Search: “models”

Sampling the Schwinger Model with Gauge-Equivariant Diffusion

arXiv:2606.27481v1 Announce Type: cross Abstract: We present a first study of a diffusion-based approach to accelerated sampling of the N_f = 2 lattice Schwinger model. Our work is inspired by recent

29 Jun 2026

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SIFT: Self-Imagination Fine-Tuning for Physically Plausible Motion in Video Diffusion Models

DGX agent

arXiv:2606.27741v1 Announce Type: new Abstract: Recent advances in video diffusion models have greatly improved visual fidelity, yet their generated motions often violate physical plausibility. We obs

safetyarxiv-cs-cv

29 Jun 2026

A Generalization Theory for JEPA-Based World Models

arXiv:2606.27014v1 Announce Type: new Abstract: Joint Embedding Predictive Architectures (JEPAs) have recently emerged as a promising paradigm for world modeling by learning predictive dynamics in a l

A Latent ODE Approach to Spatiotemporal Modeling of Cine Cardiac MRI

arXiv:2606.26718v1 Announce Type: new Abstract: Cardiac magnetic resonance imaging (CMR) captures rich spatiotemporal information about ventricular structure and motion, but conventional risk models u

EO-WM: A Physically Informed World Model for Probabilistic Earth Observation Forecasting

arXiv:2606.27277v1 Announce Type: new Abstract: Earth Observation (EO) forecasting aims to predict future Earth surface dynamics from satellite observations under changing meteorological conditions. I

Exploring the Intrinsic Geometry of Diffusion Models with Constrained Inverse Kinematics

arXiv:2606.26408v1 Announce Type: new Abstract: Recent studies suggest that diffusion models can recover geometric structure in the data manifolds they are trained on, yet the supporting evidence has

researcharxiv-cs-ro

ForesightSafety-VLA: A Unified Diagnostic Safety Benchmark for Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2606.27079v1 Announce Type: new Abstract: In embodied intelligence, safety is a prerequisite for reliable robot deployment in the physical world. Current vision-language-action (VLA) models cont

Applications

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models

arXiv:2506.15681v4 Announce Type: replace Abstract: Recent advancements in vision-language models (VLMs) have leveraged large language models (LLMs) to achieve performance on par with closed-source sy

applicationsarxiv-cs-cl

KARLA: Knowledge-base Augmented Retrieval for Language Models

arXiv:2606.26807v1 Announce Type: new Abstract: We propose a new method that allows an LLM to automatically pull in factual knowledge from a knowledge base during token generation. This means that (1)

MLFFM-SegDiff: A Multi-Level Feature Fusion Diffusion Model for Skin Lesion Segmentation

arXiv:2606.26712v1 Announce Type: cross Abstract: Skin lesion segmentation is a key task in computer-aided dermatological diagnosis, where accuracy directly impacts downstream analysis and disease cla

On-board Remote-Sensing Foundation Models for Unsupervised Change Detection of Disaster Events

arXiv:2606.27018v1 Announce Type: cross Abstract: Remote Sensing Foundation Models (RSFMs) have emerged as a powerful alternative to supervised models for Earth Observation, allowing satellites to aut

PhysEditWorld: A Large-Scale Dataset Toward Physics-Editable World Models

arXiv:2606.26694v1 Announce Type: new Abstract: Recent game world models can synthesize visually plausible, action-conditioned rollouts. However, their interaction behaviors often remain limited to ex

safetyarxiv-cs-cv

Tuning Language Models by Mixture-of-Depths Ensemble

arXiv:2410.13077v2 Announce Type: replace-cross Abstract: Transformer-based Large Language Models (LLMs) traditionally rely on final-layer loss for finetuning and final-layer representations for predi

Agentic evolution of physically constrained foundation models

model-releasesarxiv-cs-lg

arXiv:2606.25532v1 Announce Type: cross Abstract: Artificial intelligence increasingly drives automated scientific discovery, yet contemporary generalist agents lack physical grounding, frequently hal

Conformal Orbit-Valid Trust Horizons for Equivariant World Models

arXiv:2606.24946v1 Announce Type: new Abstract: Learned world models are useful only over horizons on which their rollout error remains controlled. We study trust-horizon certification for latent worl

Elo-Disentangled Player-Style Embeddings for Human Chess via Rating-Conditioned Residual Move Model

arXiv:2606.25176v1 Announce Type: new Abstract: We study representation learning for individual human chess style: a per-player embedding learned from a player's move history such that inner products

