Results 71 to 80 of about 16,728 (252)

From Lab to Landscape: Environmental Biohybrid Robotics for Ecological Futures

open access: yesAdvanced Robotics Research, EarlyView.
This Perspective explores environmental biohybrid robotics, integrating living tissues, microorganisms, and insects for operation in real‐world ecosystems. It traces the leap from laboratory experiments to forests, wetlands, and urban environments and discusses key challenges, development pathways, and opportunities for ecological monitoring and ...
Miriam Filippi
wiley   +1 more source

MGPRAG: Enhancing Medical Large Language Models via Precision Retrieval-Augmented Generation

open access: yesIEEE Access
Large language models(LLMs) have demonstrated strong performance in general tasks, but remain insufficiently trusted in complex clinical question answering (CQA). This is largely due to concerns about the accuracy of the generated content.
Yanwen Shen   +4 more
doaj   +1 more source

Feedback Adaptation for Retrieval-Augmented Generation

open access: yesFindings of the Association for Computational Linguistics: ACL 2026
Accepted at ACL 2026 ...
Jihwan Bang   +5 more
openaire   +3 more sources

Intelligent Sky Guardians (InSkyGuard): An Aerial Robotic Swarm for Autonomous Detection and Entrapment of Rogue Multirotors

open access: yesAdvanced Robotics Research, EarlyView.
Intelligent Sky Guardians (InSkyGuard) is introduced as a four‐drone swarm that autonomously detects, tracks, and safely captures rogue drones using a coordinated net system. Computer vision and leader–follower control architecture enable synchronized enclosure, while integrated failsafes enhance system reliability. Validated through closed‐environment
Joshua Hastings   +6 more
wiley   +1 more source

Functional Fibers in Soft Robotics: Advances in Material, Structural, and Systemic Tactics

open access: yesAdvanced Robotics Research, EarlyView.
Fiber‐form robotic systems offer a scalable pathway toward embodied intelligence in soft robotics. This review surveys functional fibers as material, structural, and systemic elements, highlighting advances in responsive materials, architectural programing, and fabrication strategies.
Joonhee Won   +5 more
wiley   +1 more source

Retrieval-augmented generation in multilingual settings

open access: yesProceedings of the 1st Workshop on Towards Knowledgeable Language Models (KnowLLM 2024)
Retrieval-augmented generation (RAG) has recently emerged as a promising solution for incorporating up-to-date or domain-specific knowledge into large language models (LLMs) and improving LLM factuality, but is predominantly studied in English-only settings. In this work, we consider RAG in the multilingual setting (mRAG), i.e.
Nadezhda Chirkova   +5 more
openaire   +3 more sources

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

open access: yesAdvanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder   +3 more
wiley   +1 more source

Role-Aware Agentic Retrieval-Augmented Generation for Urban Rail Transit Fault Management

open access: yesAI
Urban rail transit systems require reliable decision-support methods to assist operators in handling complex fault events. Although large language models provide strong reasoning and knowledge integration capabilities, their open-ended generation may ...
Wei Zhang   +4 more
doaj   +1 more source

Differentially Private Retrieval-Augmented Generation

open access: yesCoRR
Retrieval-augmented generation (RAG) is a widely used framework for reducing hallucinations in large language models (LLMs) on domain-specific tasks by retrieving relevant documents from a database to support accurate responses. However, when the database contains sensitive corpora, such as medical records or legal documents, RAG poses serious privacy ...
Tingting Tang   +3 more
openaire   +2 more sources

Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences

open access: yesAdvanced Science, EarlyView.
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu   +7 more
wiley   +1 more source

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