Search: “models”

JuZhou 1.0 Technical Report: The First Edge-Native Text-to-Image Foundation Model Trained Entirely on China-Developed AI Accelerators

arXiv:2606.28421v1 Announce Type: cross Abstract: Text-to-image (T2I) diffusion models typically require substantial computational resources and cloud infrastructure, posing significant challenges for

30 Jun 2026

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MM-Nav: Multi-View VLA Model for Robust Visual Navigation via Multi-Expert Learning

DGX agent

arXiv:2510.03142v2 Announce Type: replace-cross Abstract: Visual navigation policy is widely regarded as a promising direction, as it mimics humans by using egocentric visual observations for navigati

safetyarxiv-cs-cv

30 Jun 2026

SVC-Probe: A Framework for Evaluating Perturbation Generalization in Spatial Foundation-Model Embeddings

arXiv:2606.28465v1 Announce Type: cross Abstract: This work examines perturbation generalization in spatial foundation-model embeddings derived from fluorescence microscopy images. Although these mode

30 Jun 2026

t-STEP: An interpretable model for Total Electron Content predictions and irregularities estimations

arXiv:2606.29644v1 Announce Type: new Abstract: Earth system infrastructures relying on satellite-based technologies, such as Global Positioning System (GPS) communications, are affected by ionospheri

researcharxiv-cs-lg

30 Jun 2026

MobileManiBench: Simplifying Model Verification for Mobile Manipulation

model-releasesarxiv-cs-ro

arXiv:2602.05233v2 Announce Type: replace Abstract: Vision-language-action models have advanced robotic manipulation but remain constrained by reliance on the large, teleoperation-collected datasets d

29 Jun 2026

The Weakest Link Tells It All: Outcome-Supervised Process Reward Modeling via Learnable Credit Assignment

arXiv:2606.27739v1 Announce Type: new Abstract: Process reward models (PRMs) enhance the reasoning capabilities of large language models (LLMs) by providing fine-grained feedback, yet training PRMs ty

researcharxiv-cs-lg

29 Jun 2026

EPTS: Elastic Post-Training Sparsity for Efficient Large Language Model Compression

arXiv:2606.25285v1 Announce Type: new Abstract: Post-Training Sparsity (PTS) has emerged as a crucial paradigm for compressing Large Language Models to facilitate efficient deployment on resource-cons

25 Jun 2026

Agents

RoDyn: Taming Interactive Robot-Dynamic 2.5D World Model for Robotic Manipulation

arXiv:2510.09036v2 Announce Type: replace Abstract: Learned world models hold significant potential as neural simulators for robotic manipulation. However, prevalent 2D video-based models inherently l

agentsarxiv-cs-ro

25 Jun 2026

AdversaBench: Automated LLM Red-Teaming with Multi-Judge Confirmation and Cross-Model Transferability

arXiv:2606.24589v1 Announce Type: new Abstract: Scaling adversarial evaluation of large language models requires both a method for generating hard inputs and a reliable way to confirm that resulting f

24 Jun 2026

Business as Rulesual: A Benchmark and Framework for Business Rule Flow Modeling with LLMs

model-releasesarxiv-cs-cl

arXiv:2505.18542v4 Announce Type: replace Abstract: Extracting structured procedural knowledge from unstructured business documents is a critical yet unresolved bottleneck in process automation. While

24 Jun 2026

Applications

HyMaTE: A Hybrid Mamba and Transformer Model for EHR Representation Learning

arXiv:2509.24118v2 Announce Type: replace Abstract: Electronic health Records (EHRs) have become a cornerstone in modern-day healthcare. They are a crucial part for analyzing the progression of patien

applicationsarxiv-cs-lg

24 Jun 2026

A-Evolve-Training: Autonomous Post-Training of a 30B Model

arXiv:2606.20657v1 Announce Type: cross Abstract: Post-training a frontier model is normally weeks of human work: proposing data and recipe changes, launching runs, reading evals, deciding what to kee

A Linear Fractional Transformation Model and Calibration Method for Light Field Camera

arXiv:2511.03962v2 Announce Type: replace Abstract: Accurate intrinsic calibration is a crucial yet challenging prerequisite for 3D reconstruction using light field cameras. Existing calibration model

L20-Edu-135M: An Auditable Single-GPU Study of Data-Efficient Small Language Modeling

arXiv:2606.22189v1 Announce Type: new Abstract: Small language models are cheap to serve and feasible on local hardware, but strong public 135M-class systems are commonly trained with hundreds of bill

Learning-Based Modeling of Soft Robots via Cosserat Rod Theory

arXiv:2606.20958v1 Announce Type: new Abstract: Modeling soft robot dynamics is challenging due to their continuum structure and typically nonlinear dynamics. Creating models based on first-order prin

researcharxiv-cs-ro

Load Testing for Machine Learning Model Serving Systems at Scale

arXiv:2606.22013v1 Announce Type: new Abstract: Machine learning (ML) model serving has become a dominant consumer of GPU infrastructure, yet capacity planning in these systems remains largely ad hoc.

