Search: “model-releases”

Diffusion-Based sRGB Real Noise Generation via Prompt-Driven Noise Representation Learning

arXiv:2603.04870v2 Announce Type: replace Abstract: Denoising in the sRGB image space is challenging due to large noise variability. Although end-to-end methods perform well, their effectiveness in re

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Diffusion-Based Stochastic Operator Networks for Uncertainty Quantification in Stochastic Partial Differential Equations

DGX agent

arXiv:2605.17107v1 Announce Type: cross Abstract: We introduce a novel framework for uncertainty quantification of solution operators associated with stochastic partial differential equations (SPDEs).

model-releasesarxiv-cs-lg

19 May 2026

DisasterVQA: A Visual Question Answering Benchmark Dataset for Disaster Scenes

arXiv:2601.13839v2 Announce Type: replace Abstract: Social media imagery provides a low-latency source of situational information during natural and human-induced disasters, enabling rapid damage asse

Disentangled Latent Dynamics Manifold Fusion for Solving Parameterized PDEs

arXiv:2603.12676v2 Announce Type: replace Abstract: Generalizing neural surrogate models across different PDE parameters remains difficult because changes in PDE coefficients often make learning harde

Disentangling Ambiguity from Instability in Large Language Models: A Clinical Text-to-SQL Case Study

arXiv:2602.12015v2 Announce Type: replace Abstract: Deploying large language models for clinical Text-to-SQL requires distinguishing two qualitatively different causes of output diversity: (i) input a

Distributed Perceptron under Bounded Staleness, Partial Participation, and Noisy Communication

arXiv:2601.10705v3 Announce Type: replace Abstract: We study a semi-asynchronous client-server perceptron trained via iterative parameter mixing (IPM-style averaging): clients run local perceptron upd

Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation

arXiv:2502.02463v3 Announce Type: replace-cross Abstract: While Bayesian inference provides a principled framework for reasoning under uncertainty, its widespread adoption is limited by the intractabi

Do Vision-Language-Models show human-like logical problem-solving capability in point and click puzzle games?

arXiv:2605.11223v2 Announce Type: replace Abstract: Vision-Language(-Action) Models (VLMs) are increasingly applied to interactive environments, yet existing benchmarks often overlook the complex phys

DocOS: Towards Proactive Document-Guided Actions in GUI Agents

arXiv:2605.18048v1 Announce Type: new Abstract: While Graphical User Interface (GUI) agents have shown promising performance in automated device interaction, they primarily depend on static parametric

DocReward: A Document Reward Model for Structuring and Stylizing

arXiv:2510.11391v3 Announce Type: replace-cross Abstract: Recent agentic workflows automate professional document generation but focus narrowly on textual quality, overlooking structural and stylistic

Does Weight Decay Enhance Training Stability?

arXiv:2605.16622v1 Announce Type: new Abstract: In modern deep learning, weight decay is often credited with 'stabilizing' training dynamics, diverging from its classical role as a static regularizati

DP-SelFT: Differentially Private Selective Fine-Tuning for Large Language Models

arXiv:2605.17432v1 Announce Type: new Abstract: Large language models (LLMs) are commonly adapted to downstream tasks through fine-tuning, but fine-tuning data often contains sensitive information tha

DriveSafe: A Framework for Risk Detection and Safety Suggestions in Driving Scenarios

arXiv:2605.16892v1 Announce Type: cross Abstract: Comprehensive situational awareness is essential for autonomous vehicles operating in safety-critical environments, as it enables the identification a

DriveSafer: End-to-End Autonomous Driving with Safety Guidance

arXiv:2605.16737v1 Announce Type: cross Abstract: End-to-End (E2E) autonomous driving models have shown growing capability in recent years, with performance improving on increasingly challenging bench

DSAA: Dual-Stage Attribute Activation for Fine-grained Open Vocabulary Detection

arXiv:2605.18023v1 Announce Type: new Abstract: Open-Vocabulary Object Detection (OVD) models break the limitations of closed-set detection, enabling the iden- tification of unseen categories through

Dynamic Elliptical Graph Factor Models via Riemannian Optimization with Geodesic Temporal Regularization

arXiv:2605.18316v1 Announce Type: new Abstract: Inferring time-varying graph structures from high-dimensional nodal observations is a fundamental problem arising in neuroscience, finance, climatology,

