Search: “framework”

Scaling Sequence-to-Sequence Generative Neural Rendering

arXiv:2510.04236v3 Announce Type: replace Abstract: We present Kaleido, a family of generative models designed for photorealistic, unified object- and scene-level neural rendering. Kaleido operates on

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Selector-Guided Autonomous Curriculum for One-Shot Reinforcement Learning from Verifiable Rewards

DGX agent

arXiv:2605.01823v1 Announce Type: new Abstract: Recently, Reinforcement Learning from Verifiable Rewards (RLVR) has been established as a highly effective technique for augmenting the math reasoning s

model-releasesarxiv-cs-lg

5 May 2026

Self-Supervised Spatial And Zero-Shot Angular Super-Resolution by Spatial-Angular Implicit Representation For Rotating-View SNR-Efficient Diffusion MRI

arXiv:2605.02575v1 Announce Type: new Abstract: Rotating-view thick-slice acquisition is highly SNR-efficient for mesoscale diffusion MRI (dMRI) but requires numerous rotating views to satisfy Nyquist

Semantic Context-aware mOdality fUsion Transformer (SCOUT): A Context-Aware Multimodal Transformer for Concept-Grounded Pathology Report Generation

arXiv:2605.01144v1 Announce Type: new Abstract: Whole-slide images (WSIs) present a fundamental challenge for computational pathology due to their extreme resolution, multi-scale heterogeneity, and th

local-aiarxiv-cs-cv

Sentra-Guard: A Real-Time Multilingual Defense Against Adversarial LLM Prompts

arXiv:2510.22628v2 Announce Type: replace-cross Abstract: This paper presents a real-time modular defense system named Sentra-Guard. The system detects and mitigates jailbreak and prompt injection att

safetyarxiv-cs-ai

Agents

Sound Source Localization for Spatial Mapping of Surgical Actions in Dynamic Scenes

arXiv:2510.24332v3 Announce Type: replace-cross Abstract: Purpose: Surgical scene understanding is key to advancing computer-aided and intelligent surgical systems. Current approaches predominantly re

agentsarxiv-cs-cv

TCDA: Thread-Constrained Discourse-Aware Modeling for Conversational Sentiment Quadruple Analysis

arXiv:2605.01717v1 Announce Type: new Abstract: Conversational Aspect-based Sentiment Quadruple Analysis (DiaASQ) needs to capture the complex interrelationships in multiple rounds of dialogues. Exist

Training-Free Time Series Classification via In-Context Reasoning with LLM Agents

model-releasesarxiv-cs-ai

arXiv:2510.05950v2 Announce Type: replace Abstract: Time series classification (TSC) spans diverse application scenarios, yet labeled data are often scarce, making task-specific training costly and in

Unifying Deep Stochastic Processes for Image Enhancement

arXiv:2605.01568v1 Announce Type: new Abstract: Deep stochastic processes have recently become a central paradigm for image enhancement, with many methods explicitly conditioning the stochastic trajec

Unsupervised Machine Learning for Detecting Structural Anomalies in European Regional Statistics

arXiv:2605.02884v1 Announce Type: new Abstract: Ensuring the coherence of regional socio-economic statistics is a central task for national statistical institutes. Traditional validation tools, such a

safetyarxiv-cs-lg

Agents

Verbal-R3: Verbal Reranker as the Missing Bridge between Retrieval and Reasoning

arXiv:2605.01399v1 Announce Type: new Abstract: The conventional Retrieval-Augmented Generation (RAG) paradigm of injecting raw retrieved texts into the Large Language Model (LLM)'s context often resu

agentsarxiv-cs-cl

VERGE: Formal Refinement and Guidance Engine for Verifiable LLM Reasoning

arXiv:2601.20055v2 Announce Type: replace Abstract: Despite the syntactic fluency of Large Language Models (LLMs), ensuring their logical correctness in high-stakes domains remains a fundamental chall

local-aiarxiv-cs-cl

Virtual Scanning for NSCLC Histology: Investigating the Discriminatory Power of Synthetic PET

arXiv:2605.02746v1 Announce Type: new Abstract: Accurate histological differentiation between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) is critical for personalized treatment in non-small

VISTA: Video Interaction Spatio-Temporal Analysis Benchmark

arXiv:2605.01391v1 Announce Type: new Abstract: Existing benchmarks for Vision-Language Models (VLMs) primarily evaluate spatio-temporal understanding on simple single-action videos, closed attribute

WILD SAM: A Simulated-and-Real Data Augmentation for Autonomous Driving Perception under Challenging Weather

arXiv:2605.01081v1 Announce Type: new Abstract: The performance of state-of-the-art object detectors degrades significantly under adverse weather, causing a safety-critical domain shift problem for au

