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The growing capabilities of large language models in natural language understanding significantly strengthen existing agentic systems.
Roberta: A robustly optimized bert pretraining approach, 2019
Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., and Stoyanov, V · 1907
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ROUGE: A package for automatic evaluation of summaries
Lin, C.-Y · 2004
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LoRA: Low-rank adaptation of large language models
Hu, E. J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W · 2022
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Ugif: Ui grounded instruction following
Venkatesh, S. G., Talukdar, P., and Narayanan, S · 2022
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Self-instruct: Aligning language model with self generated instructions, 2022
Wang, Y., Kordi, Y., Mishra, S., Liu, A., Smith, N. A., Khashabi, D., and Hajishirzi, H · 2022
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React: Synergizing reasoning and acting in language models
Yao, S., Zhao, J., Yu, D., Du, N., Shafran, I., Narasimhan, K., and Cao, Y · 2022
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Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., Almeida, D., Altenschmidt, J., Altman, S., Anadkat, S., et al · 2023
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Bai, J., Bai, S., Chu, Y., Cui, Z., Dang, K., Deng, X., Fan, Y., Ge, W., Han, Y., Huang, F., et al · 2023
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Metagpt: Meta programming for multi-agent collaborative framework
Hong, S., Zheng, X., Chen, J., Cheng, Y., Wang, J., Zhang, C., Wang, Z., Yau, S. K. S., Lin, Z., Zhou, L., et al · 2023
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An llm compiler for parallel function calling
Kim, S., Moon, S., Tabrizi, R., Lee, N., Mahoney, M. W., Keutzer, K., and Gholami, A · 2023
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Towards general text embeddings with multi-stage contrastive learning
Li, Z., Zhang, X., Zhang, Y., Long, D., Xie, P., and Zhang, M · 2023
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Gorilla: Large language model connected with massive apis
Patil, S. G., Zhang, T., Wang, X., and Gonzalez, J. E · 2023
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Toolllm: Facilitating large language models to master 16000+ real-world apis
Qin, Y., Liang, S., Ye, Y., Zhu, K., Yan, L., Lu, Y., Lin, Y., Cong, X., Tang, X., Qian, B., et al · 2023
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Toolalpaca: Generalized tool learning for language models with 3000 simulated cases
Tang, Q., Deng, Z., Lin, H., Han, X., Liang, Q., Cao, B., and Sun, L · 2023
Cited alongside, same era.
Stanford alpaca: An instruction-following llama model
Taori, R., Gulrajani, I., Zhang, T., Dubois, Y., Li, X., Guestrin, C., Liang, P., and Hashimoto, T. B · 2023
Cited alongside, same era.
Enabling conversational interaction with mobile ui using large language models
Wang, B., Li, G., and Li, Y · 2023
Cited alongside, same era.
https://source.android.com/ , 2024
Aosp · 2024
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https://google.github.io/styleguide/pyguide.html#381-docstrings , 2024
Google-style docstrings · 2024
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https://developer.android.com/guide/components/intents-common , 2024
Tinyagent: Function calling at the edge
Erdogan, L. E., Lee, N., Jha, S., Kim, S., Tabrizi, R., Moon, S., Hooper, C., Anumanchipalli, G., Keutzer, K., and Gholami, A · 2024
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Chatglm: A family of large language models from glm-130b to glm-4 all tools
GLM, T., Zeng, A., Xu, B., Wang, B., Zhang, C., Yin, D., Zhang, D., Rojas, D., Feng, G., Zhao, H., et al · 2024
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Minicpm: Unveiling the potential of small language models with scalable training strategies
Hu, S., Tu, Y., Han, X., He, C., Cui, G., Long, X., Zheng, Z., Fang, Y., Huang, Y., Zhao, W., et al · 2024
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Personal llm agents: Insights and survey about the capability, efficiency and security
Li, Y., Wen, H., Wang, W., Li, X., Yuan, Y., Liu, G., Liu, J., Xu, W., Wang, X., Sun, Y., et al · 2024
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Common intents · 2024
Cited alongside, same era.
https://developer.android.com/ai/aicore , 2024
Google ai edge sdk for gemini nano · 2024
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https://developer.android.com/guide/components/intents-filters , 2024
Android developer guides · 2024
Cited alongside, same era.
https://developer.android.com/reference/android/content/Intent , 2024
intent · 2024
Cited alongside, same era.
https://github.com/objectbox/objectbox-java , 2024
Objectbox: Fast and efficient database with vector search · 2024
Cited alongside, same era.
Phi-3 technical report: A highly capable language model locally on your phone
Abdin, M., Jacobs, S. A., Awan, A. A., Aneja, J., Awadallah, A., Awadalla, H., Bach, N., Bahree, A., Bakhtiari, A., Behl, H., et al · 2024
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Octopus v2: On-device language model for super agent
Chen, W. and Li, Z · 2024
Cited alongside, same era.
Toolformer: Language models can teach themselves to use tools
Schick, T., Dwivedi-Yu, J., Dessì, R., Raileanu, R., Lomeli, M., Hambro, E., Zettlemoyer, L., Cancedda, N., and Scialom, T · 2024
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Gemma 2: Improving open language models at a practical size
Team, G., Riviere, M., Pathak, S., Sessa, P. G., Hardin, C., Bhupatiraju, S., Hussenot, L., Mesnard, T., Shahriari, B., Ramé, A., et al · 2024
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Qwen2.5: A party of foundation models, September 2024
Team, Q · 2024
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Autodroid: Llm-powered task automation in android
Wen, H., Li, Y., Liu, G., Zhao, S., Yu, T., Li, T. J.-J., Jiang, S., Liu, Y., Zhang, Y., and Liu, Y · 2024
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Yang, A., Yang, B., Hui, B., Zheng, B., Yu, B., Zhou, C., Li, C., Li, C., Liu, D., Huang, F., et al · 2024
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Phonelm:an efficient and capable small language model family through principled pre-training, 2024
Yi, R., Li, X., Xie, W., Lu, Z., Wang, C., Zhou, A., Wang, S., Zhang, X., and Xu, M · 2024
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Llm as a system service on mobile devices
Yin, W., Xu, M., Li, Y., and Liu, X · 2024
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Mobile foundation model as firmware
Yuan, J., Yang, C., Cai, D., Wang, S., Yuan, X., Zhang, Z., Li, X., Zhang, D., Mei, H., Jia, X., et al · 2024
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Deepseek-coder-v2: Breaking the barrier of closed-source models in code intelligence
Zhu, Q., Guo, D., Shao, Z., Yang, D., Wang, P., Xu, R., Wu, Y., Li, Y., Gao, H., Ma, S., et al · 2024
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