Search: “model-releases”

DriVerse: Navigation World Model for Driving Simulation via Multimodal Trajectory Prompting and Motion Alignment

model-releasesarxiv-cs-ro

arXiv:2504.18576v2 Announce Type: replace Abstract: This paper presents DriVerse, a generative model for simulating navigation-driven driving scenes from a single image and a future trajectory. Previo

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DyABD: The Abdominal Muscle Segmentation in Dynamic MRI Benchmark

DGX agent

arXiv:2604.23187v1 Announce Type: cross Abstract: This work introduces DyABD, a novel and complex benchmark dataset of dynamic abdominal MRIs from patients with abdominal hernias and associated high q

model-releasesarxiv-cs-ai

28 Apr 2026

DynProto: Dynamic Prototype Evolution for Out-of-Distribution Detection

arXiv:2604.23729v1 Announce Type: new Abstract: Recent studies show that using potential out-of-distribution (OOD) labels from large corpora as auxiliary information can improve OOD detection in visio

EAGLE: Expert-Augmented Attention Guidance for Tuning-Free Industrial Anomaly Detection in Multimodal Large Language Models

arXiv:2602.17419v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) can enrich industrial anomaly detection with semantic descriptions and anomaly reasoning, but they still la

Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity Recognition

arXiv:2203.04153v2 Announce Type: replace Abstract: Sensor-based human activity recognition (HAR) is a paramount technology in the Internet of Things services. HAR using representation learning, which

EgoDyn-Bench: Evaluating Ego-Motion Understanding in Vision-Centric Foundation Models for Autonomous Driving

arXiv:2604.22851v1 Announce Type: cross Abstract: While Vision-Language Models (VLMs) have advanced highlevel reasoning in autonomous driving, their ability to ground this reasoning in the underlying

ELSA: Exact Linear-Scan Attention for Fast and Memory-Light Vision Transformers

arXiv:2604.23798v1 Announce Type: cross Abstract: Existing attention accelerators often trade exact softmax semantics, depend on fused Tensor Core kernels, or incur sequential depth that limits FP32 t

EMCompress: Video-LLMs with Endomorphic Multimodal Compression

arXiv:2508.21094v3 Announce Type: replace Abstract: Video-LLMs face a fundamental tension in long-video reasoning: static, sparse frame sampling either dilutes evidence across task-irrelevant segments

EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models

arXiv:2502.04424v4 Announce Type: replace-cross Abstract: With the integration of multimodal large language models (MLLMs) into robotic systems and AI applications, embedding emotional intelligence (E

EmoTrans: A Benchmark for Understanding, Reasoning, and Predicting Emotion Transitions in Multimodal LLMs

arXiv:2604.23348v1 Announce Type: cross Abstract: Recent multimodal large language models (MLLMs) have shown strong capabilities in perception, reasoning, and generation, and are increasingly used in

Empirical Ablation and Ensemble Optimization of a Convolutional Neural Network for CIFAR-10 Classification

arXiv:2604.23861v1 Announce Type: cross Abstract: Convolutional neural networks (CNNs) remain a central approach in image classification, but their performance depends strongly on architectural and tr

End-to-End Learning for Partially-Observed Time Series with PyPOTS

arXiv:2604.24041v1 Announce Type: cross Abstract: Partially-observed time series (POTS) is ubiquitous in real-world applications, yet most existing toolchains separate missing-value handling from down

Energy-Arena: A Dynamic Benchmark for Operational Energy Forecasting

model-releasesarxiv-cs-lg

arXiv:2604.24705v1 Announce Type: cross Abstract: Energy forecasting research faces a persistent comparability gap that makes it difficult to measure consistent progress over time. Reported accuracy g

EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce

arXiv:2604.23993v1 Announce Type: cross Abstract: Product mapping, the task of deciding whether two e-commerce listings refer to the same product, is a core problem for price monitoring and channel vi

Estimating Dense-Packed Zone Height in Liquid-Liquid Separation: A Physics-Informed Neural Network Approach

model-releasesarxiv-cs-lg

arXiv:2601.18399v2 Announce Type: replace Abstract: Separating liquid-liquid dispersions in gravity settlers is critical in chemical, pharmaceutical, and recycling processes. The dense-packed zone hei