DynMuon: A Dynamic Spectral Shaping View of Muon

arXiv:2605.17109v1 Announce Type: cross Abstract: In recent years, Muon has emerged as the dominant method for training large language models, and transformers more broadly. The essential difference,

Easier to Judge than to Find: Predicting In-Context Learning Success for Demonstration Selection

arXiv:2605.18512v1 Announce Type: new Abstract: In-context learning (ICL) is highly sensitive to which demonstrations appear in the prompt, but selecting them is expensive because the space of possibl

Efficient Lookahead Encoding and Abstracted Width for Learning General Policies in Classical Planning

arXiv:2605.18674v1 Announce Type: new Abstract: Generalized planning aims to learn policies that generalize across collections of instances within a classical planning domain. Recent Graph Neural Netw

EfficientTDMPC: Improved MPC Objectives for Sample-Efficient Continuous Control

arXiv:2605.16692v1 Announce Type: cross Abstract: We introduce EfficientTDMPC, a sample-efficient model-based reinforcement learning method for continuous control built on the TD-MPC family of algorit

Effort as Ceiling, Not Dial: Reasoning Budget Does Not Modulate Cognitive Cost Alignment Between Humans and Large Reasoning Models

arXiv:2605.16938v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) generate chain-of-thought traces whose length tracks human reaction times across cognitive tasks, but recent debate ques

EgoExoMem: Cross-View Memory Reasoning over Synchronized Egocentric and Exocentric Videos

arXiv:2605.18734v1 Announce Type: new Abstract: Egocentric memory is widely used in embodied intelligence, but it may be insufficient for comprehensive spatial-temporal reasoning. Inspired by human re

EgoIntrospect: An Egocentric Dataset and Benchmark for User-Centric Internal State Reasoning

arXiv:2605.17262v1 Announce Type: new Abstract: Despite extensive efforts on egocentric video datasets and benchmarks, understanding users' internal states, which is crucial for enabling seamless AI a

Embodied Task Planning via Graph-Informed Action Generation with Large Language Models

arXiv:2601.21841v3 Announce Type: replace Abstract: While Large Language Models (LLMs) have demonstrated strong zero-shot reasoning capabilities, their deployment as embodied agents still faces fundam

EmoMind: Decoding Affective Captions from Human Brain fMRI

arXiv:2605.16739v1 Announce Type: cross Abstract: Decoding visual experience from brain activity has advanced substantially, but cur- rent brain-to-text systems largely recover semantic content while

Employing Vision-Language Models for Face Image Quality Assessment

arXiv:2605.17489v1 Announce Type: new Abstract: Face Image Quality Assessment (FIQA) is a crucial control step in biometric pipelines. It ensures only reliable samples are processed to maintain system

EndoCogniAgent: Closed-Loop Agentic Reasoning with Self-Consistency Validation for Endoscopic Diagnosis

arXiv:2508.07292v3 Announce Type: replace Abstract: Endoscopic diagnosis is an iterative process in which clinicians progressively acquire, compare, and verify local visual evidence before reaching a

Enhancing Metacognitive AI: Knowledge-Graph Population with Graph-Theoretic LLM Enrichment

arXiv:2605.16676v1 Announce Type: new Abstract: Metacognition-the ability to monitor one's own knowledge state, spot gaps, and autonomously fill them--remains largely absent from modern AI. Here, we p

Ensembling Tabular Foundation Models - A Diversity Ceiling And A Calibration Trap

arXiv:2605.18696v1 Announce Type: cross Abstract: Tabular foundation models (TFMs) now match or beat tuned gradient-boosted trees on a growing fraction of tabular tasks, but no single TFM wins on ever

EPIC-Bench: A Perception-Centric Benchmark for Fine-Grained Embodied Visual Grounding in Vision-Language Models

arXiv:2605.17070v1 Announce Type: new Abstract: While large vision-language models (VLMs) are increasingly adopted as the perceptual backbone for embodied agents, existing benchmarks often rely on que

Episodic-Semantic Memory Architecture for Long-Horizon Scientific Agents

arXiv:2605.17625v1 Announce Type: new Abstract: As Large Language Models (LLMs) evolve into persistent scientific collaborators, context window saturation has emerged as a critical bottleneck. Scienti

Error-Decomposed Class-Conditional Fusion for Statistically Guaranteed Hard-Category Robust Perception

arXiv:2605.17591v1 Announce Type: new Abstract: Aggregate object detection metrics inherently mask catastrophic and repeatable failures in operationally critical, long-tail minority classes. This pape

ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop

arXiv:2605.18746v1 Announce Type: cross Abstract: Spatial intelligence unfolds through a perception-action loop: agents act to acquire observations, and reason about how observations vary as a functio

Evaluating Cognitive Age Alignment in Interactive AI Agents

arXiv:2605.17894v1 Announce Type: new Abstract: While agentic AI and its core multimodal large language models (MLLMs) have demonstrated remarkable promise in language and visual reasoning across doma

Evaluating Deep Research Agents on Expert Consulting Work: A Benchmark with Verifiers, Rubrics, and Cognitive Traps

arXiv:2605.17554v1 Announce Type: new Abstract: Frontier deep research agents (DRAs) plan a research task, synthesize across documents, and return a structured deliverable on demand. They are being de

Evidence-Grounded Frontier Mapping and Agentic Hypothesis Generation in Nanomedicine

arXiv:2605.18144v1 Announce Type: new Abstract: Nanomedicine research spans delivery chemistry, immunology, imaging, biomaterials, and disease-specific translational science, yet its conceptual design

EvilGenie: A Reward Hacking Benchmark

arXiv:2511.21654v2 Announce Type: replace Abstract: We introduce EvilGenie, a benchmark for reward hacking in programming settings. We source problems from LiveCodeBench and create an environment in w

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory

arXiv:2511.20857v2 Announce Type: replace-cross Abstract: Statefulness is essential for large language model (LLM) agents to perform long-term planning and problem-solving. This makes memory a critica

Evolve the Method, Not the Prompts: Evolutionary Synthesis of Jailbreak Attacks on LLMs

arXiv:2511.12710v2 Announce Type: replace Abstract: Automated red teaming frameworks for Large Language Models (LLMs) have become increasingly sophisticated, yet many still formulate attack optimizati

EvoMemBench: Benchmarking Agent Memory from a Self-Evolving Perspective

arXiv:2605.18421v1 Announce Type: cross Abstract: Recent benchmarks for Large Language Model (LLM) agents mainly evaluate reasoning, planning, and execution. However, memory is also essential for agen

EvoQRE: Modeling Bounded Rationality in Safety-Critical Traffic Simulation via Evolutionary Quantal Response Equilibrium

model-releasesarxiv-cs-ro

arXiv:2601.05653v2 Announce Type: replace Abstract: Existing traffic simulation frameworks for autonomous vehicles typically rely on imitation learning or game-theoretic approaches that solve for Nash

Expandable, Compressible, Mineable: Open-World Thermal Image Restoration

arXiv:2605.16967v1 Announce Type: new Abstract: In open-world settings, thermal infrared (TIR) image degradations continuously emerge and evolve, while most existing all-in-one restoration methods are

Experimentally validated quantum-secure federated learning over a multi-user quantum network

arXiv:2501.12709v2 Announce Type: replace-cross Abstract: Federated learning enables decentralized, privacy-preserving training but remains vulnerable to privacy leakage in the quantum era. Quantum fe

Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons

arXiv:2605.16975v1 Announce Type: cross Abstract: Electrocardiogram (ECG) foundation models pretrained on typical diagnostic 10-second ECG segments, have demonstrated strong transferability across a r

extit{Don't Guess, Just Ask}: Resolving Ambiguity in Referring Segmentation via Multi-turn Clarification

arXiv:2605.17531v1 Announce Type: new Abstract: Referring segmentation aims to segment the target objects in images or videos based on the textual query. Despite remarkable progress over the past year

extsc{PrivScope}: Task-scoped Disclosure Control for Hybrid Agentic Systems

arXiv:2605.16630v1 Announce Type: cross Abstract: Hybrid local--cloud agents enrich user requests with context from persistent working state before delegating capability-intensive subtasks to a cloud

exttt{SynC}: Synergistic Boosting of Structure and Representation for Deep Graph Clustering

arXiv:2406.15797v2 Announce Type: replace-cross Abstract: Employing graph neural networks (GNNs) for graph clustering has shown promising results in deep graph clustering. However, existing methods di

FAM-HRI: Foundation-Model Assisted Multi-Modal Human-Robot Interaction Combining Gaze and Speech

model-releasesarxiv-cs-ro

arXiv:2503.16492v3 Announce Type: replace-cross Abstract: ffective Human-Robot Interaction (HRI) is crucial for enhancing accessibility and usability in real-world robotics applications. However, exis