İçeriğe geç

Canlı masa

Makaleler
ve çalışmalar.

Hugging Face günlük masasında bugün en çok oy alan makaleler. Atıf sırası OpenAlex’ten: son bir yıl, yapay zeka alt alanı. Oy, yıldız ve atıf sayıları kaynağın kendi rakamı.

Masa
50
En çok oy
86
En çok atıf
2.750

Akış 10 Kasım 2026 · 13:34 · Hugging Face · OpenAlex

Popüler50Yıldız50Yeni50Atıf18
Atıf2.750 atıfAçıkA Comprehensive Overview of Large Language ModelsLarge Language Models (LLMs) have recently demonstrated remarkable capabilities in natural language processing tasks and beyond. This success of LLMs has led to a large influx of research contributions in this direction. These works encompass diverse topics such as architectural innovations, better training strategies, context length improvements, fine-tuning, multimodal LLMs, robotics, datasets, benchmarking, eff…Humza Naveed, Asad Ullah Khan, Shi Qiu ve 6 kişi · ACM Transactions on Intelligent Systems and Technology · 18 Haziran 2025
AtıfOrganization Science · 1 Mart 2026Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of Artificial Intelligence on Knowledge Worker Productivity and QualityAtıfACM Computing Surveys · 17 Kasım 2025Instruction Tuning for Large Language Models: A SurveyAtıfNature · 28 Ocak 2026A benchmark of expert-level academic questions to assess AI capabilities