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

arXiv:2604.23466v1 Announce Type: cross Abstract: NVIDIA's CUDA Tile (CuTile) introduces a Python-based, tile-centric abstraction for GPU kernel development that aims to simplify programming while ret

Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards

arXiv:2604.23341v1 Announce Type: cross Abstract: The deployment of Large Language Models (LLMs) as assistants in electric grid operations promises to streamline compliance and decision-making but exp

Evaluating Large Language Models on Computer Science University Exams in Data Structures

arXiv:2604.23347v1 Announce Type: new Abstract: We present a comprehensive evaluation of Large Language Models (LLMs) on Computer Science (CS) Data Structure examination questions. Our work introduces

Evaluating Temporal Consistency in Multi-Turn Language Models

arXiv:2604.23051v1 Announce Type: new Abstract: Language models are increasingly deployed in interactive settings where users reason about facts over time rather than in isolation. In such scenarios,

Evaluating the Search Agent in a Parallel World

arXiv:2603.04751v2 Announce Type: replace Abstract: Integrating web search tools has significantly extended the capability of LLMs to address open-world, real-time, and long-tail problems. However, ev

Evaluating whether AI models would sabotage AI safety research

arXiv:2604.24618v1 Announce Type: new Abstract: We evaluate the propensity of frontier models to sabotage or refuse to assist with safety research when deployed as AI research agents within a frontier

Event-based SLAM Benchmark for High-Speed Maneuvers

model-releasesarxiv-cs-ro

arXiv:2604.24033v1 Announce Type: new Abstract: Event-based cameras are bio-inspired sensors with pixels that independently and asynchronously respond to brightness changes at microsecond resolution,

Evolve: A Persistent Knowledge Lifecycle for Small Language Models

arXiv:2604.23424v1 Announce Type: cross Abstract: Evolve pairs a small local language model with a persistent, teacher-compiled knowledge store -- refined through sleep consolidation and usage-driven

EX-FIQA: Leveraging Intermediate Early eXit Representations from Vision Transformers for Face Image Quality Assessment

arXiv:2604.22842v1 Announce Type: new Abstract: Face Image Quality Assessment is crucial for reliable face recognition systems, yet existing Vision Transformer-based approaches rely exclusively on fin

EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain

arXiv:2406.14075v2 Announce Type: replace Abstract: It is crucial to understand a specific domain by events. Extensive event extraction research has been conducted in many domains such as news, financ

Exploring Hierarchical Consistency and Unbiased Objectness for Open-Vocabulary Object Detection

arXiv:2604.23344v1 Announce Type: new Abstract: Conventional object detectors typically operate under a closed-set assumption, limiting recognition to a predefined set of base classes seen during trai

Exploring the Secondary Risks of Large Language Models

arXiv:2506.12382v5 Announce Type: replace-cross Abstract: Ensuring the safety and alignment of Large Language Models is a significant challenge with their growing integration into critical application

FAIR_XAI: Improving Multimodal Foundation Model Fairness via Explainability for Wellbeing Assessment

arXiv:2604.23786v1 Announce Type: new Abstract: In recent years, the integration of multimodal machine learning in wellbeing assessment has offered transformative potential for monitoring mental healt

FastAT Benchmark: A Comprehensive Framework for Fair Evaluation of Fast Adversarial Training Methods

arXiv:2604.22853v1 Announce Type: new Abstract: Fast Adversarial Training (FastAT) seeks to achieve adversarial robustness at a fraction of the computational cost incurred by standard multi-step metho

FDIM: A Feature-distance-based Generic Video Quality Metric for Versatile Codecs

arXiv:2604.24123v1 Announce Type: new Abstract: Video technology is advancing toward Ultra High Definition (UHD) and High Dynamic Range (HDR), which intensifies the need for higher compression efficie

FOCUS: Fused Observation of Channels for Unveiling Spectra

arXiv:2507.14787v2 Announce Type: replace-cross Abstract: Hyperspectral imaging (HSI) captures hundreds of narrow, contiguous wavelength bands, making it a powerful tool in biology, agriculture, and e

For-Value: Efficient Forward-Only Data Valuation for finetuning LLMs and VLMs

arXiv:2508.10180v3 Announce Type: replace Abstract: Data valuation is essential for enhancing the transparency and accountability of large language models (LLMs) and vision-language models (VLMs). How