Model Inversion meets Cryptographic Fuzzy Extractors

arXiv:2510.25687v3 Announce Type: replace-cross Abstract: Model inversion attacks pose an open challenge to privacy-sensitive applications that use machine learning (ML) models. For example, face auth

researcharxiv-cs-lg

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PAIWorld: A 3D-Consistent World Foundation Model for Robotic Manipulation

arXiv:2606.18375v2 Announce Type: replace Abstract: World foundation models (WFMs) are powerful simulators, yet they predominantly operate in a single-view setting and lack the multi-view 3D consisten

safetyarxiv-cs-ro

Safety

VRPO: Rethinking Value Modeling for Robust RL under Noisy Supervision in LLM Post-Training

arXiv:2508.03058v2 Announce Type: replace Abstract: Reinforcement Learning (RL) in real-world environments often suffers from ambiguous or incomplete reward supervision, which undermines policy stabil

safetyarxiv-cs-lg

Agents

Skill-Augmented AI Agents for Medical Research Analysis: An Exploratory Multi-Model Human Evaluation in an NSCLC Transcriptomic Biomarker Task

arXiv:2606.11830v1 Announce Type: new Abstract: Background. Large language models and AI agents are increasingly used to support biomedical research, but native model outputs may omit key analytical s

agentsarxiv-cs-ai

11 Jun 2026

Efficient-WAM: A 1B-Parameter World-Action Model with Low-Cost Future Imagination

model-releasesarxiv-cs-ro

arXiv:2606.10040v1 Announce Type: new Abstract: World-Action Models (WAMs) have emerged as a promising paradigm for embodied control by coupling future visual prediction with action generation. Howeve

FADA: Accessible fetal ultrasound interpretation and annotation with a selectively distilled unified vision-language model

arXiv:2606.11106v1 Announce Type: cross Abstract: A global shortage of trained sonographers limits prenatal ultrasound screening in low- and middle-income countries, where over half of pregnant women

P3D-Bench: Benchmarking MLLMs for Parametric 3D Generation and Structural Reasoning

arXiv:2606.11152v1 Announce Type: new Abstract: Multimodal large language models can write code to produce complex programs as well as use programs to do 3D modeling, which opens up a new avenue for 3

SARM2: Multi-Task Stage Aware Reward Modeling for Self Improving Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.10305v1 Announce Type: new Abstract: Fine-tuning vision-language-action (VLA) policies for long-horizon manipulation still relies heavily on behavior cloning, which requires costly high-qua

BUDDY: BUdget-Driven DYnamic Depth Routing for Adaptive Large Language Model Inference

arXiv:2606.09514v1 Announce Type: new Abstract: Large language models (LLMs) incur high inference cost due to their depth and parameter scale. Depth pruning can reduce latency by skipping redundant Tr

9 Jun 2026

Safety

CheXanatomy: Anatomy-Aware Vision-Language Modeling for Chest Radiographs

arXiv:2606.08420v1 Announce Type: new Abstract: Vision-language models (VLMs) pretrained on large-scale image-text pairs demonstrate strong image-level understanding, but are primarily optimized for g

safetyarxiv-cs-cv

9 Jun 2026

HASA: Subnet Allocation for Compute-Constrained Model-Heterogeneous Federated Learning

arXiv:2606.07621v1 Announce Type: cross Abstract: Edge services increasingly use federated learning to personalize on-device models while keeping sensitive data local. In practice, deployments must ha

9 Jun 2026

Rethinking Genomic Modeling Through Optical Character Recognition

arXiv:2602.02014v2 Announce Type: replace-cross Abstract: Recent genomic foundation models largely adopt large language model architectures that treat DNA as a one-dimensional token sequence. However,

researcharxiv-cs-ai

8 Jun 2026

CogManip: Benchmarking Manipulative Behavior in Multi-Turn Interactions with Large Language Model

arXiv:2606.06099v1 Announce Type: new Abstract: Whether Large Language Models (LLMs) exhibit covert psychological manipulation in complex human-AI interactions has garnered increasing safety concerns.

