232 lines
8.7 KiB
BibTeX
232 lines
8.7 KiB
BibTeX
@misc{anthropic2024mcp,
|
|
author = {{Anthropic}},
|
|
title = {Model Context Protocol (MCP) Specification},
|
|
year = {2024},
|
|
howpublished = {\url{https://modelcontextprotocol.io}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{huggingface2024mcp,
|
|
author = {{Hugging Face}},
|
|
title = {Introduction to Model Context Protocol (MCP)},
|
|
year = {2024},
|
|
howpublished = {\url{https://huggingface.co/learn/mcp-course/en/unit1/key-concepts}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{langgraph2024,
|
|
author = {{LangChain}},
|
|
title = {LangGraph: Building Stateful, Multi-agent Applications with LLMs},
|
|
year = {2024},
|
|
howpublished = {\url{https://docs.langchain.com/oss/python/langgraph/workflows-agents}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{meta2024llama3,
|
|
author = {{Meta AI}},
|
|
title = {Llama 3: Open-weight Large Language Models},
|
|
year = {2024},
|
|
howpublished = {\url{https://llama.meta.com/llama3/}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{pgvector2024,
|
|
author = {{PostgreSQL Global Development Group}},
|
|
title = {pgvector: Open-source Vector Similarity Search for PostgreSQL},
|
|
year = {2024},
|
|
howpublished = {\url{https://github.com/pgvector/pgvector}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{pinecone2023rag,
|
|
author = {{Pinecone}},
|
|
title = {Retrieval Augmented Generation (RAG) and Semantic Search},
|
|
year = {2023},
|
|
howpublished = {\url{https://www.pinecone.io/learn/retrieval-augmented-generation/}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{dettmers2023bitsandbytes,
|
|
author = {Dettmers, Tim},
|
|
title = {4-bit Quantization and Bitsandbytes for LLMs},
|
|
year = {2023},
|
|
howpublished = {\url{https://huggingface.co/blog/4bit-transformers-bitsandbytes}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{channels2024docs,
|
|
author = {{Django Software Foundation}},
|
|
title = {Django Channels Documentation},
|
|
year = {2024},
|
|
howpublished = {\url{https://channels.readthedocs.io/en/stable/}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{django2024docs,
|
|
author = {{Django Software Foundation}},
|
|
title = {Django Documentation},
|
|
year = {2024},
|
|
howpublished = {\url{https://docs.djangoproject.com/}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{drf2024docs,
|
|
author = {{Encode OSS}},
|
|
title = {Django REST Framework Documentation},
|
|
year = {2024},
|
|
howpublished = {\url{https://www.django-rest-framework.org/}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{celery2024docs,
|
|
author = {{Celery Project}},
|
|
title = {Celery Documentation},
|
|
year = {2024},
|
|
howpublished = {\url{https://docs.celeryq.dev/}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{redis2024docs,
|
|
author = {{Redis Ltd.}},
|
|
title = {Redis Documentation},
|
|
year = {2024},
|
|
howpublished = {\url{https://redis.io/docs/}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{fastapi2024docs,
|
|
author = {{FastAPI}},
|
|
title = {FastAPI Documentation},
|
|
year = {2024},
|
|
howpublished = {\url{https://fastapi.tiangolo.com/}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{sbert2024docs,
|
|
author = {{UKPLab / SBERT}},
|
|
title = {Sentence-Transformers Documentation},
|
|
year = {2024},
|
|
howpublished = {\url{https://www.sbert.net/}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
|
|
@misc{llamacpp2024,
|
|
author = {{ggml-org}},
|
|
title = {llama.cpp Documentation},
|
|
year = {2024},
|
|
howpublished = {\url{https://github.com/ggml-org/llama.cpp}},
|
|
note = {Accessed: 2026-03-09}
|
|
}
|
|
@inproceedings{lewis2020rag,
|
|
author = {Lewis, Patrick and Perez, Ethan and Piktus, Aleksandra and Petroni, Fabio and Karpukhin, Vladimir and Goyal, Naman and K{"u}ttler, Heinrich and Lewis, Mike and Yih, Wen{-}tau and Rockt{"a}schel, Tim and Riedel, Sebastian and Kiela, Douwe},
|
|
title = {Retrieval-Augmented Generation for Knowledge-Intensive {NLP} Tasks},
|
|
booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
|
|
year = {2020},
|
|
url = {https://arxiv.org/abs/2005.11401}
|
|
}
|
|
|
|
@inproceedings{schick2023toolformer,
|
|
author = {Schick, Timo and Dwivedi{-}Yu, Jane and Dess{\`i}, Roberto and Raileanu, Roberta and Lomeli, Maria and Hambro, Eric and Zettlemoyer, Luke and Cancedda, Nicola and Scialom, Thomas},
