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The paper by Dr. Liang Wenfeng's team at DeepSeek in collaboration with Peking University has won the ACL 2025 Best Paper Award. This research proposes the Native Sparse Attention (NSA) mechanism, which achieves algorithm-hardware co-optimization through three parallel attention branches: compression, selection, and sliding. It improves the processing speed of long texts by 11 times and outperforms traditional full-attention models. NSA supports a context length of up to 1 million tokens, achieving an 11.6 times decoding speed improvement on 64k text, and a 27B parameter model demonstrates excellent performance on multiple benchmark tests.

Research reveals scholars from 8 countries embedded hidden AI prompts in papers to influence reviews. 17 CS papers used white text/tiny fonts to request 'positive evaluations' from AI reviewers, raising academic integrity concerns.....

E Ink recently announced the development of a new touchpad for laptops, which uses the same e-paper technology as e-readers. This innovative product is not simply about increasing the size of the touchpad or adding secondary display features, but rather positioning it as a dedicated platform for AI applications and assistants, designed to run in parallel with mainstream operating systems. E Ink released a prototype image showing the upgraded touchpad, which is equipped with a color e-ink screen similar to the Amazon Kindle Color.

Recently, an intelligent academic research tool called ScholAI has attracted widespread attention. This innovative tool, based on the Multi-Cloud Platform (MCP), integrates functions such as paper search, analysis, management, CCF ranking query, and semantic query analysis, providing researchers with an efficient and intelligent academic research solution. The AIbase editorial team has compiled the latest information from the web to provide you with a comprehensive overview of ScholAI's unique advantages and future potential. Core Features of ScholAI: One

A deep dive into how Eureka AI addresses three major pain points in R&D - information overload, innovation bottlenecks, and evaluation difficulties - through core features such as a technical Q&A assistant and TRIZ theory innovation. It provides end-to-end AI support solutions from concept to implementation.

In the rapid development of technology, the application of artificial intelligence (AI) is becoming more and more widespread. Many people are beginning to look forward to the rise of the "agent" technology. An agent refers to an intelligent program that can work autonomously and accomplish specific goals. Recently, discussions about AI agents have been flourishing, but existing technologies still have a long way to go before achieving true intelligent agents. Imagine if we could have an AI agent capable of automatically writing academic papers. It could delve into learning how to write papers, analyze data, and conduct literature reviews after receiving datasets and research fields...

Recently, the DeepSeek team released a technical paper about their latest model, DeepSeek-V3, focusing on the challenges of scaling in large AI model training and related considerations of hardware architecture. This 14-page paper not only summarizes the experiences and lessons learned during the development of V3 by DeepSeek but also provides deep insights for future hardware design. Notably, CEO of DeepSeek, Liang Wenfeng, also participated in writing the paper.

A recent paper jointly published by Tsinghua University and Shanghai Jiao Tong University challenges the widely held belief that pure reinforcement learning (RL) enhances large model reasoning capabilities. The research found that models incorporating reinforcement learning performed worse than their original counterparts in certain tasks.

In modern scientific research, accessing and discovering relevant literature is crucial for researchers. Therefore, Ai2PaperFinder was created, a powerful tool designed to help users easily find the academic papers they need. The platform brings together over 8 million full-text papers and over 108 million abstracts, offering broad and deep coverage. Ai2PaperFinder's unique strength lies in its powerful literature retrieval capabilities. Users can quickly find relevant research papers by inputting keywords. Whether it's a trending topic or a niche area...

Recently, a miniature deep-sea multi-modal robot jointly developed by Beihang University, the Institute of Deep-Sea Science and Engineering of the Chinese Academy of Sciences, and Zhejiang University, was successfully published in the top international academic journal Science Robotics. This robot has milestone significance in ocean exploration and scientific research, particularly in deep-sea applications. Measuring less than 50 centimeters long and weighing only 1500 grams, this remarkable robot can perform multi-modal movement at a depth of 10,000 meters. This means it can not only swim, but also glide and crawl, demonstrating exceptional capabilities.

Sakana AI's newly developed AI Scientist-v2 model has accomplished a jaw-dropping feat—it independently authored a complete scientific paper, from conception to completion, without any human intervention. Even more astonishing, this paper successfully passed the double-blind peer review of the ICLR2025 workshop, fooling the discerning eyes of human experts. This AI-generated paper achieved fully end-to-end autonomous creation; Sakana AI confirms that the entire process was completed without any human modification.

A revolutionary AI tool transforms complex arXiv papers into easily digestible blog posts, drastically improving research efficiency and accessibility.

With the rapid development of artificial intelligence, AI tools have become increasingly popular among college students for completing reports and essays. According to CCTV News, some university teachers and experts have reported cases of academic misconduct, including fabricating research data, editing experimental images, and substituting original designs. A notice in a university assignment group drew widespread attention, stating that students submitting AI-generated essays would receive a failing grade.

Recently, China National Knowledge Infrastructure announced the official launch of its new knowledge service solution, which integrates the Cognitive Model with DeepSeek. This combination aims to provide users with more precise and comprehensive knowledge answers through its expertise across all disciplines and fields, as well as deep thinking capabilities.

In the field of academic research, literature retrieval is a complex and crucial information acquisition task. Researchers need the capability to handle intricate, domain-specific search queries to meet detailed research requirements. However, existing academic search platforms, like Google Scholar, often struggle to address these complex research queries. For example, queries related to non-stationary reinforcement learning using the UCB method require stronger computational and analytical capabilities. Moreover, researchers typically need to spend a significant amount of time and effort manually browsing extensive academic literature when conducting literature reviews.