6 Jun 2026

AdaPlanBench: Evaluating Adaptive Planning in Large Language Model Agents under World and User Constraints

model-releasesarxiv-cs-cl

arXiv:2606.05622v1 Announce Type: new Abstract: Planning for real-world problems by language models often involves both world and user constraints, which may not be fully specified upfront and are pro

5 Jun 2026

FUSAR-GPT : A Spatiotemporal Feature-Embedded and Two-Stage Decoupled Visual Language Model for SAR Imagery

arXiv:2602.19190v4 Announce Type: replace Abstract: Research on the intelligent interpretation of all-weather, all-time Synthetic Aperture Radar (SAR) is crucial for advancing remote sensing applicati

5 Jun 2026

Applications

An Ensembled Latent Factor Model via Differential Evolution and Gradient Descent Optimization

arXiv:2606.04408v1 Announce Type: cross Abstract: High-dimensional and incomplete (HDI) data are prevalent in many real-world big data scenarios. Latent factor models serve as a common representation

applicationsarxiv-cs-ai

Audio Interaction Model

arXiv:2606.05121v1 Announce Type: cross Abstract: Audio is an inherently interactive modality, yet today's Large Audio Language Models (LALMs) are offline, and streaming audio models each handle only

researcharxiv-cs-ai

Food-R1: A Unified Multi-Task Food Vision-Language Model with Reinforcement Learning

arXiv:2606.04986v1 Announce Type: new Abstract: Recent studies have explored Vision-Language Models (VLMs) for food analysis. However, most existing methods rely primarily on supervised fine-tuning (S

LoopMoE: Unifying Iterative Computation with Mixture-of-Experts for Language Modeling

arXiv:2606.04438v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) and looped architectures scale models along two orthogonal axes, namely parameter capacity and effective depth. However, main

SPLIT-PINN: Separable Probability Learning Technique via Physics-Informed Neural Networks for High-Dimensional Probabilistic Modeling

arXiv:2606.04000v1 Announce Type: cross Abstract: We present a probabilistic modeling framework for incorporating small-scale spatial heterogeneity into macroscopic descriptions of material behavior f

UniCAD: A Unified Benchmark and Universal Model for Multi-Modal Multi-Task CAD

arXiv:2606.05058v1 Announce Type: cross Abstract: Computer-Aided Design (CAD) underpins modern engineering and manufacturing by enabling the creation of precise, editable 3D models. However, CAD resea

Tutorials

A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners

arXiv:2606.03685v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) improves end-to-end classical planning in large language models (LLMs), but do these models also learn to represent and r

tutorialsarxiv-cs-ai

3 Jun 2026

BehaviorBench: Modeling Real-World User Decisions from Behavioral Traces

arXiv:2606.02798v1 Announce Type: new Abstract: Many decision-support settings require systems that adapt to individual users, but evaluation data for this problem remain limited. Existing benchmarks

3 Jun 2026

RogueMerge: Robust and Unified Attacks against LLM Model Merging

arXiv:2606.03344v1 Announce Type: cross Abstract: Model merging composes specialized capabilities into a single LLM by aggregating task vectors sourced from unverified public platforms, exposing a cri

3 Jun 2026

Beyond Isolated Behaviors: Hierarchical User Modeling for LLM Personalization

model-releasesarxiv-cs-cl

arXiv:2606.02300v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse domains, yet personalizing their outputs to individual users remai

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts?

arXiv:2505.16915v3 Announce Type: replace-cross Abstract: While recent Text-to-Image (T2I) models show impressive capabilities in synthesizing images from brief descriptions, they struggle with the lo

Emergent Transfer of a Physics Foundation Model from Simulation to Laboratory Turbulence

arXiv:2606.01470v1 Announce Type: cross Abstract: Whether physics foundation models can be usefully deployed on laboratory experiments remains an open question for scientific machine learning (ML). We

researcharxiv-cs-ai

Machine Learning Surrogate Modeling for Homogenization of Hyperelastic Materials with Boolean Microstructures

arXiv:2606.00938v1 Announce Type: cross Abstract: Data-driven surrogate models are an alternative to numerical homogenization of heterogeneous materials. In this contribution, a supervised learning ap

Margin Adaptive DPO: Leveraging Reward Model for Granular Control in Preference Optimization

arXiv:2510.05342v2 Announce Type: replace-cross Abstract: Direct Preference Optimization (DPO) has emerged as a simple and effective method for aligning large language models. However, its reliance on

ProbeScale: Probing Analysis to Optimize Neural Scaling Laws for Efficient Small Language Model Inference

arXiv:2606.01806v1 Announce Type: cross Abstract: Small Language Models (SLMs) offer a balance between capability and computational feasibility. Neural scaling laws inform their optimal training, sugg

Agents

Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends

arXiv:2606.01164v1 Announce Type: new Abstract: With rapid development of large language models and diffusion-based content generation, world modeling has attracted increasing research attention, bene

agentsarxiv-cs-cv

Local Ai

Understanding-Enhanced Model Collaboration for Long-Tailed Egocentric Mistake Detection

arXiv:2606.02120v1 Announce Type: cross Abstract: In this report, we address the problem of determining whether a user performs an action incorrectly from egocentric video data. To this end, we propos

local-aiarxiv-cs-ai