From Sounds to Scenes: A Benchmark for Evaluating Context-Aware Auditory Scene Understanding in Large Audio Language Models

arXiv:2606.25391v1 Announce Type: cross Abstract: Recent Large Audio Language Models (LALMs) have achieved remarkable progress in audio perceptual tasks across individual acoustic layers, including sp

LibEvoBench: Probing Temporal Knowledge Stratification in Code Generation Models

arXiv:2606.25402v1 Announce Type: cross Abstract: Large software projects often depend on older versions of libraries, even as APIs continue to evolve across releases. This creates a challenge for LLM

MiniOpt: Reasoning to Model and Solve General Optimization Problems with Limited Resources

arXiv:2606.25832v1 Announce Type: new Abstract: Achieving strong optimization generalization across diverse optimization problems while requiring limited training resources remains a challenging probl

safetyarxiv-cs-lg

Privacy-Aware Visual Language Models

arXiv:2405.17423v4 Announce Type: replace-cross Abstract: As Visual Language Models (VLMs) become increasingly embedded in everyday applications, ensuring they can recognise and appropriately handle p

SpeechEQ: Benchmarking Emotional Intelligence Quotient in Socially Aware Voice Conversational Models

arXiv:2606.25990v1 Announce Type: new Abstract: As multimodal conversational systems increasingly engage in spoken interaction, their ability to navigate paralinguistic social cues has become a critic

Wan-Streamer v0.1: End-to-end Real-time Interactive Foundation Models

arXiv:2606.25041v1 Announce Type: new Abstract: We present Wan-Streamer, a native-streaming, end-to-end interactive foundation model designed from the ground up for real-time, low-latency, full-duplex

Age of LLM: A Strategic 1v1 Benchmark for Reasoning, Diplomacy and Reliability of Large Language Models under Fog of War

arXiv:2606.24391v1 Announce Type: new Abstract: We introduce Age of LLM, a turn-based 1v1 benchmark in which two LLMs face off on a 13x7 grid to destroy the enemy base. Three stressors are deliberate:

Agents

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models

arXiv:2606.24152v1 Announce Type: new Abstract: Existing literature claims that video generation essentially is world modelling. On the one hand, the claim is productive because it pushes generative A

agentsarxiv-cs-cv

CALIBER: Calibrating Confidence Before and After Reasoning in Language Models

arXiv:2606.24281v1 Announce Type: cross Abstract: Reasoning language models are increasingly asked not only to answer difficult questions, but also to estimate their likelihood of success. Existing me

FISHER: A Foundation Model for Multi-Modal Industrial Signal Comprehensive Representation

arXiv:2507.16696v3 Announce Type: replace-cross Abstract: Industrial signal analysis is hindered by severe data heterogeneity, which we characterize as the M5 problem. Existing solutions rely on speci

Geometric Action Model for Robot Policy Learning

arXiv:2606.17046v2 Announce Type: replace-cross Abstract: Generalist robot policies must follow user instructions while reasoning about how objects, cameras, and robot actions interact in the 3D physi

safetyarxiv-cs-cv

L3Cube-MahaPOS: A Marathi Part-of-Speech Tagging Dataset and BERT Models

arXiv:2606.24825v1 Announce Type: new Abstract: Part-of-Speech (POS) tagging is a foundational NLP task underpinning machine translation, information extraction, and syntactic parsing. Despite Marathi

Maestro Order: A Model-Agnostic Orchestration Harness

arXiv:2606.23983v1 Announce Type: cross Abstract: A single forward pass of a capable model is a fast, fluent, and unreliable problem-solver: it is right often enough to be useful and wrong often enoug

MambaRaw: Selective State Space Modeling for Efficient 4K Raw Image Reconstruction

model-releasesarxiv-cs-cv

arXiv:2606.24479v1 Announce Type: new Abstract: In-camera JPEG previews are ubiquitous in raw image formats and provide an sRGB reference at negligible storage cost. Although existing metadata-based r

MedBench v5: A Dynamic, Process-Oriented, and Hallucination-Aware Benchmark for Clinical Multimodal Models

arXiv:2606.24155v1 Announce Type: new Abstract: Existing medical AI benchmarks lack process visibility, atomic skill evaluation, and integrated hallucination detection. We introduce MedBench v5, a red

On the Stability of Prompt Ranking in Large Language Model Evaluation

arXiv:2606.24381v1 Announce Type: cross Abstract: Prompt-based interaction has become a dominant paradigm for using large language models (LLMs), where multiple candidate prompts are evaluated and the

