Search: “models”

Adaptive double-phase Rudin--Osher--Fatemi denoising model

arXiv:2510.04382v2 Announce Type: replace-cross Abstract: Even though more than 30 years have passed since the seminal Rudin--Osher--Fatemi (ROF) paper on total variation (TV) denoising, it remains re

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AtlasVid: Efficient Ultra-High-Resolution Long Video Generation via Decoupled Global-Local Modeling

DGX agent

arXiv:2605.16649v1 Announce Type: new Abstract: Recent diffusion-based video generators have achieved remarkable visual fidelity and prompt controllability, yet scaling them to ultra-high-resolution (

local-aiarxiv-cs-cv

19 May 2026

Baba in Wonderland: Online Self-Supervised Dynamics Discovery for Executable World Models

arXiv:2605.16725v1 Announce Type: new Abstract: Executable world models can be read, edited, executed, and reused for planning, but only if the program captures the environment's transition law rather

BacktestBench: Benchmarking Large Language Models for Automated Quantitative Strategy Backtesting

arXiv:2605.17937v1 Announce Type: cross Abstract: Quantitative backtesting is essential for evaluating trading strategies but remains hampered by high technical barriers and limited scalability. While

Applications

Buffer-Parameterized Machine Learning Surrogate Models for Cross-Technology Signal Integrity Analysis and Optimization

arXiv:2605.18170v1 Announce Type: cross Abstract: Signal integrity (SI) analysis in printed circuit board (PCB) interconnects faces increasing complexity due to diverse integrated circuit (IC) buffer

applicationsarxiv-cs-lg

CAR-SAM: Cross-Attention Reconstruction for Post-Training Quantization of the Segment Anything Model

arXiv:2605.16901v1 Announce Type: new Abstract: Segment Anything Models (SAMs) are extensively used in computer vision for universal image segmentation, but deploying them on resource-constrained devi

ChemVA: Advancing Large Language Models on Chemical Reaction Diagrams Understanding

arXiv:2605.17214v1 Announce Type: new Abstract: While Large Language Models (LLMs) have revolutionized scientific text processing, they exhibit a significant capability gap when interpreting chemical

safetyarxiv-cs-ai

Concepts Worth Having: Refining VLM-Guided Concept Bottleneck Models with Minimal Annotations

arXiv:2605.16405v1 Announce Type: new Abstract: Concept-bottleneck models (CBMs) are neural classifiers that compute predictions from high-level concepts extracted from the input. CBMs ensure stakehol

CounterCount: A Diagnostic Framework for Counting Bias in Vision Language Models

arXiv:2605.17826v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) excel at multimodal reasoning, yet it remains unclear whether their answers are grounded in visual evidence or driven by

local-aiarxiv-cs-ai

Dual-Rate Diffusion: Accelerating diffusion models with an interleaved heavy-light network

arXiv:2605.18190v1 Announce Type: cross Abstract: Diffusion models achieve state-of-the-art generative performance but suffer from high computational costs during inference due to the repeated evaluat

DyGRO-VLA: Cross-Task Scaling of Vision-Language-Action Models via Dynamic Grouped Residual Optimization

arXiv:2605.17486v1 Announce Type: cross Abstract: Recent progress in Reinforcement Learning (RL) provides a principled approach to optimizing Vision-Language-Action (VLA) models, facilitating a shift

safetyarxiv-cs-lg

Dynamic Generation of Multi-LLM Agents Communication Topologies with Graph Diffusion Models

arXiv:2510.07799v2 Announce Type: replace-cross Abstract: The efficiency of multi-agent systems driven by large language models (LLMs) largely hinges on their communication topology. However, designin

Empirical evaluation of Time Series Foundation Models for Day-ahead and Imbalance Electricity Price Forecasting in Belgium

arXiv:2605.17045v1 Announce Type: cross Abstract: Recent advances in Time Series Foundation Models (TSFMs) promise zero-shot forecasting capabilities with minimal task-specific training. While these m

researcharxiv-cs-lg

Fine-tuning an ECG Foundation Model to Predict Coronary CT Angiography Outcomes

arXiv:2512.05136v3 Announce Type: replace-cross Abstract: CAD remains a major global public health burden, yet scalable screening tools are limited. Although CCTA is a first-line non-invasive diagnost

Generating Physically Consistent Molecules with Energy-Based Models

arXiv:2605.18381v1 Announce Type: new Abstract: Molecules in equilibrium follow a Boltzmann distribution, making the underlying energy landscape a physically grounded modeling objective. However, such

safetyarxiv-cs-lg

How Good LLMs Are at Answering Bangla Medical Visual Questions? Dataset and Benchmarking

model-releasesarxiv-cs-cl

arXiv:2605.18111v1 Announce Type: new Abstract: Recent advancements in Large Language Models (LLMs) and Large Vision Language Models (LVLMs) have enabled general-purpose systems to demonstrate promisi

