Search: “framework”

Robotic Desk Organization: A Multi-Primitive Approach to Manipulating Heterogeneous Objects via Environmental Constraints

arXiv:2605.02135v1 Announce Type: new Abstract: Desktop organization remains challenging for service robots because of heterogeneous objects and diverse manipulation objectives, such as collection and

applicationsarxiv-cs-ro

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Robust Cross-Domain WiFi Fall Detection via Physics-Driven Attention-Enhanced Transformers

DGX agent

arXiv:2605.00869v1 Announce Type: cross Abstract: Device-free fall detection utilizing WiFi Channel State Information (CSI) has emerged as a promising, privacy-preserving solution for elderly health m

local-aiarxiv-cs-cv

5 May 2026

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

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

model-releasesarxiv-cs-lg

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

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

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

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

researcharxiv-cs-lg

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

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

researcharxiv-cs-lg

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

researcharxiv-cs-lg

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