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Paper Central is a comprehensive and convenient academic platform launched by Hugging Face. It integrates open source academic resources from multiple sources such as arXiv, Hugging Face paper pages, models, data sets, Space, GitHub, and conference proceedings to help researchers and developers quickly obtain and use open source resources.
SciAgentsDiscovery is a system that utilizes multi-agent systems and large-scale ontology knowledge graphs to automate scientific research. By integrating large-scale language models, data retrieval tools, and multi-agent learning systems, it can autonomously generate and refine research hypotheses, revealing underlying mechanisms, design principles, and unexpected material properties. The system demonstrates its ability to discover interdisciplinary relationships in the field of bioinspired materials, beyond traditional human-driven research methods.
The TOFU dataset contains fictitiously generated question and answer pairs based on 200 non-existent authors and is used to evaluate the forgetting performance of large language models on real tasks. The goal of this task is to forget a model that is fine-tuned on various forgetting set ratios. This dataset is in question and answer format, making it ideal for use with popular chat models such as Llama2, Mistral or Qwen. However, it also works for any other large language model. The corresponding code base is written for the Llama2 chat and Phi-1.5 models, but can be easily adapted to other models.
BenAI Research Assistant is an artificial intelligence-based literature analysis plug-in for enhancing biomedical research. It helps scientists read literature more efficiently, discover evidence quickly, and provides tools to read faster. It supports key functions such as deciding whether to read an article, understanding and discovering its key insights, answering scientific questions, and maintaining the research process without the need for additional tools. Suitable for scientists in academia, pharmaceutical and biotech companies.
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