Learning Lifted Action Models from Traces with Minimal Information About Actions and States

arXiv:2605.18627v1 Announce Type: new Abstract: It has been recently shown that lifted STRIPS models can be learned correctly and efficiently from action traces alone; i.e., applicable action sequence

Long Context Modeling with Ranked Memory-Augmented Retrieval

arXiv:2503.14800v3 Announce Type: replace-cross Abstract: Effective long-term memory management is crucial for language models handling extended contexts. We introduce the Enhanced Ranked Memory Augme

LURE: Latent Space Unblocking for Multi-Concept Reawakening in Diffusion Models

arXiv:2601.14330v2 Announce Type: replace Abstract: Concept erasure aims to suppress sensitive content in diffusion models, but recent studies show that erased concepts can still be reawakened, reveal

MixSD: Mixed Contextual Self-Distillation for Knowledge Injection

model-releasesarxiv-cs-cl

arXiv:2605.16865v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) is widely used to inject new knowledge into language models, but it often degrades pretrained capabilities such as reasonin

Mixture-of-Experts Can Surpass Dense LLMs Under Strictly Equal Resource

arXiv:2506.12119v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) language models dramatically expand model capacity and achieve remarkable performance without increasing per-token co

New Wide-Net-Casting Jailbreak Attacks Risk Large Models

arXiv:2605.17128v1 Announce Type: cross Abstract: Jailbreak attacks on large models have drawn growing attention due to their close ties to societal safety. This work identifies a practical yet unexpl

safetyarxiv-cs-ai

No Plan, Yet Human: A Reactive Robotics Model Predicts Human Planning Failures on a Clinical Task

arXiv:2605.16514v1 Announce Type: cross Abstract: Understanding why some sequential planning problems are harder than others requires models that go beyond average performance. They should capture the

OCCAM: Open-set Causal Concept explAnation and Ontology induction for black-box vision Models

arXiv:2605.18481v1 Announce Type: new Abstract: Interpreting the decisions of deep image classifiers remains challenging, particularly in black-box settings where model internals are inaccessible. We

local-aiarxiv-cs-ai

Tools

OlmoEarth v1.1: A more efficient family of models

OlmoEarth v1.1 represents an updated release of Allen AI's open-source language models designed with improved efficiency compared to the original version. The update likely focuses on reduced computat

toolshugging-face

OmniSelect: Dynamic Modality-Aware Token Compression for Efficient Omni-modal Large Language Models

arXiv:2605.18041v1 Announce Type: new Abstract: Omnimodal large language models (OmniLLMs) have recently gained increasing attention for unified audio-video understanding. However, processing long mul

PH-Dreamer: A Physics-Driven World Model via Port-Hamiltonian Generative Dynamics

arXiv:2605.18303v1 Announce Type: cross Abstract: World models built on recurrent state space architectures enable efficient latent imagination, yet remain physically unstructured, producing dynamics

safetyarxiv-cs-ai

Position: Universal Time Series Foundation Models Rest on a Category Error

arXiv:2602.05287v2 Announce Type: replace Abstract: This position paper argues that the pursuit of 'Universal Foundation Models for Time Series' rests on a fundamental category error, mistaking a stru

pyforce-1.0.0: Python Framework for data-driven model Order Reduction of multi-physiCs problEms

arXiv:2605.18082v1 Announce Type: new Abstract: pyforce is a Python package implementing Data-Driven Reduced Order Modelling techniques for applications to multi-physics problems, mainly set in the Nu

researcharxiv-cs-lg

Tutorials

Sparse Deep Additive Model with Interactions: Enhancing Interpretability and Predictability

arXiv:2509.23068v2 Announce Type: replace-cross Abstract: Recent advances in deep learning highlight the need for personalized models that can learn from small samples, handle high-dimensional feature

tutorialsarxiv-cs-lg

Stabilizing, Scaling & Enhancing MeanFlow for Large-scale Diffusion Distillation

model-releasesarxiv-cs-cv

arXiv:2605.17834v1 Announce Type: new Abstract: Diffusion models exhibit remarkable generative capability, but their high latency limits practical deployment. Many studies have attempted to reduce sam

VA-Adapter: Adapting Ultrasound Foundation Model to Echocardiography Probe Guidance

arXiv:2510.06809v3 Announce Type: replace Abstract: Echocardiography is a critical tool for detecting heart diseases, yet its steep operational difficulty causes a shortage of skilled personnel. Probe

Applications

What Drives Success in Physical Planning with Joint-Embedding Predictive World Models?

