Search: “models”

PARSE: Part-Aware Relational Spatial Modeling

arXiv:2603.07704v2 Announce Type: replace Abstract: Inter-object relations underpin spatial intelligence, yet existing representations -- linguistic prepositions or object-level scene graphs -- are to

researcharxiv-cs-cv

8 Jun 2026

Agents

Pega expands AI platform with agent orchestration, development tools and new pricing model

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DGX agent

Workflow automation vendor Pegasystems Inc. today unveiled a broad set of artificial intelligence enhancements aimed at helping enterprises deploy AI agents in mission-critical business processes whil

agentssiliconangle

8 Jun 2026

RPC-GS: Gaussian Splatting with native RPC Rendering for Satellite Imagery

arXiv:2606.06690v1 Announce Type: new Abstract: We present RPC-GS, the first Gaussian Splatting framework for satellite imagery that operates natively with Rational Polynomial Camera (RPC) models. The

8 Jun 2026

Hardware

VIRTUS-FPP: Virtual Sensor Modeling for Fringe Projection Profilometry in NVIDIA Isaac Sim

arXiv:2509.22685v2 Announce Type: replace-cross Abstract: Fringe projection profilometry (FPP) is a high-precision structured-light sensing technique for 3D surface reconstruction, yet its practical d

hardwarearxiv-cs-cv

8 Jun 2026

Bridging Domain Expertise and Generalization for Performance Estimation

arXiv:2606.06335v1 Announce Type: cross Abstract: Performance estimation under distribution shift aims to predict how a model behaves on an unlabeled test set whose distribution differs from the train

safetyarxiv-cs-ai

6 Jun 2026

Edit-R2: Context-Aware Reinforcement Learning for Multi-Turn Image Editing

arXiv:2606.05950v1 Announce Type: new Abstract: Text-guided image editing has advanced rapidly with diffusion models and unified multimodal foundation models. However, most existing methods remain con

6 Jun 2026

UniVoice: A Unified Model for Speech and Singing Voice Generation

arXiv:2606.05852v1 Announce Type: cross Abstract: Text-to-speech (TTS) and singing voice synthesis (SVS) both aim to generate human vocal audio from symbolic inputs, but they impose different requirem

safetyarxiv-cs-ai

6 Jun 2026

Learning What to Forget: Improving LLM Unlearning via Learned Token-Level Importance

arXiv:2606.06320v1 Announce Type: cross Abstract: Machine unlearning aims to remove targeted knowledge from a trained model while preserving its general capabilities. For autoregressive language model

researcharxiv-cs-cl

LoomVideo: Unifying Multimodal Inputs into Video Generation and Editing

arXiv:2606.06042v1 Announce Type: new Abstract: Developing unified video generation and editing models capable of interpreting interleaved multimodal inputs is a promising yet challenging frontier fie

Trajectory Dynamics in Language Model Hidden States Predict Human Processing Costs Beyond Surprisal

arXiv:2606.05346v1 Announce Type: new Abstract: Human language comprehension unfolds sequentially: each word is processed in the context of those that came before, and the interpretation builds increm

local-aiarxiv-cs-cl

Would you still call this Dax? Novel Visual References in VLMs and Humans

arXiv:2606.05409v1 Announce Type: cross Abstract: Vision-language models (VLMs), like human learners, are frequently exposed to new visual concepts, but how they map novel visual references to languag

A Pathology Foundation Model for Gastric Cancer with Real-World Validation

arXiv:2606.04792v1 Announce Type: new Abstract: Gastric cancer remains a major cause of cancer mortality, yet its histological and molecular heterogeneity complicates diagnosis and risk stratification

safetyarxiv-cs-cv

Beyond Retrieval: Learning Compact User Representations for Scalable LLM Personalization

arXiv:2606.04547v1 Announce Type: cross Abstract: Personalizing large language models requires adapting model behavior to individual users while preserving robustness and deployment-scale efficiency.

DSIRM: Learning Query-Bridged Discrete Semantic Identifiers for E-commerce Relevance Modeling

arXiv:2606.04374v1 Announce Type: cross Abstract: Despite rapid progress of continuous embeddings for e-commerce search relevance, a long-standing open problem is the difficulty in capturing fine-grai

tutorialsarxiv-cs-ai

GroupToM-Bench: Benchmarking Group Theory of Mind and Nonlinear Social Emergence in MLLMs

arXiv:2606.04184v1 Announce Type: new Abstract: True general intelligence requires not only a model of the physical world but also a social world model: the capacity to infer how individual mental sta

Imagine Before You Draw: Visual Prompt Engineering for Image Generation

arXiv:2606.04457v1 Announce Type: new Abstract: Incorporating visual semantic representations as an intermediate step before image generation can reduce the modeling difficulty between text and images

It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks

model-releasesarxiv-cs-lg

arXiv:2602.12147v4 Announce Type: replace Abstract: Time series foundation models (TSFMs) are revolutionizing the forecasting landscape from specific dataset modeling to generalizable task evaluation.

