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2,592 papers
Large language models (LLMs) are developing rapidly and have been widely applied in intelligent question answering, knowledge retrieval, education, healthcare, enterprise services, and other fields. However, LLMs still exhibit limitations in knowledge updating, understanding complex relationships, and tracing answer so...
ABSTRACT This paper formulates and analyzes the concept of "Noetic Castration" (algorithmic smoothing) in the context of generative AI-assisted literary production. Operating strictly within syntactic and statistical optimization, Large Language Models (LLMs) interpret peak emotional, existential, and metaphysical expr...
The integration of reinforcement learning (RL) into the optimization of multi-agent collaboration for Large Language Models (LLMs) is an important combination of two advanced areas, Multi-Agent Systems (MAS) and LLMs. This paper thoroughly examines the main approaches, evaluation standards, recent progress and existing...
The proposed method provides a feasible pathway for intelligent diagnosis, precise feedback, and personalized learning support in Chinese composition education and indicates that semantic features can improve the accuracy and ordinal consistency of writing mastery prediction.
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Artificial intelligence (AI) has become a significant force in the field of quantitative trading because it extends traditional rule-based systems to areas such as adaptive prediction, dynamic configuration and automated execution. At the same time, the widespread adoption of machine learning, reinforcement learning, a...
It is concluded that autonomous UAV operations necessitate a fundamental shift toward Trustworthy and Explainable AI (XAI), coupled with high-fidelity digital twin validation, to guarantee system stability in safety-critical domains.
The research findings show that RL has gradually expanded from simply improving the accuracy of the final answer to optimizing queries, multi-round search, process decision-making and trustworthy screening, providing new ideas for enhancing the active retrieval ability of RAG and improving the credibility of informatio...
Digital transformation transforms an enterprise's green innovation capabilities, requiring the measurement and identification of genuine organizational changes and analyzing how capital constraints shape the marginal returns of technological investment. This paper, based on 18,642 annual observations of Chinese A-share...
This paper investigates the development path of large language model preference alignment techniques, focusing on the training mechanism of Reinforcement Learning from Human Feedback and its three-stage process, including supervised fine-tuning, reward model training, and PPO-based policy optimization.
Fire shapes the biodiversity of tropical savannas, yet challenges exist in accessing and interpreting the breadth of fire-ecology evidence to support appropriate management. We compiled a comprehensive fire–biodiversity database for Australian tropical savannas to improve knowledge discovery and support the iterative d...
This paper proposes a research hypothesis concerning the possibility of identifying the point at which further iterative reconsideration of a task by a large language model ceases to produce substantial improvement. The central idea is based on an iterative tool that does not simply ask a model to answer the same promp...
ABSTRACT This paper formulates and analyzes the concept of "Noetic Castration" (algorithmic smoothing) in the context of generative AI-assisted literary production. Operating strictly within syntactic and statistical optimization, Large Language Models (LLMs) interpret peak emotional, existential, and metaphysical expr...
A Blog post by IBM Granite on Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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A Blog post by Liquid AI on Hugging Face
Genie 4: our new world model unlocking unprecedented realism in real-time simulation.
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