arXiv:2512.24497v3 Announce Type: replace Abstract: A long-standing challenge in AI is to develop agents capable of solving a wide range of physical tasks and generalizing to new, unseen tasks and env

applicationsarxiv-cs-ai

When Marginals Match but Structure Fails: Covariance Fidelity in Generative Models

arXiv:2603.17041v2 Announce Type: replace-cross Abstract: Generative models are increasingly deployed as substitutes for real data in downstream scientific workflows, yet standard evaluation criteria

Your SaaS Is an Insurance Product: A Modeling Framework

model-releasesarxiv-cs-lg

arXiv:2605.16699v1 Announce Type: new Abstract: Capped-usage SaaS products -- LLM subscriptions such as Claude Code and ChatGPT, cloud platforms such as Vercel and Cloudflare Workers, corporate benefi

Applications

A Scalable Nonparametric Continuous-Time Survival Model through Numerical Quadrature

arXiv:2605.16208v1 Announce Type: cross Abstract: Flexible continuous-time survival modeling is critical for capturing complex time-varying hazard dynamics in high-dimensional data; however, training

applicationsarxiv-cs-lg

Congrats to the @cursor_ai team on Composer 2.5 — a huge milestone for agentic coding models. Together AI, the AI Native Cloud, is proud to …

Congrats to the @cursor_ai team on Composer 2.5 — a huge milestone for agentic coding models. Together AI, the AI Native Cloud, is proud to partner on this launch. Composer 2.5 is pushing the frontier

agentstogether-ai--x

Controllable Molecular Generative Foundation Models

arXiv:2605.15354v1 Announce Type: new Abstract: Despite the success of foundation models in language and vision, molecular graph generation still lacks a unified framework for heterogeneous design tas

safetyarxiv-cs-lg

GQLA: Group-Query Latent Attention for Hardware-Adaptive Large Language Model Decoding

arXiv:2605.15250v1 Announce Type: cross Abstract: Multi-head Latent Attention (MLA), the attention used in DeepSeek-V2/V3, jointly compresses keys and values into a low-rank latent and matches the H10

Tutorials

Health-Conditioned Vision-Language-Action Models for Malfunction-Aware Robot Control

arXiv:2605.16056v1 Announce Type: new Abstract: Research on Vision Language Action (VLA) models has been increasing rapidly in recent years. Although some of them focus on detecting, preventing, and r

tutorialsarxiv-cs-ro

LASER: Language Model Regression for Semi-Structured Workflow Resource and Runtime Estimation

arXiv:2512.19701v2 Announce Type: replace-cross Abstract: Accurate prediction of resource consumption and runtime for cloud workflow jobs is critical for scheduling efficiency, yet remains challenging

LLM-EDT: Large Language Model Enhanced Cross-domain Sequential Recommendation with Dual-phase Training

arXiv:2511.19931v2 Announce Type: replace-cross Abstract: Cross-domain Sequential Recommendation (CDSR) has been proposed to enrich user-item interactions by incorporating information from various dom

Multi-Probe Zero Collision Hash (MPZCH): Mitigating Embedding Collisions and Enhancing Model Freshness in Large-Scale Recommenders

model-releasesarxiv-cs-lg

arXiv:2602.17050v3 Announce Type: replace Abstract: Embedding tables are critical components of large-scale recommendation systems, facilitating the efficient mapping of high-cardinality categorical f

Neutral-Reference Prompting for Vision-Language Models

arXiv:2605.15615v1 Announce Type: new Abstract: Efficient transfer learning of vision-language models (VLMs) commonly suffers from a Base-New Trade-off (BNT): improving performance on unseen (new) cla

safetyarxiv-cs-cv

Reference Games as a Testbed for the Alignment of Model Uncertainty and Clarification Requests

arXiv:2601.07820v2 Announce Type: replace Abstract: In human conversation, both interlocutors play an active role in maintaining mutual understanding. When listeners are uncertain about what speakers

safetyarxiv-cs-cl

Tutorials

The @cursor_ai team shipped Composer 2 and now Composer 2.5 on the same Kimi K2.5 base model. Performance benchmarks are📈. Frontier quality…

The @cursor_ai team shipped Composer 2 and now Composer 2.5 on the same Kimi K2.5 base model. Performance benchmarks are📈. Frontier quality and open-source economics. 85% of the compute powering these

tutorialsfireworks-ai--x

Toward Natural and Companionable Virtual Agents via Cross-Temporal Emotional Modeling

arXiv:2605.15812v1 Announce Type: cross Abstract: Recent advances in foundation models have enabled conversational agents that aim for sustained companionship rather than mere task completion. Yet mos

Running Modern AI Image Models on a GTX 1060 6GB — A Practical Guide Tested & verified on NVIDIA GTX 1060 6GB (Pascal Architecture) · ComfyUI · May 2026 Written to counter the widespread misinformation that 'only SD 1.5 runs on 6GB VRAM'