Çok atıf alanlar

14 makale

Atıf871 atıfTopic ModelingData Science and Engineering · 2 Ocak 2026Retrieval-Augmented Generation for AI-Generated Content: A SurveyAdvancements in model algorithms, the growth of foundational models, and access to high-quality datasets have propelled the evolution of Artificial Intelligence Generated Content (AIGC). Despite its notable successes, AIGC still faces hurdles such as updating knowledge, handling long-tail data, mitigating data leakage, and managing high training and inference costs. Retrieval-augmented generation (RAG) has recentl…Makaleyi aç →
Atıf753 atıfEthics and Social Impacts of AIACM Computing Surveys · 15 Ekim 2025AI Alignment: A Contemporary SurveyAI alignment aims to make AI systems behave in line with human intentions and values. As AI systems grow more capable, so do risks from misalignment. To provide a comprehensive and up-to-date overview of the alignment field, in this survey, we delve into the core concepts, methodology, and practice of alignment. First, we identify four principles as the key objectives of AI alignment: Robustness, Interpretability,…Makaleyi aç →
Atıf752 atıfAdversarial Robustness in Machine LearningACM Transactions on Software Engineering and Methodology · 16 Şubat 2026Model Context Protocol (MCP): Landscape, Security Threats, and Future Research DirectionsThe Model Context Protocol (MCP) is an emerging open standard that defines a unified, bi-directional communication and dynamic discovery protocol between AI models and external tools or resources, aiming to enhance interoperability and reduce fragmentation across diverse systems. This paper conducts a systematic study of MCP from both architectural and security perspectives. We first define the full lifecycle of a…Makaleyi aç →
Atıf706 atıfTopic ModelingNature · 22 Nisan 2026Evaluating large language models for accuracy incentivizes hallucinationsAbstract Large language models sometimes produce confident, plausible falsehoods (‘hallucinations’), limiting their reliability 1,2 . Previous work has offered numerous explanations and effective mitigations such as retrieval and tool use 3 , consistency-based self-verification 4 and reinforcement learning from human feedback 5 . Nonetheless, the problem persists even in state-of-the-art language models 6,7 . Here…Makaleyi aç →
Atıf698 atıfTopic ModelingACM Transactions on Information Systems · 19 Kasım 2025Graph Retrieval-Augmented Generation: A SurveyRecently, Retrieval-Augmented Generation (RAG) has achieved remarkable success in addressing the challenges of Large Language Models (LLMs) without necessitating retraining. By referencing an external knowledge base, RAG refines LLM outputs, effectively mitigating issues such as “hallucination,” lack of domain-specific knowledge, and outdated information. However, the complex structure of relationships among diffe…Makaleyi aç →
Atıf671 atıfArtificial Intelligence ApplicationsInformation Fusion · 22 Ağustos 2025AI Agents vs. Agentic AI: A Conceptual taxonomy, applications and challengesInformation fusion, in the context of the Generative AI era, must distinguish AI Agents from Agentic AI. This review critically distinguishes between AI Agents and Agentic AI, offering a structured, conceptual taxonomy, application mapping, and analysis of opportunities and challenges to clarify their divergent design philosophies and capabilities. We begin by outlining the search strategy and foundational definit…Makaleyi aç →
Atıf592 atıfAI-based Problem Solving and PlanningACM Transactions on Information Systems · 11 Temmuz 2025A Survey on the Memory Mechanism of Large Language Model-based AgentsLarge language model (LLM)-based agents have recently attracted much attention from the research and industry communities. Compared with original LLMs, LLM-based agents are featured in their self-evolving capability, which is the basis for solving real-world problems that need long-term and complex agent-environment interactions. The key component to support agent-environment interactions is the memory of the agen…Makaleyi aç →
Atıf567 atıfTopic ModelingIEEE Transactions on Pattern Analysis and Machine Intelligence · 27 Ocak 2026Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and AssessmentWith the continuous growth in the number of parameters of the Transformer-based pretrained language models (PLMs), particularly the emergence of large language models (LLMs) with billions of parameters, many natural language processing (NLP) tasks have demonstrated remarkable success. However, the enormous size and computational demands of these models pose significant challenges for adapting them to specific down…Makaleyi aç →
Atıf543 atıfTopic ModelingScience China Information Sciences · 12 Mayıs 2026Towards reasoning era: a survey of long chain-of-thought for reasoning large language modelsAbstract Recent advancements in reasoning with large language models (RLLMs), such as OpenAI-o1 and DeepSeek-R1, have demonstrated their impressive capabilities in complex domains like mathematics and coding. A central factor in their success lies in the application of long chain-of-thought (Long CoT) characteristics, which enhance reasoning abilities and enable the solution of intricate problems. However, despite…Makaleyi aç →
Atıf540 atıfPrivacy-Preserving Technologies in DataACM Transactions on Intelligent Systems and Technology · 22 Temmuz 2025A Survey of Machine UnlearningToday, computer systems hold large amounts of personal data. Yet while such an abundance of data allows breakthroughs in AI, and especially machine learning, its existence can be a threat to user privacy, and it can weaken the bonds of trust between humans and AI. Recent regulations now require that, on request, private information about a user must be removed both from computer systems and from machine learning m…Makaleyi aç →
Atıf466 atıfAdversarial Robustness in Machine LearningIEEE Transactions on Pattern Analysis and Machine Intelligence · 2 Şubat 2026Jailbreak and Guard Aligned Language Models With Only Few In-Context DemonstrationsLarge Language Models (LLMs) have demonstrated remarkable success across diverse applications, yet their susceptibility to malicious exploitation remains a critical challenge. Notably, LLMs are known to be vulnerable to jailbreaking attacks, where adversaries craft malicious inputs to induce harmful or unethical outputs. In this paper, motivated by the unique effectiveness and scalability of In-Context Learning (I…Makaleyi aç →
Atıf419 atıfIntelligent Tutoring Systems and Adaptive LearningScientific Reports · 3 Haziran 2025AI tutoring outperforms in-class active learning: an RCT introducing a novel research-based design in an authentic educational settingAdvances in generative artificial intelligence show great potential for improving education. Yet little is known about how this new technology should be used and how effective it can be compared to current best practices. Here we report a randomized, controlled trial measuring college students' learning and their perceptions when content is presented through an AI-powered tutor compared with an active learning cla…Makaleyi aç →
Atıf387 atıfAdversarial Robustness in Machine LearningSuperIntelligence - Robotics - Safety & Alignment · 20 Temmuz 2025Deliberative Alignment: Reasoning Enables Safer Language ModelsAs large-scale language models increasingly impact safety-critical domains, ensuring their reliable adherence to well-defined principles remains a fundamental challenge. We introduce Deliberative Alignment, a new paradigm that directly teaches the model safety specifications and trains it to explicitly recall and accurately reason over the specifications before answering. We used this approach to align OpenAI’s o-…Makaleyi aç →
Atıf374 atıfTopic ModelingASEE Journal of Engineering Technology · 24 Nisan 2026Prompt Engineering for ChatGPT: A Quick Guide to Techniques, Tips, and Best PracticesIn the rapidly evolving landscape of natural language processing (NLP), ChatGPT has emerged as a powerful tool for various industries and applications. To fully harness the potential of ChatGPT, it is crucial to understand and master the art of prompt engineering-the process of designing and refining input prompts to elicit desired responses from an AI NLP model. This article provides a comprehensive guide to mast…Makaleyi aç →
Makaleler · MAAI