AI Codebase Maturity Model: From Assisted Coding to Self-Sustaining Systems

arXiv:2604.09388v1 Announce Type: cross Abstract: AI coding tools are widely adopted, but most teams plateau at prompt-and-review without a framework for systematic progression. This paper presents th

13 Apr 2026

DiffVC: A Non-autoregressive Framework Based on Diffusion Model for Video Captioning

arXiv:2604.08084v1 Announce Type: new Abstract: Current video captioning methods usually use an encoder-decoder structure to generate text autoregressively. However, autoregressive methods have inhere

researcharxiv-cs-cv

Large Language Model Post-Training: A Unified View of Off-Policy and On-Policy Learning

arXiv:2604.07941v1 Announce Type: new Abstract: Post-training has become central to turning pretrained large language models (LLMs) into aligned and deployable systems. Recent progress spans supervise

safetyarxiv-cs-cl

LPM 1.0: Video-based Character Performance Model

arXiv:2604.07823v1 Announce Type: new Abstract: Performance, the externalization of intent, emotion, and personality through visual, vocal, and temporal behavior, is what makes a character alive. Lear

Non-identifiability of Explanations from Model Behavior in Deep Networks of Image Authenticity Judgments

arXiv:2604.07254v1 Announce Type: cross Abstract: Deep neural networks can predict human judgments, but this does not imply that they rely on human-like information or reveal the cues underlying those

Operator Learning for Surrogate Modeling of Wave-Induced Forces from Sea Surface Waves

arXiv:2604.06433v1 Announce Type: cross Abstract: Wave setup plays a significant role in transferring wave-induced energy to currents and causing an increase in water elevation. This excess momentum f

Applications

Phantom: Physics-Infused Video Generation via Joint Modeling of Visual and Latent Physical Dynamics

arXiv:2604.08503v1 Announce Type: new Abstract: Recent advances in generative video modeling, driven by large-scale datasets and powerful architectures, have yielded remarkable visual realism. However

applicationsarxiv-cs-cv

Robust support vector model based on bounded asymmetric elastic net loss for binary classification

arXiv:2603.06257v2 Announce Type: replace-cross Abstract: In this paper, we propose a novel bounded asymmetric elastic net (L_{baen}) loss function and combine it with the support vector machine (SV

A Multi-Tiered AI Accessibility Model (MAIAM): Proportionate Access and Capability Limits for Comprehensive Frontier AI Safety

arXiv:2610.20921v1 Announce Type: new Abstract: Most debate about releasing capable AI systems treats the choice as binary: keep the model behind an API, or publish the weights. That framing runs toge

safetyarxiv-cs-ai

Can LLMs Anticipate Their Cruxes?

arXiv:2610.21006v1 Announce Type: new Abstract: To use language models to help us make decisions we would like to understand the rationale behind the language model's outputs. In principle, the langua

researcharxiv-cs-cl

In-Context Learning Before Specialisation: Theory of Learning in a Solvable Topic Model

arXiv:2610.21901v1 Announce Type: cross Abstract: Sequence models can generalise in fundamentally distinct ways: extrapolating structures seen in training, or using their prompt to adapt to novel task

researcharxiv-cs-ai

Hardware

Intern Lumina U2: A Multi-Codebook Diffusion Large Language Model for Omni-Visual Understanding and Image Generation

arXiv:2610.20818v1 Announce Type: new Abstract: Unified multimodal generation covers discrete, continuous, and hybrid paradigms. Discrete approaches with single-codebook visual tokenizers align natura

hardwarearxiv-cs-cv

LLMR: Knowledge Distillation with a Large Language Model-Induced Reward

arXiv:2409.12500v2 Announce Type: replace-cross Abstract: Large language models have become increasingly popular and demonstrated remarkable performance in various natural language processing (NLP) ta

researcharxiv-cs-ai

Physics-Aware Distillation of a Grid Foundation Model for Real-Time Edge Inference

arXiv:2610.21833v1 Announce Type: new Abstract: Grid foundation models (GridFMs) are graph transformers pretrained on a masked power-flow objective, and evaluate power flow orders of magnitude faster

System1-Arena: Which Decisions Can Be Left to System 1?

arXiv:2610.21244v1 Announce Type: cross Abstract: Large language models (LLMs) often make discrete decisions, such as flagging phishing or escalating to a human. System-1 models, such as Jev and the O

