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ArXiv Domain 2025-09-04
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. MMReview: A Multidisciplinary and Multimodal Benchmark for LLM-Based Peer Review AutomationWith the rapid growth of academic publications, peer review has become an essential yet time-consuming responsibility within the research community. Large Language Models (LLMs) have increasingly been adopted to assist in the generation of review comments; however, current LLM-based review tasks lack a unified evaluation benchmark to rigorously assess the models’ abi ...
ArXiv Domain 2025-09-03
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. ROSE: A Reward-Oriented Data Selection Framework for LLM Task-Specific Instruction TuningInstruction tuning has underscored the significant potential of large language models (LLMs) in producing more human controllable and effective outputs in various domains. In this work, we focus on the data selection problem for task-specific instruction tuning of LLMs. Prevailing methods primarily rely on the crafted similarity metrics to select training data that ali ...
ArXiv Domain 2025-09-05
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. Continuous Saudi Sign Language Recognition: A Vision Transformer ApproachSign language (SL) is an essential communication form for hearing-impaired and deaf people, enabling engagement within the broader society. Despite its significance, limited public awareness of SL often leads to inequitable access to educational and professional opportunities, thereby contributing to social exclusion, particularly in Saudi Arabia, where over 84,000 individuals depend ...
ArXiv Domain 2025-09-06
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. Delta Activations: A Representation for Finetuned Large Language ModelsThe success of powerful open source Large Language Models (LLMs) has enabled the community to create a vast collection of post-trained models adapted to specific tasks and domains. However, navigating and understanding these models remains challenging due to inconsistent metadata and unstructured repositories. We introduce Delta Activations, a method to represent finetuned models as vec ...
ArXiv Domain 2025-09-07
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. On sources to variabilities of simple cells in the primary visual cortex: A principled theory for the interaction between geometric image transformations and receptive field responsesThis paper gives an overview of a theory for modelling the interaction between geometric image transformations and receptive field responses for a visual observer that views objects and spatio-temporal events in the environment. This treatment is developed over combinations of ...
ArXiv Domain 2025-09-08
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. On sources to variabilities of simple cells in the primary visual cortex: A principled theory for the interaction between geometric image transformations and receptive field responsesThis paper gives an overview of a theory for modelling the interaction between geometric image transformations and receptive field responses for a visual observer that views objects and spatio-temporal events in the environment. This treatment is developed over combinations of ...
ArXiv Domain 2025-09-09
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. Scaling Environments for Organoid Intelligence with LLM-Automated Design and Plasticity-Based EvaluationAs the complexity of artificial agents increases, the design of environments that can effectively shape their behavior and capabilities has become a critical research frontier. We propose a framework that extends this principle to a novel class of agents: biological neural networks in the form of neural organoids. This paper introduces three scalable, cl ...
ArXiv Domain 2025-09-10
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. Scaling Environments for Organoid Intelligence with LLM-Automated Design and Plasticity-Based EvaluationAs the complexity of artificial agents increases, the design of environments that can effectively shape their behavior and capabilities has become a critical research frontier. We propose a framework that extends this principle to a novel class of agents: biological neural networks in the form of neural organoids. This paper introduces three scalable, cl ...
ArXiv Domain 2025-09-11
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. Scaling Environments for Organoid Intelligence with LLM-Automated Design and Plasticity-Based EvaluationAs the complexity of artificial agents increases, the design of environments that can effectively shape their behavior and capabilities has become a critical research frontier. We propose a framework that extends this principle to a novel class of agents: biological neural networks in the form of neural organoids. This paper introduces three scalable, cl ...
ArXiv Domain 2025-09-12
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. Scaling Environments for Organoid Intelligence with LLM-Automated Design and Plasticity-Based EvaluationAs the complexity of artificial agents increases, the design of environments that can effectively shape their behavior and capabilities has become a critical research frontier. We propose a framework that extends this principle to a novel class of agents: biological neural networks in the form of neural organoids. This paper introduces three scalable, cl ...
ArXiv Domain 2025-09-13
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. Scaling Environments for Organoid Intelligence with LLM-Automated Design and Plasticity-Based EvaluationAs the complexity of artificial agents increases, the design of environments that can effectively shape their behavior and capabilities has become a critical research frontier. We propose a framework that extends this principle to a novel class of agents: biological neural networks in the form of neural organoids. This paper introduces three scalable, cl ...
ArXiv Domain 2025-09-14
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. Scaling Environments for Organoid Intelligence with LLM-Automated Design and Plasticity-Based EvaluationAs the complexity of artificial agents increases, the design of environments that can effectively shape their behavior and capabilities has become a critical research frontier. We propose a framework that extends this principle to a novel class of agents: biological neural networks in the form of neural organoids. This paper introduces three scalable, cl ...
ArXiv Domain 2025-09-15
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. Scaling Environments for Organoid Intelligence with LLM-Automated Design and Plasticity-Based EvaluationAs the complexity of artificial agents increases, the design of environments that can effectively shape their behavior and capabilities has become a critical research frontier. We propose a framework that extends this principle to a novel class of agents: biological neural networks in the form of neural organoids. This paper introduces three scalable, cl ...
ArXiv Domain 2025-09-16
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. Scaling Environments for Organoid Intelligence with LLM-Automated Design and Plasticity-Based EvaluationAs the complexity of artificial agents increases, the design of environments that can effectively shape their behavior and capabilities has become a critical research frontier. We propose a framework that extends this principle to a novel class of agents: biological neural networks in the form of neural organoids. This paper introduces three scalable, cl ...
ArXiv Domain 2025-09-17
Created2019-06-18|AI
数据来源:ArXiv Domain LLM Domain Papers1. Scaling Environments for Organoid Intelligence with LLM-Automated Design and Plasticity-Based EvaluationAs the complexity of artificial agents increases, the design of environments that can effectively shape their behavior and capabilities has become a critical research frontier. We propose a framework that extends this principle to a novel class of agents: biological neural networks in the form of neural organoids. This paper introduces three scalable, cl ...
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