Search: “model-releases”

EgoSafetyBench: A Diagnostic Egocentric Video Benchmark for Evaluating Embodied VLMs as Runtime Safety Guards

arXiv:2607.00218v1 Announce Type: cross Abstract: Vision-language models (VLMs) are now proposed as runtime safety guards for embodied agents in homes and factories. A deployable guard must catch genu

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Model Releases

EmbodimentSemantic: A Spatial Scene-Graph Dataset and Benchmark for Vision-Language Models on Embodied Manipulation Trajectories

DGX agent

arXiv:2607.00020v1 Announce Type: new Abstract: Spatial grounding remains a key limitation of vision-language-action (VLA) systems for robotic manipulation. While current models can recognize objects

model-releasesarxiv-cs-ro

2 Jul 2026

End-to-End Training for Autoregressive Video Diffusion via Self-Resampling

arXiv:2512.15702v2 Announce Type: replace Abstract: Autoregressive video diffusion models hold promise for world simulation but are vulnerable to exposure bias arising from the train-test mismatch. Wh

Enhanced Vision-Language Models for Diverse Sensor Understanding: Cost-Efficient Optimization and Benchmarking

arXiv:2412.20750v3 Announce Type: replace Abstract: Large-scale Vision-Language Models (VLMs) have achieved notable progress in aligning visual inputs with text. However, their ability to deeply under

Entropy-Regularized Probabilistic Gates for Sparse Model Discovery in Scarce-Data Federated Learning

arXiv:2607.00275v1 Announce Type: cross Abstract: Federated Learning (FL) is a distributed machine learning (ML) paradigm with collaboration among multiple clients without sharing data. FL is challeng

EPC: A Standardized Protocol for Measuring Evaluator Preference Dynamics in LLM Agent Systems

arXiv:2607.00297v1 Announce Type: cross Abstract: When LLM agents use evaluator feedback to adapt their behavior in closed loops, evaluator biases propagate through the agent's strategy distribution -

EVOTS: Evolutionary Transformer Search for Time Series Forecasting

arXiv:2607.00154v1 Announce Type: cross Abstract: Evolutionary neural architecture design for multivariate time-series forecasting remains underexplored, with most approaches relying on fixed Transfor

ext{Log}_ext{b}Quant: Quantizing Language Models in Logarithmic Space

arXiv:2607.01127v1 Announce Type: new Abstract: Quantization has become an invaluable tool to reduce memory requirements and inference speed of modern language models, in particular to make them avail

FedIA: Importance-Aware Aggregation for Domain-Robust Federated Graph Learning

arXiv:2509.18171v4 Announce Type: replace Abstract: Federated graph learning (FGL) is a natural paradigm for social-media user graphs, where language communities, regional markets, and service boundar

FlowPath: Learning Data-Driven Manifolds with Invertible Flows for Robust Irregularly-sampled Time Series Classification

arXiv:2511.10841v3 Announce Type: replace-cross Abstract: Modeling continuous-time dynamics from sparse and irregularly-sampled time series remains a fundamental challenge. Neural controlled different

FLYNN: Robust Neural Network for Robot Navigation using Fly Brain Topology

arXiv:2607.00025v1 Announce Type: cross Abstract: While deep learning models achieve state-of-the-art performance in complex tasks, they remain brittle when faced with new environments or sensory depr

Foundation Models vs. Radiomics for Lung Computed Tomography: A Benchmark of Feature Extractors, Classification Heads, and Segmentation Choices

arXiv:2607.01001v1 Announce Type: new Abstract: Radiomics is the established approach for CT-based lung cancer phenotyping, yet comparisons with foundation models rarely isolate contributions of featu

FRAME: Learning the Adaptation Domain with a Mixture of Fractional-Fourier Experts

arXiv:2607.00162v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) reparameterizes weight updates in a fixed basis: low-rank adapters operate in the spatial domain, while a recent

From Signals to Structure: How Memory Architecture Drives Language Emergence in LLM Agents

arXiv:2607.00233v1 Announce Type: new Abstract: How do two agents invent a shared language from scratch? In a Lewis signaling game, a sender and receiver must coordinate on a code using only their int

From 'Strings' to 'Things' for Personal Knowledge Graphs: Evaluating LLM Triple Extraction for Recommendation Systems

arXiv:2607.00003v1 Announce Type: cross Abstract: Personal Knowledge Graphs (PKGs) offer a privacy-preserving framework for modeling user preferences, yet constructing them from unstructured, decentra