Zero-Shot Interpretable Image Steganalysis for Invertible Image Hiding

arXiv:2605.01331v1 Announce Type: new Abstract: Image steganalysis, which aims at detecting secret information concealed within images, has become a critical countermeasure for assessing the security

Agent Capsules: Quality-Gated Granularity Control for Multi-Agent LLM Pipelines

arXiv:2605.00410v1 Announce Type: new Abstract: A multi-agent pipeline with N agents typically issues N LLM calls per run. Merging agents into fewer calls (compound execution) promises token savings,

safetyarxiv-cs-cl

AIDA-ReID: Adaptive Intermediate Domain Adaptation for Generalizable and Source-Free Person Re-Identification

arXiv:2605.00111v1 Announce Type: new Abstract: Person re-identification (Re-ID) aims to match images of the same individual across non-overlapping camera views and remains challenging due to domain s

AlphaInventory: Evolving White-Box Inventory Policies via Large Language Models with Deployment Guarantees

model-releasesarxiv-cs-lg

arXiv:2605.00369v1 Announce Type: new Abstract: We study how large language models can be used to evolve inventory policies in online, non-stationary environments. Our work is motivated by recent adva

Augmented Lagrangian Multiplier Network for State-wise Safety in Reinforcement Learning

arXiv:2605.00667v1 Announce Type: new Abstract: Safety is a primary challenge in real-world reinforcement learning (RL). Formulating safety requirements as state-wise constraints has become a prominen

safetyarxiv-cs-lg

Beyond Prompt-Induced Lies: Investigating LLM Deception on Benign Prompts

arXiv:2508.06361v4 Announce Type: replace Abstract: Large Language Models (LLMs) are widely deployed in reasoning, planning, and decision-making tasks, making their trustworthiness critical. A signifi

safetyarxiv-cs-lg

Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking

arXiv:2605.00348v1 Announce Type: cross Abstract: Recent multi-bit watermarking methods for large language models (LLMs) prioritize capacity over reliability, often conflating decoding with detection.

local-aiarxiv-cs-cl

Bring Your Own Prompts: Use-Case-Specific Bias and Fairness Evaluation for LLMs

arXiv:2407.10853v5 Announce Type: replace Abstract: Bias and fairness risks in Large Language Models (LLMs) vary substantially across deployment contexts, yet existing approaches lack systematic guida

Agents

Causality-enhanced Decision-Making for Autonomous Mobile Robots in Dynamic Environments

arXiv:2504.11901v5 Announce Type: replace Abstract: The growing integration of robots in shared environments-such as warehouses, shopping centres, and hospitals-demands a deep understanding of the und

agentsarxiv-cs-ro

Comparative Analysis of Polygon-Based and Global Machine Learning Models for Bus Occupancy Prediction

arXiv:2605.00083v1 Announce Type: new Abstract: Accurate forecasting of bus ridership (passengers numbers) is crucial for efficient management and optimization of public transport systems. Traditional

local-aiarxiv-cs-lg

DMDSC: A Dynamic-Margin Deep Simplex Classifier for Open-Set Recognition on Medical Image Datasets

arXiv:2605.00675v1 Announce Type: new Abstract: Medical imaging datasets are often characterized by extreme class imbalances, where rare pathologies are significantly underrepresented compared to comm

Dynamic-TD3: A Novel Algorithm for UAV Path Planning with Dynamic Obstacle Trajectory Prediction

arXiv:2605.00059v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) finds extensive application in autonomous drone navigation within complex, high-risk environments. However, its practi

safetyarxiv-cs-ro

Applications

FieryGS: In-the-Wild Fire Synthesis with Physics-Integrated Gaussian Splatting

arXiv:2605.00177v1 Announce Type: cross Abstract: We consider the problem of synthesizing photorealistic, physically plausible combustion effects in in-the-wild 3D scenes. Traditional CFD and graphics

applicationsarxiv-cs-cv

FreeRet: MLLMs as Training-Free Retrievers

arXiv:2509.24621v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) are emerging as versatile foundations for mixed-modality retrieval. Yet, they often require heavy post-hoc

safetyarxiv-cs-cv

Applications

GOR-IS: 3D Gaussian Object Removal in the Intrinsic Space

arXiv:2605.00498v1 Announce Type: new Abstract: Recent advances in Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have made it standard practice to reconstruct 3D scenes from multi-vie

applicationsarxiv-cs-cv

LandSegmenter: Towards a Flexible Foundation Model for Land Use and Land Cover Mapping

arXiv:2511.08156v2 Announce Type: replace Abstract: Land Use and Land Cover (LULC) mapping is a fundamental task in Earth Observation (EO). However, current LULC models are typically developed for a s