Longer Context, Deeper Thinking: Uncovering the Role of Long-Context Ability in Reasoning

arXiv:2505.17315v2 Announce Type: replace Abstract: Recent language models exhibit strong reasoning capabilities, yet the influence of long-context capacity on reasoning remains underexplored. In this

M^3Eval: Multi-Modal Memory Evaluation through Cognitively-Grounded Video Tasks

arXiv:2606.05008v1 Announce Type: cross Abstract: As multi-modal models advance towards long-form video understanding, memory emerges as a critical capability. Despite substantial efforts in developin

Measuring Model Robustness via Fisher Information: Spectral Bounds, Theoretical Guarantees, and Practical Algorithms

arXiv:2606.04767v1 Announce Type: cross Abstract: The robustness of deep neural networks is crucial for safety-critical deployments, yet existing evaluation methods are often attack-dependent and lack

safetyarxiv-cs-cv

Modeling and Interpreting Teamwork Dynamics in Cancer Care Outcome Prediction

arXiv:2606.04499v1 Announce Type: cross Abstract: Cancer care requires a longitudinal approach in which treatments are planned and delivered over time according to the needs of each individual patient

tutorialsarxiv-cs-lg

PE-MHL: Physics-Encoded Modular Hybrid Layers for Scalable Learning of Complex Systems

model-releasesarxiv-cs-lg

arXiv:2606.04290v1 Announce Type: new Abstract: Hybrid models that combine physics-based and data-driven components have shown strong potential for achieving accuracy and interpretability in control a

Physics-Informed Neural Network Modeling of Biodegradable Contaminant Transport through GCL/SL Composite Liners

arXiv:2606.04392v1 Announce Type: cross Abstract: This study develops a two-domain physics-informed neural network framework for contaminant transport through a GCL/SL composite liner system, in which

researcharxiv-cs-cl

RAMPART: Registry-based Agentic Memory with Priority-Aware Runtime Transformation

arXiv:2606.04628v1 Announce Type: new Abstract: RAMPART is a compile-time memory model and pure in-RAM block registry for LLM-based agents. Context assembly is a programmable runtime operation where c

SFMambaNet: Spectral-Frequency Enhanced Selective State Space Model for Correspondence Pruning

arXiv:2606.04493v1 Announce Type: cross Abstract: Correspondence pruning aims to identify inliers from an initial set of correspondences. Most existing Graph Neural Network (GNN)-based methods rely on

Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation

arXiv:2606.04665v1 Announce Type: new Abstract: Deep unsupervised domain adaptation (Deep UDA) methods successfully leverage rich labeled data in a source domain to boost the performance on related bu

researcharxiv-cs-lg

A formal definition and meta-model for a machine theory of mind

arXiv:2606.03471v1 Announce Type: new Abstract: This paper proposes, for the first time, a rigorous formal definition of the concept of Machine Theory of Mind, based on principles supported by evidenc

Assessing and Mitigating Miscalibration in LLM-Based Social Science Measurement

arXiv:2605.11954v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in social science as scalable measurement tools for converting unstructured text into variables t

Backdoor Unlearning Generalization: A Path Toward the Removal of Unknown Triggers in LLMs

arXiv:2606.03785v1 Announce Type: new Abstract: Backdoor attacks in Large Language Models (LLMs) are a growing security concern, where models can generate adversary-chosen content. Existing defenses t

safetyarxiv-cs-cl

Bayesian Tensor Decomposition with Diffusion Model Prior

arXiv:2606.03212v1 Announce Type: new Abstract: Low-rank tensor decomposition (TD) is usually effective on clean, fully observed data, but it often degrades under severe missingness or noise. Low-rank

safetyarxiv-cs-lg

CL-DMDF:Dynamic Multimodal Data Fusion Model Based on Contrastive Learning

arXiv:2606.02659v1 Announce Type: cross Abstract: Multimodal data fusion involves integrating and analyzing information from multiple modalities to uncover latent correlations and complementary patter

local-aiarxiv-cs-ai

Ideogram 4.0 Just Open Sourced!

local-air-stablediffusion

Ideogram released version 4.0 of its text-to-image model as an open-weight model with native 2K resolution, bounding box control, and improved text rendering. The model weights are available on GitHub

