Category
2,285 papers
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.
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...
Reach audiences
Advertise in front of researchers, engineers, and readers.
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...
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 In this chapter, we focus on a digital innovation which is not confined to a single application such as digital platforms, but on one – Artificial Intelligence or AI – which is in course of pervading the whole of the economy and society, and fully deserves the title of one (or several) general purpose technolo...
This work proposes that their diffusion can be understood through a viral analogy, with LLM use spreading through populations, becoming embedded in cognitive and cultural practices, and highlights how LLM adoption may involve nonlinear collective transitions with important consequences for cognitive autonomy.
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
