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The success of Large Language Models (LLMs) is inherently linked to the availability of vast, diverse, and high-quality data for training and evaluation.
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Webgpt: Browser-assisted question-answering with human feedback
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Florence: A new foundation model for computer vision
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Constitutional ai: Harmlessness from ai feedback
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DISCO: Distilling counterfactuals with large language models
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Language models can teach themselves to program better
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Is synthetic data from generative models ready for image recognition?
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Unnatural instructions: Tuning language models with (almost) no human labor
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Large language models can self-improve
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Coderl: Mastering code generation through pretrained models and deep reinforcement learning
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Solving quantitative reasoning problems with language models
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Galactica: A Large Language Model for Science
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Image data augmentation for deep learning: A survey
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Learning from mistakes makes llm better reasoner
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Llemma: An open language model for mathematics
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A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity. In Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers) . 675–718
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DISC-MedLLM: Bridging General Large Language Models and Real-World Medical Consultation
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Closing the loop: Testing chatgpt to generate model explanations to improve human labelling of sponsored content on social media. In World Conference on Explainable Artificial Intelligence . Springer, 198–213
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HuatuoGPT-II, One-stage Training for Medical Adaption of LLMs
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Sharegpt4v: Improving large multi-modal models with better captions
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Alpagasus: Training a better alpaca with fewer data
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Llava-interactive: An all-in-one demo for image chat, segmentation, generation and editing
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Generative AI for Math: Abel
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al · 2023
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John Joon Young Chung, Ece Kamar, and Saleema Amershi. 2023 · 2023
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Ultrafeedback: Boosting language models with high-quality feedback
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Chatlaw: Open-source legal large language model with integrated external knowledge bases
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Chataug: Leveraging chatgpt for text data augmentation
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Safe rlhf: Safe reinforcement learning from human feedback
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Enhancing chat language models by scaling high-quality instructional conversations
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Steerlm: Attribute conditioned sft as an (user-steerable) alternative to rlhf
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ChatGPT outperforms crowd workers for text-annotation tasks
Fabrizio Gilardi, Meysam Alizadeh, and Maël Kubli. 2023 · 2023
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Time travel in llms: Tracing data contamination in large language models
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Reinforced self-training (rest) for language modeling
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Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio César Teodoro Mendes, Allie Del Giorno, Sivakanth Gopi, Mojan Javaheripi, Piero Kauffmann, Gustavo de Rosa, Olli Saarikivi, et al · 2023
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Biyang Guo, Xin Zhang, Ziyuan Wang, Minqi Jiang, Jinran Nie, Yuxuan Ding, Jianwei Yue, and Yupeng Wu. 2023 · 2023
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Language Models Can Teach Themselves to Program Better. In International Conference on Learning Representations (ICLR)
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Chartllama: A multimodal llm for chart understanding and generation
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Mixgen: A new multi-modal data augmentation. In Proceedings of the IEEE/CVF winter conference on applications of computer vision . 379–389
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Cyclealign: Iterative distillation from black-box llm to white-box models for better human alignment
Jixiang Hong, Quan Tu, Changyu Chen, Xing Gao, Ji Zhang, and Rui Yan. 2023 · 2023
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Multilingual Mathematical Autoformalization
Albert Q. Jiang, Wenda Li, and Mateja Jamnik. 2023a · 2023
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AI-Powered Real-Time Speech-to-Speech Translation for Virtual Meetings Using Machine Learning Models. In 2023 Intelligent Computing and Control for Engineering and Business Systems (ICCEBS) . IEEE, 1–6
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Openassistant conversations-democratizing large language model alignment
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Rewardbench: Evaluating reward models for language modeling
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Common 7b language models already possess strong math capabilities
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Llava-med: Training a large language-and-vision assistant for biomedicine in one day
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SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding
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Case2Code: Learning Inductive Reasoning with Synthetic Data
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HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection
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ChemLLM: A Chemical Large Language Model
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LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model
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