Agents

Learning to See via Epiretinal Implant Stimulation in silico with Model-Based Deep Reinforcement Learning

arXiv:2606.03118v1 Announce Type: cross Abstract: Objective: Diseases such as age-related macular degeneration and retinitis pigmentosa cause the degradation of the photoreceptor layer. One approach t

agentsarxiv-cs-cv

PRISM: Rethinking Atmospheric Scattering Reconstruction as a Unified Understanding and Restoration Model for Real-world Dehazing

arXiv:2604.07048v2 Announce Type: replace Abstract: Real-world image dehazing (RID) aims to remove haze-induced degradation from real scenes. This task remains challenging due to non-uniform haze dist

tutorialsarxiv-cs-cv

Re-Ranking Through an Attribution Lens for Citation Quality in Legal QA

arXiv:2606.03728v1 Announce Type: new Abstract: Retrieval-augmented generation systems for legal question answering typically retrieve passages based on semantic similarity and provide them to a langu

SleepVLM: Explainable and Rule-Grounded Sleep Staging via a Vision-Language Model

arXiv:2603.26738v3 Announce Type: replace-cross Abstract: While automated sleep staging has achieved expert-level accuracy, its clinical adoption is hindered by a lack of auditable reasoning. We intro

The Word and the Way: Strategies for Domain-Specific BERT Pre-Training in German Medical NLP

arXiv:2606.03250v1 Announce Type: new Abstract: Digital healthcare generates vast amounts of clinical text that can support AI-assisted applications, yet German biomedical language models remain limit

Applications

TiWeaver: Unified Temporal Dynamics Modeling via Contextual Patching

arXiv:2606.03121v1 Announce Type: new Abstract: Multivariate time series forecasting plays a critical role in real-world applications, including weather prediction, stock analysis, and health monitori

applicationsarxiv-cs-lg

Hardware

Towards Compact Autonomous Driving Perception with Balanced Learning and Multi-sensor Fusion

arXiv:2606.02979v1 Announce Type: cross Abstract: We present a novel compact deep multi-task learning model to handle various autonomous driving perception tasks in one forward pass. The model perform

hardwarearxiv-cs-ai

Trans GAN-WT: A Feature Extraction and Interactive Learning-Based Anomaly Detection Model for Wind Turbine Time Series Data

arXiv:2606.03112v1 Announce Type: cross Abstract: With the increasing scale and number of wind farms, wind turbines' daily operation and maintenance costs are increasing. To reduce operation and maint

researcharxiv-cs-lg

WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation

arXiv:2503.07265v4 Announce Type: replace-cross Abstract: Text-to-Image (T2I) models are capable of generating high-quality artistic creations and visual content. However, existing research and evalua

A Modelling and Evaluation Framework for EuroCrops-Driven Sentinel-2 Crop Segmentation

arXiv:2606.00676v1 Announce Type: new Abstract: This work presents a configurable pipeline for generating semantic-segmentation-ready agricultural datasets from Sentinel-2 imagery and EuroCrops parcel

safetyarxiv-cs-cv

A physics-informed foundation model for quantitative diffusion MRI

arXiv:2606.00156v1 Announce Type: cross Abstract: Understanding the human brain requires access to its microscopic tissue architecture. Diffusion magnetic resonance imaging (MRI) provides the only non

Applications

Advanced Mathematics Learning Behavior Prediction and Academic Early Warning Model Based on Multimodal Data Analysis

arXiv:2606.01224v1 Announce Type: new Abstract: Early detection of at-risk students and timely academic intervention pose major challenges in advanced mathematics education, where complex conceptual h

applicationsarxiv-cs-ai

AFUN: Towards an Affordance Foundation Model for Functionality Understanding

arXiv:2606.02551v1 Announce Type: cross Abstract: Affordance understanding bridges visual perception and physical action, serving as an explainable interface for robot manipulation in open and unstruc

local-aiarxiv-cs-cv

BenchEvolver: Frontier Task Synthesis via Solution-Centric Evolution

arXiv:2606.01286v1 Announce Type: cross Abstract: The rapid progress of frontier large language models has led to widespread benchmark saturation, limiting the ability of existing datasets to differen

ChartArena: Benchmarking Chart Parsing across Languages, Scenarios, and Formats

arXiv:2606.01348v1 Announce Type: new Abstract: Charts are a primary medium for conveying quantitative and relational information, yet systematically evaluating chart parsing models remains difficult.

CLIP-like Model as a Foundational Density Ratio Estimator

arXiv:2506.22881v3 Announce Type: replace Abstract: Density ratio estimation is a core concept in statistical machine learning because it provides a unified mechanism for tasks such as importance weig

tutorialsarxiv-cs-cv