Agents

ABot-ER: Unified Embodied Reasoning through Agentic Data-Model Co-Evolution

arXiv:2610.18355v2 Announce Type: new Abstract: We introduce ABot Embodied Reasoning (ABot-ER), a unified embodied reasoning foundation model that breaks the tension between breadth and depth in embod

agentsarxiv-cs-ai

AgentStripes: An Evidence-Graded Maturity Model for AI Agents

arXiv:2610.18603v1 Announce Type: new Abstract: Benchmarks report what an Artificial Intelligence (AI) agent can do on a task suite, but not whether one released version has been engineered with the c

Kandinsky S2V 1.0: Audio-Driven Avatar Video Generation

arXiv:2610.19290v1 Announce Type: new Abstract: We present Kandinsky S2V 1.0, an open family of speech-to-video models for controllable audio-driven human animation, comprising Kandinsky S2V 1.0 Lite

Model vs. User: Whose Values Prevail? Inference-Time Value Alignment in Multi-Turn Conversations

arXiv:2610.19817v1 Announce Type: new Abstract: Human values shape how we expect language models to behave. Dominant alignment approaches treat values as global objectives, although the appropriate va

safetyarxiv-cs-cl

Quantifying privacy risks in foundation model representations of brain MRI

arXiv:2610.20494v1 Announce Type: new Abstract: Pretrained representations are increasingly used to share and reuse information from medical images without exposing the original scans, but it is uncle

Suggested Is Not Superseded: A Pre-Registered Evaluation of a System-One Model as a Memory-Retirement Gate

arXiv:2610.15710v1 Announce Type: new Abstract: Long-term memory for assistants needs a gate that decides when a new utterance retires an old stored claim. Benchmark labels for this step mark a pair a

Training a Compact, Strong, and Realistic Text-to-Speech Model

arXiv:2610.14776v1 Announce Type: cross Abstract: Text-to-speech (TTS) systems are conventionally optimized for intelligibility and speaker similarity. However, neither objective captures the prosodic

Truthful and Expected-Payment-Optimal Model Routing in Graph-Based Agentic Workflows

model-releasesarxiv-cs-cl

arXiv:2610.19316v1 Announce Type: cross Abstract: Assigning routine tasks to cheaper large language model (LLM) providers can reduce generation cost, but switching providers may require processing acc

Agents

A Gated Catchment Hydrology Model (GCHM) for Physically-Interpretable Rainfall-Evapotranspiration-Runoff Simulation Across Diverse Hydroclimatic Regimes

arXiv:2610.14493v1 Announce Type: new Abstract: Recent advances in machine learning have improved rainfall-runoff prediction, yet most data-driven models remain difficult to interpret and do not expli

agentsarxiv-cs-lg

CacheLink: Functional KV Transport for Zero-Prefill Cross-Model Context Handoff

arXiv:2610.15509v1 Announce Type: new Abstract: KV caches make long-context serving efficient by reusing past computation, but model switching breaks this reuse and forces the receiver to prefill the

Chunk-wise Model-based Policy Optimization

arXiv:2610.14564v1 Announce Type: cross Abstract: Model-based reinforcement learning has shown superior sample efficiency by leveraging the learned latent dynamics either in the form of derivative-fre

safetyarxiv-cs-lg

Applications

ClothCode: Generative Modeling for Garment State Estimation and Dynamics Prediction

arXiv:2610.14200v1 Announce Type: cross Abstract: We introduce ClothCode, a unified generative framework for garment state estimation and action-conditioned dynamics prediction in a shared discrete co

applicationsarxiv-cs-cv

Dog-Breed Text-to-image Flow Matching from Pretraining to Fine-Tuning on 4 Consumer GPUs

arXiv:2610.18870v1 Announce Type: new Abstract: We generally perceive that training text-to-image diffusion models requires heavy compute: it is true if we aim at a comprehensive frontier model. This

FOCUS: A Subspecialty Foundation Model for Intraoperative Central Nervous System Pathology

arXiv:2610.16914v1 Announce Type: new Abstract: Intraoperative frozen-section diagnosis of central nervous system (CNS) lesions guides surgical decisions but is challenged by artefacts, diagnostic com

researcharxiv-cs-cv

From Spectral Saliency to Finite Deletion: Evaluating Selective Language Model Edits

arXiv:2610.18098v1 Announce Type: new Abstract: Deleting singular components offers a precise way to remove a capability from a language model, yet the first-order spectral saliency used to rank compo