From Structural Equation Modelling to Double Machine Learning: Robustness Analysis for Survey-Based Research

arXiv:2607.00512v1 Announce Type: new Abstract: Structural equation modelling (SEM) is widely used in survey-based business and information systems research to assess latent constructs and theory-driv

From Technical Metrics to User Perception: A User Study of a Multimodal Human-Robot Interaction System for Object Detection and Grasping

arXiv:2607.00530v1 Announce Type: cross Abstract: Improvements in the technical performance of human--robot interaction (HRI) systems do not automatically translate into differences that human users c

FUMO: Prior-Modulated Diffusion for Single Image Reflection Removal

arXiv:2603.19036v2 Announce Type: replace Abstract: Single image reflection removal (SIRR) is challenging in real scenes, where reflection strength varies spatially and reflection patterns are tightly

FusionFactory: Fusing LLM Capabilities with Multi-LLM Log Data

arXiv:2507.10540v3 Announce Type: replace Abstract: The rapid advancement of large language models (LLMs) has created a diverse landscape of models, each excelling at different tasks. This diversity d

GAIA: Geometry-Adaptive Operator Learning for Forward and Inverse Problems

arXiv:2607.01128v1 Announce Type: new Abstract: Operator learning for partial differential equations (PDEs) on arbitrary geometries builds fast neural surrogates for large-scale simulation. Although r

GameDevBench: Evaluating Agentic Capabilities Through Game Development

arXiv:2602.11103v2 Announce Type: replace Abstract: Despite rapid progress on coding agents, progress on their multimodal counterparts has lagged behind. A key challenge is the scarcity of evaluation

GEAR-Seg: A Grounded Explainable Agent for Reasoning Segmentation and Data Engine

arXiv:2607.00544v1 Announce Type: new Abstract: Reasoning segmentation requires localizing targets based on complex, implicit queries. Current end-to-end models typically entangle perception and deduc

Geometry-Aware Cross-Height Channel Knowledge Map Prediction for UAV-Assisted Communications With Uncertainty-Guided 3D Sensing

arXiv:2607.00887v1 Announce Type: new Abstract: Low-altitude Unmanned Aerial Vehicles (UAVs) often need to infer channel knowledge across a range of heights from only sparse observations collected at

GeoSearcher: Anchor-Guided Progressive Reasoning for Remote Sensing Visual Grounding with Process Supervision

arXiv:2607.01050v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have shown strong cross-modal understanding and coordinate generation abilities in visual grounding. How

Ghost in the Kernel: In-Context Learning with Efficient Transformers via Domain Generalization

arXiv:2607.00479v1 Announce Type: new Abstract: Transformer-based large models have demonstrated remarkable generalization abilities across different tasks by leveraging a context-aware attention modu

GKDT: General Keypoint Detection Transformer

arXiv:2607.00752v1 Announce Type: new Abstract: With the emergence of various pre-trained vision and language models, computer vision is shifting from narrow-domain to open-domain recognition. The con

GMO-E^2DIT: Grounded Multi-Operation Editing for E-Commerce Images

arXiv:2607.00920v1 Announce Type: new Abstract: Real-world e-commerce image editing often requires multiple, localized, and auditable operations rather than global restyling. This compositional nature

GPTKB v1.5: A Massive Knowledge Base for Exploring Factual LLM Knowledge

arXiv:2507.05740v2 Announce Type: replace Abstract: Language models are powerful artifacts, yet their factual knowledge is still poorly understood, and inaccessible to ad-hoc browsing and scalable sta

GRACE-RAG: Governed Retrieval Architecture for Canonical Evidence Synthesis, Enabling Lightweight Deployment in Closed-Domain Institutional Settings

arXiv:2607.00013v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are widely used in institutional question answering settings where responses must be grounded in authorit

Group-Equivariant Poincare Convolutional Networks

arXiv:2607.00556v1 Announce Type: cross Abstract: While recent advancements like the Poincare ResNet have demonstrated the potential of learning visual representations directly in hyperbolic space, th

GryphOne: Symbol-Aware Masked Diffusion for Structural Refinement in Offline Handwritten Mathematical Expression Recognition

arXiv:2602.03370v2 Announce Type: replace Abstract: Handwritten mathematical expression recognition (HMER) requires reasoning over diverse symbols and structures, yet autoregressive models struggle wi