Pigeonholing: Bad prompts hurt models to collapse and make mistakes

arXiv:2606.24267v1 Announce Type: cross Abstract: While in-context learning is generally shown to be effective in Large Language Models (LLMs), bad contexts can cause performance degradation and mode

Reinforcement Learning Towards Broadly and Persistently Beneficial Models

arXiv:2606.24014v1 Announce Type: new Abstract: As AI systems are deployed across increasingly diverse and high-stakes settings, model alignment must generalize beyond the tasks and domains seen durin

S1-Omni-Image: A Unified Model for Scientific Image Understanding, Generation, and Editing

arXiv:2606.24441v1 Announce Type: new Abstract: We present S1-Omni-Image, an open-weight unified multimodal model for scientific image understanding, generation, and editing. Unlike general-purpose im

ScaleToT: Generalizing Structured LLM Reasoning for Billion-Scale Low-Activity User Modeling

arXiv:2606.24605v1 Announce Type: new Abstract: Accurate user modeling often depends on rich interaction histories, which are unavailable for billions of low-activity users. Large Language Models (LLM

When Preferences Fail to Become Incentives: A Utility-Behavior Gap in Large Language Models

arXiv:2606.22974v2 Announce Type: replace Abstract: Recent work on preference elicitation in large language models (LLMs) has demonstrated that, when given a series of choices between two outcomes, LL

BadDreamer: Transferable Backdoor Attacks against Video World Models for Autonomous Driving

arXiv:2606.21172v1 Announce Type: new Abstract: Video world models are increasingly used in autonomous driving to forecast future scene evolution and provide future-aware spatio-temporal representatio

safetyarxiv-cs-cv

Certified World Models: Predictability Across Configuration, Horizon, and Resolution

arXiv:2606.13092v2 Announce Type: replace Abstract: Scale buys interpolation; structure buys certifiable transfer. A world model's average error does not say whether a particular rollout can be truste

Detail++: Training-Free Detail Enhancer for T2I Diffusion Models

model-releasesarxiv-cs-cv

arXiv:2507.17853v3 Announce Type: replace Abstract: Recent advances in text-to-image (T2I) generation have led to impressive visual results. However, these models still face significant challenges whe

Does RoPE Prevent or Degrade Retrieval Heads? A Mechanistic Analysis Across Model Families

model-releasesarxiv-cs-lg

arXiv:2606.21249v1 Announce Type: new Abstract: Retrieval heads, attention heads that copy information from earlier context to the current position, have been proposed as the mechanistic substrate for

dVLA-RL: Reinforcement Learning over Denoising Trajectories for Discrete Diffusion Vision-Language-Action Models

arXiv:2606.23623v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have established a powerful paradigm for generalist robotic manipulation by grounding control into the semantic reas

safetyarxiv-cs-ro

HiL-ResRL: A Model-Agnostic Finetuning Adapter via Human-in-the-loop Residual Reinforcement Learning

arXiv:2606.22860v1 Announce Type: new Abstract: Recent advancements in generative imitation learning have significantly propelled the field of robotic manipulation. However, the majority of existing m

safetyarxiv-cs-ro

Large Language Model-Assisted Cleaning of Report-Derived Labels in a Large-Scale Chest CT Dataset

model-releasesarxiv-cs-cv

arXiv:2606.22382v1 Announce Type: cross Abstract: Purpose: To evaluate whether large language model (LLM)-assisted label cleaning can identify label-report discordance in CT-RATE, a large-scale public

NeuroShield: A Device-Agnostic Foundation Model for EEG Authentication

arXiv:2606.20673v1 Announce Type: cross Abstract: A central challenge in EEG authentication is that models are typically tied to the acquisition settings in which they are trained. In particular, vari

OGD4All: A Framework for Accessible Interaction with Geospatial Open Government Data Based on Large Language Models

model-releasesarxiv-cs-lg

arXiv:2602.00012v3 Announce Type: replace Abstract: We present OGD4All, a transparent, auditable, and reproducible framework based on Large Language Models (LLMs) to enhance citizens' interaction with

Prompting Diffusion Models for Zero-Shot Instance Segmentation

arXiv:2606.22660v1 Announce Type: new Abstract: Several disruptive research directions have recently emerged in computer vision, including foundation models achieving previously unseen zero-shot perfo

Quantum Convolutional Neural Networks for Groundwater Heat Plume Prediction: A Surrogate Modeling Approach

arXiv:2606.23411v1 Announce Type: cross Abstract: Quantum machine learning methods are increasingly explored for modeling complex environmental systems, including groundwater heat plume dynamics. In t