|
|
title = {Toolformer: Language Models Can Teach Themselves to Use Tools},
|
|
booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
|
|
year = {2023},
|
|
url = {https://arxiv.org/abs/2302.04761}
|
|
}
|
|
|
|
@article{wu2023autogen,
|
|
author = {Wu, Qingyun and Bansal, Gagan and Zhang, Jieyu and Wu, Yiran and Li, Beibin and Zhu, Erkang and Jiang, Li and Zhang, Xiaoyun and Wang, Chi and Li, Shaokun and Liu, Siyuan and Awadallah, Ahmed Hassan},
|
|
title = {AutoGen: Enabling Next-Gen {LLM} Applications via Multi-Agent Conversation},
|
|
journal = {arXiv preprint arXiv:2308.08155},
|
|
year = {2023},
|
|
url = {https://arxiv.org/abs/2308.08155}
|
|
}
|
|
|
|
@article{vanlehn2011,
|
|
author = {VanLehn, Kurt},
|
|
title = {The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems},
|
|
journal = {Educational Psychologist},
|
|
volume = {46},
|
|
number = {4},
|
|
pages = {197--221},
|
|
year = {2011},
|
|
doi = {10.1080/00461520.2011.611369}
|
|
}
|
|
|
|
@inproceedings{karpukhin2020dpr,
|
|
author = {Karpukhin, Vladimir and Oguz, Barlas and Min, Sewon and Lewis, Patrick and Wu, Ledell and Edunov, Sergey and Chen, Danqi and Yih, Wen{-}tau},
|
|
title = {Dense Passage Retrieval for Open-Domain Question Answering},
|
|
booktitle = {Proceedings of EMNLP},
|
|
year = {2020},
|
|
url = {https://arxiv.org/abs/2004.04906}
|
|
}
|
|
|
|
@article{johnson2019faiss,
|
|
author = {Johnson, Jeff and Douze, Matthijs and J{\'e}gou, Herv{\'e}},
|
|
title = {Billion-scale Similarity Search with {GPUs}},
|
|
journal = {IEEE Transactions on Big Data},
|
|
year = {2019},
|
|
volume = {7},
|
|
number = {3},
|
|
pages = {535--547},
|
|
url = {https://arxiv.org/abs/1702.08734}
|
|
}
|
|
|
|
@inproceedings{reimers2019sbert,
|
|
author = {Reimers, Nils and Gurevych, Iryna},
|
|
title = {Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks},
|
|
booktitle = {Proceedings of EMNLP-IJCNLP},
|
|
year = {2019},
|
|
pages = {3982--3992},
|
|
url = {https://arxiv.org/abs/1908.10084}
|
|
}
|
|
|
|
@inproceedings{hu2021lora,
|
|
author = {Hu, Edward J. and Shen, Yelong and Wallis, Phillip and Allen-Zhu, Zeyuan and Li, Yuanzhi and Wang, Shean and Wang, Lu and Chen, Weizhu},
|
|
title = {{LoRA}: Low-Rank Adaptation of Large Language Models},
|
|
booktitle = {International Conference on Learning Representations (ICLR)},
|
|
year = {2022},
|
|
url = {https://arxiv.org/abs/2106.09685}
|
|
}
|
|
|
|
@article{li2023camel,
|
|
author = {Li, Guohao and Hammoud, Hasan Abed Al Kader and Itani, Hani and Khizbullin, Dmitrii and Ghanem, Bernard},
|
|
title = {{CAMEL}: Communicative Agents for ``Mind'' Exploration of Large Language Model Society},
|
|
journal = {arXiv preprint arXiv:2303.17760},
|
|
year = {2023},
|
|
url = {https://arxiv.org/abs/2303.17760}
|
|
}
|
|
|
|
@inproceedings{yao2023react,
|
|
author = {Yao, Shunyu and Zhao, Jeffrey and Yu, Dian and Du, Nan and Shafran, Izhak and Narasimhan, Karthik and Cao, Yuan},
|
|
title = {{ReAct}: Synergizing Reasoning and Acting in Language Models},
|
|
booktitle = {International Conference on Learning Representations (ICLR)},
|
|
year = {2023},
|
|
url = {https://arxiv.org/abs/2210.03629}
|
|
}
|
|
|
|
@article{gao2023ragsurvey,
|
|
author = {Gao, Yunfan and Xiong, Yun and Gao, Xinyu and Jia, Kang and Pan, Jinliu and Bi, Yuxi and Dai, Yi and Sun, Jiawei and Wang, Meng and Wang, Haofen},
|
|
title = {Retrieval-Augmented Generation for Large Language Models: A Survey},
|
|
journal = {arXiv preprint arXiv:2312.10997},
|
|
year = {2023},
|
|
url = {https://arxiv.org/abs/2312.10997}
|
|
}
|
|
|
|
@article{liu2023promptsurvey,
|
|
author = {Liu, Pengfei and Yuan, Weizhe and Fu, Jinlan and Jiang, Zhengbao and Hayashi, Hiroaki and Neubig, Graham},
|
|
title = {Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing},
|
|
journal = {ACM Computing Surveys},
|
|
year = {2023},
|
|
volume = {55},
|
|
number = {9},
|
|
pages = {1--35},
|
|
doi = {10.1145/3560815}
|
|
}
|
|
|
|
@inproceedings{wei2022cot,
|
|
author = {Wei, Jason and Wang, Xuezhi and Schuurmans, Dale and Bosma, Maarten and Ichter, Brian and Xia, Fei and Chi, Ed and Le, Quoc and Zhou, Denny},
|
|
title = {Chain-of-Thought Prompting Elicits Reasoning in Large Language Models},
|
|
booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
|
|
year = {2022},
|
|
url = {https://arxiv.org/abs/2201.11903}
|
|
}
|