GSRQ: Gain-Shape Residual Quantization for Sub-1-bit KV Cache

arXiv:2607.01065v1 Announce Type: new Abstract: The deployment of Large Language Models (LLMs) with extended context windows is increasingly constrained by the linear growth of Key-Value (KV) cache me

Histopathology Multi-modal Embedding for Pathology Composed Retrieval

arXiv:2502.07221v4 Announce Type: replace Abstract: To overcome the black-box nature of predictive AI and the hallucination risks of generative models, retrieval-based models offer an interpretable, e

Homogenization of ell_2-Adversarial Training in High-Dimensions: Exact Dynamics under Stochastic Gradient Descent

arXiv:2607.00207v1 Announce Type: cross Abstract: We develop a framework for analyzing the learning dynamics of ell_2-adversarial training of single-index models on Gaussian mixtures in the high-dimen

Identifying and Resolving Pitfalls of Knowledge-Based VQA Benchmarks: Auditing, Repairing, and Augmenting

arXiv:2607.00159v1 Announce Type: new Abstract: Knowledge-Based Visual Question Answering (KB-VQA) aims to evaluate whether Visual Language Models (VLMs) can retrieve, ground, and reason over external

Imprint: Online Memory Compression for Long-Horizon Egocentric QA

arXiv:2607.00696v1 Announce Type: new Abstract: Long-horizon egocentric question answering involves answering about events that have occurred hours or days in the past. This requires memory representa

Improving Sparse-View 3DGS Generalization via Flat Minima Optimization

arXiv:2607.00885v1 Announce Type: cross Abstract: Recent advances in neural rendering have established 3D Gaussian Splatting (3DGS) as a highly efficient representation for novel view synthesis, enabl

Information-Regularized Attention for Visual-Centric Reasoning

arXiv:2607.00434v1 Announce Type: new Abstract: Vision-language models (VLMs) have become a paradigm for multimodal learning, yet remain unstable due to object hallucination, weak visual grounding, an

Interpretable vs Learned Encoders for High-Cardinality Fraud Detection

arXiv:2607.00477v1 Announce Type: new Abstract: A total of seven categorical encoding methods were tested on the IEEE-CIS fraud benchmark dataset (590,540 records, 3.5% positives, 8 high-cardinality c

IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video

arXiv:2603.16432v3 Announce Type: replace Abstract: Unsupervised physical parameter estimation from video lacks a common benchmark: existing methods evaluate on non-overlapping synthetic data, the sol

Is One Layer Enough? Training A Single Transformer Layer Can Match Full-Parameter RL Training

arXiv:2607.01232v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a central component of post-training large language models (LLMs), yet little is understood about how RL adapta

KAGE-Bench: Fast Known-Axis Visual Generalization Evaluation for Reinforcement Learning

arXiv:2601.14232v2 Announce Type: replace-cross Abstract: Pixel-based reinforcement learning agents often fail under purely visual distribution shift even when latent dynamics and rewards are unchange

KGS-GCN: Kinematics-Driven Gaussian Splatting and Probabilistic Topology for Skeleton-Based Action Recognition

arXiv:2603.16943v2 Announce Type: replace-cross Abstract: Skeleton-based action recognition is widely applied in sensor-based systems, including human-computer interaction and intelligent surveillance

L-Proto: Language-Aware Episodic Prototypical Training for Multilingual Speaker Verification

arXiv:2606.17416v2 Announce Type: replace-cross Abstract: Multilingual speaker verification remains challenging because language-dependent acoustic variability causes speaker identity to become entang

Large language models replicate and predict human cooperation across experiments in game theory

arXiv:2511.04500v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as decision-making agents in high-stakes domains and as imitators of human behavior in the so

Learning Dexterous Manipulation Using Contact Wrench Guidance From Human Demonstration

arXiv:2607.00033v1 Announce Type: cross Abstract: Dexterous robot manipulation can benefit from the abundance of human demonstrations, but transferring such demonstrations to robot policies remains ch

Learning dynamical systems from noisy data with Weak-form Kernel Ridge Regression

arXiv:2607.00257v1 Announce Type: new Abstract: Accurate prediction of complex dynamical systems from noisy measurements remains a significant challenge in scientific computing. Kernel ridge regressio

Leveraging Phase Information to Boost Unrolled Network Learning for Image Deblurring

arXiv:2607.00251v1 Announce Type: cross Abstract: While most image deblurring techniques directly restore the spatial image variable, we propose an amplitude and phase decomposition recognizing the im