Forecasting Commencing Enrolments Under Data Sparsity: A Zero-Shot Time Series Foundation Models Framework for Higher Education Planning

arXiv:2602.12120v3 Announce Type: replace Abstract: Effective resource allocation in higher education depends on reliable enrolment forecasts, yet institutional planners frequently face data series di

Franca: Nested Matryoshka Clustering for Scalable Visual Representation Learning

arXiv:2507.14137v4 Announce Type: replace Abstract: We present Franca (pronounced Fran-ka): free one; the first fully open-source (data, code, weights) vision foundation model that matches and in many

FreqFormer: Hierarchical Frequency-Domain Attention with Adaptive Spectral Routing for Long-Sequence Video Diffusion Transformers

arXiv:2604.22808v1 Announce Type: cross Abstract: Long-sequence video diffusion transformers hit a quadratic self-attention cost that dominates runtime and memory for very long token sequences. Most e

From Pixels to Explanations: Interpretable Diabetic Retinopathy Grading with CNN-Transformer Ensembles, Visual Explainability and Vision-Language Models

arXiv:2604.23079v1 Announce Type: cross Abstract: The quality of diabetic retinopathy (DR) screening relies on the ability to correctly grade severity; however, many deep-learning (DL) classifiers can

Game-Time: Evaluating Temporal Dynamics in Spoken Language Models

arXiv:2509.26388v3 Announce Type: replace-cross Abstract: Conversational Spoken Language Models (SLMs) are emerging as a promising paradigm for real-time speech interaction. However, their capacity of

GAMMAF: A Common Framework for Graph-Based Anomaly Monitoring Benchmarking in LLM Multi-Agent Systems

arXiv:2604.24477v1 Announce Type: cross Abstract: The rapid integration of Large Language Models (LLMs) into Multi-Agent Systems (MAS) has significantly enhanced their collaborative problem-solving ca

GCP: Guarded Collaborative Perception with Spatial-Temporal Aware Malicious Agent Detection

arXiv:2501.02450v2 Announce Type: replace Abstract: Collaborative perception significantly enhances autonomous driving safety by extending each vehicle's perception range through message sharing among

Generalising maximum mean discrepancy: kernelised functional Bregman divergences

arXiv:2604.24047v1 Announce Type: cross Abstract: Bregman divergences play a pivotal role in statistics, machine learning and computational information geometry. Particularly in the context of machine

Generating Place-Based Compromises Between Two Points of View

arXiv:2604.24536v1 Announce Type: new Abstract: Large Language Models (LLMs) excel academically but struggle with social intelligence tasks, such as creating good compromises. In this paper, we presen

Geometry-Aware Offline-to-Online Learning in Linear Contextual Bandits

model-releasesarxiv-cs-lg

arXiv:2604.24016v1 Announce Type: new Abstract: We study offline-to-online learning in linear contextual bandits with biased offline regression data: the offline parameter need not match the online on

Global Context or Local Detail? Adaptive Visual Grounding for Hallucination Mitigation

arXiv:2604.24396v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are frequently undermined by object hallucination--generating content that contradicts visual reality--due to an over-re

GoClick: Lightweight Element Grounding Model for Autonomous GUI Interaction

arXiv:2604.23941v1 Announce Type: new Abstract: Graphical User Interface (GUI) element grounding (precisely locating elements on screenshots based on natural language instructions) is fundamental for

GradMAP: Gradient-Based Multi-Agent Proximal Learning for Grid-Edge Flexibility

arXiv:2604.24549v1 Announce Type: cross Abstract: Coordinating large populations of grid-edge devices requires learning methods that remain fully decentralised in deployment while still respecting thr

Graph-augmented Segmentation of Complex Shapes in Laser Powder bed Fusion for Enhanced In Situ Inspection

arXiv:2604.24234v1 Announce Type: new Abstract: The technological maturity of in situ inspection and monitoring methods in additive manufacturing is steadily increasing, enabling more efficient and pr

Graph Memory Transformer (GMT)

arXiv:2604.23862v1 Announce Type: cross Abstract: We investigate whether the Feed-Forward Network (FFN) sublayer in a decoder-only transformer can be replaced by an explicit learned memory graph while

GraphPlanner: Graph Memory-Augmented Agentic Routing for Multi-Agent LLMs

arXiv:2604.23626v1 Announce Type: new Abstract: LLM routing has achieved promising results in integrating the strengths of diverse models while balancing efficiency and performance. However, to suppor