InfraWorld: Motion-Aware World Modeling for Roadside 4D Occupancy Forecasting

arXiv:2610.14544v1 Announce Type: new Abstract: Roadside 4D occupancy forecasting predicts future semantic occupancy in a fixed infrastructure coordinate system. Roadside scenes are globally structure

Joint Neural Posterior Estimation and Model Selection for Chemical Reaction Networks

arXiv:2610.18825v1 Announce Type: cross Abstract: Simulation-based Bayesian inference for Chemical Reaction Networks (CRNs) must simultaneously solve two computationally demanding problems: discrimina

Rethinking Human Intent-to-CAD: Parametric CAD Model Generation via Cooperative Multi-Task Alignment and Spatial-Aware Reinforcement Learning

arXiv:2610.15681v1 Announce Type: new Abstract: Parametric Computer-Aided-Design (CAD) modeling from human intent remains challenging, particularly during the conceptual design stage, where design goa

safetyarxiv-cs-cv

Revisiting Error Feedback for Model Quantization

arXiv:2610.18139v1 Announce Type: new Abstract: We study causal error-feedback coefficients as design variables for model quantization. Modeling instantaneous quantization errors as independent, zero-

Visualizing the World Model in an Agent's Value Function

arXiv:2610.14186v1 Announce Type: cross Abstract: Could model-free reinforcement learning algorithms actually be learning a model of the environment? In this work, we apply counterfactual intervention

safetyarxiv-cs-lg

WoVR+: World Model as Reliable Simulator for Versatile VLA Policy Optimization with RL

arXiv:2610.17922v1 Announce Type: new Abstract: Action-conditioned world models can reduce costly real-robot interaction in reinforcement learning for Vision-Language-Action models (VLA-RL), but hallu

safetyarxiv-cs-ro

Retrieval-Augmented Multimodal Language Model with Heterogeneous Evidence Integration for Clinical Prognosis

arXiv:2610.13510v1 Announce Type: new Abstract: Clinical prognosis requires integrating structured measurements, physiological waveforms, longitudinal history, and population context. We introduce PRI

12 Oct 2026

Barron Optimal Transport I: Generative Modeling

arXiv:2610.10875v1 Announce Type: new Abstract: Motivated by recent applications in generative modeling and sampling, we introduce a framework for optimal measure transport where cost captures the not

Conditional Residual Prediction: Improving Autoregressive Video Diffusion without a Bidirectional Teacher

arXiv:2610.11479v1 Announce Type: cross Abstract: Causal video diffusion models generate video autoregressively, which suits streaming, interactive, and long-video generation. Under standard training,

DreamTrue: Action-Faithful Robot World Model with Counterfactual Post-Training

arXiv:2610.12468v1 Announce Type: cross Abstract: We present DreamTrue, a multi-view, cross-embodiment robot world model for action-faithful and physically plausible video prediction. Training such a

safetyarxiv-cs-cv

Learning to Orchestrate Evolutionary Search: Progression-Aware Deep Reinforcement Learning for Dynamic DE-CMA-ES Coordination in Optimization and Structural Model Updating

arXiv:2610.11546v1 Announce Type: cross Abstract: Solving high-dimensional structural model updating problems requires an algorithm capable of navigating complex, non-convex landscapes with correlated

LeWAM: A JEPA World Action Model with Diffusion-Steering-Based MPC

arXiv:2610.12407v1 Announce Type: cross Abstract: World action models (WAMs) predict actions and future observations, typically from a reconstruction-based representation that carries noisy, redundant

safetyarxiv-cs-ai

Local Ai

Not Every Change Is Necessary: Recoverable Drift in Large Language Model Unlearning

arXiv:2610.11915v1 Announce Type: new Abstract: Machine unlearning in large language models aims to remove unwanted knowledge while preserving the model's remaining capabilities. Although existing met

local-aiarxiv-cs-cl

PAM-ToD: Plug-and-Play Appearance Modeling for Cross-Time-of-Day 3D Gaussian Splatting

arXiv:2610.11572v1 Announce Type: new Abstract: Adapting a pre-trained 3D Gaussian Splatting (3DGS) road scene to a new time of day requires learning appearance changes from a few anchor images while

Adversarial Images Hijack Web Agents from Visual Grounding to Browser Execution

model-releasesarxiv-cs-cl

arXiv:2610.09240v1 Announce Type: cross Abstract: Modern web agents built on large vision-language models process webpages, select relevant UI elements, and translate model outputs into browser action

8 Oct 2026

Multi-Objective Aligned Small Language Model Framework for SUD Patient Dialogue Generation