Learning from Supervision with Semantic and Episodic Memory: A Reflective Approach to Agent Adaptation

arXiv:2510.19897v2 Announce Type: replace Abstract: We investigate how agents built on pretrained large language models (LLMs) can learn target classification functions from labeled examples without p

Learning from the Unseen: Generative Data Augmentation for Geometric-Semantic Accident Anticipation

arXiv:2605.00051v1 Announce Type: new Abstract: Anticipating traffic accidents is a critical yet unresolved problem for autonomous driving, hindered by the inherent complexity of modeling interactions

Learning Multimodal Energy-Based Model with Multimodal Variational Auto-Encoder via MCMC Revision

arXiv:2605.00644v1 Announce Type: new Abstract: Energy-based models (EBMs) are a flexible class of deep generative models and are well-suited to capture complex dependencies in multimodal data. Howeve

Learning the Helmholtz equation operator with DeepONet for non-parametric 2D geometries

arXiv:2605.00760v1 Announce Type: new Abstract: This paper deals with solving the 2D Helmholtz equation on non-parametric domains, leveraging a physics-informed neural operator network based on the De

local-aiarxiv-cs-lg

Leveraging Vision-Language Models as Weak Annotators in Active Learning

arXiv:2605.00480v1 Announce Type: new Abstract: Active learning aims to reduce annotation cost by selectively querying informative samples for supervision under a limited labeling budget. In this work

MemoryBench: A Benchmark for Memory and Continual Learning in LLM Systems

model-releasesarxiv-cs-lg

arXiv:2510.17281v5 Announce Type: replace Abstract: Scaling up data, parameters, and test-time computation has been the mainstream methods to improve LLM systems (LLMsys), but their upper bounds are a

ML-Agent: Reinforcing LLM Agents for Autonomous Machine Learning Engineering

arXiv:2505.23723v2 Announce Type: replace Abstract: The emergence of large language model (LLM)-based agents has significantly advanced the development of autonomous machine learning (ML) engineering.

MoDAl: Self-Supervised Neural Modality Discovery via Decorrelation for Speech Neuroprosthesis

arXiv:2605.00025v1 Announce Type: cross Abstract: Speech neuroprosthesis systems decode intended speech from neural activity in the absence of audible output, offering a path to restoring communicatio

Modeling Subjective Urban Perception with Human Gaze

arXiv:2605.00764v1 Announce Type: new Abstract: Urban perception describes how people subjectively evaluate urban environments, shaping how cities are experienced and understood. Existing computationa

Applications

Network Digital Untwinning: Towards Backward Optimization of Digital Twins

arXiv:2605.00169v1 Announce Type: cross Abstract: Network digital twins (NDTs) are transforming network management by offering precise virtual replicas of physical network systems. However, their reli

applicationsarxiv-cs-lg

Observable Performance Does Not Fully Reflect System Organization: A Multi-Level Analysis of Gait Dynamics Under Occlusal Constraint

arXiv:2605.00778v1 Announce Type: new Abstract: In biomechanical systems, observable performance is often used as a proxy for underlying system organization. However, this assumption implicitly presum

On the Expressive Power of Contextual Relations in Transformers

arXiv:2603.25860v2 Announce Type: replace-cross Abstract: Transformer architectures have achieved remarkable empirical success in modeling contextual relations, yet a clear understanding of their expr

Reinforcement Learning for LLM Post-Training: A Survey

arXiv:2407.16216v3 Announce Type: replace Abstract: Large language models (LLMs) trained via pretraining and supervised fine-tuning (SFT) can still produce harmful and misaligned outputs, or struggle

safetyarxiv-cs-cl

Retrieval-Augmented Reasoning for Chartered Accountancy

arXiv:2605.00257v1 Announce Type: new Abstract: The inception of Large Language Models (LLMs) has catalyzed AI adoption in the finance sector, yet their reliability in complex, jurisdiction-specific t

Scale-Aware Adversarial Analysis: A Diagnostic for Generative AI in Multiscale Complex Systems

arXiv:2605.00510v1 Announce Type: cross Abstract: Complex physical systems, from supersonic turbulence to the macroscopic structure of the universe, are governed by continuous multiscale dynamics. Whi

Scaling data and AI with Managed Service for Apache Airflow

model-releasesgoogle-cloud-ai

Orchestration is no longer just about moving data; it is about governing enterprise intelligence. To reflect our deep commitment to and embrace of open-source software, we shared earlier that Cloud Co

Something from Nothing: Data Augmentation for Robust Severity Level Estimation of Dysarthric Speech

arXiv:2603.15988v2 Announce Type: replace-cross Abstract: Dysarthric speech quality assessment (DSQA) is critical for clinical diagnostics and inclusive speech technologies. However, subjective evalua