Fetching the paper…
Reading the bibliography…
Many networking tasks now employ deep learning (DL) to solve complex prediction and optimization problems.
Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
Earlier work this paper cites.
Dl2: A deep learning-driven scheduler for deep learning clusters
Yanghua Peng, Yixin Bao, Yangrui Chen, Chuan Wu, Chen Meng, and Wei Lin. 2021 · 1960
Earlier work this paper cites.
Commute path bandwidth traces from 3G networks: analysis and applications. In Proceedings of the 2013 ACM Multimedia Systems Conference
Haakon Riiser, Paul Vigmostad, Carsten Griwodz, and Pål Halvorsen. 2013 · 2013
Earlier work this paper cites.
Multi-resource packing for cluster schedulers. In Proceedings of the 2014 ACM SIGCOMM Conference
Robert Grandl, Ganesh Ananthanarayanan, Srikanth Kandula, Sriram Rao, and Aditya Akella. 2014 · 2014
Earlier work this paper cites.
A buffer-based approach to rate adaptation: Evidence from a large video streaming service. In Proceedings of the 2014 ACM SIGCOMM Conference
Te-Yuan Huang, Ramesh Johari, Nick McKeown, Matthew Trunnell, and Mark Watson. 2014 · 2014
Earlier work this paper cites.
Probe and adapt: Rate adaptation for http video streaming at scale
Zhi Li, Xiaoqing Zhu, Joshua Gahm, Rong Pan, Hao Hu, Ali C Begen, and David Oran. 2014 · 2014
Earlier work this paper cites.
Towards the deployment of machine learning solutions in network traffic classification: A systematic survey
Fannia Pacheco, Ernesto Exposito, Mathieu Gineste, Cedric Baudoin, and Jose Aguilar. 2018 · 2014
Earlier work this paper cites.
Information-agnostic flow scheduling for commodity data centers. In 2015 USENIX Symposium on Networked Systems Design and Implementation (NSDI)
Wei Bai, Li Chen, Kai Chen, Dongsu Han, Chen Tian, and Hao Wang. 2015 · 2015
Earlier work this paper cites.
Mahimahi: accurate record-and-replay for http. In 2015 USENIX Annual Technical Conference (USENIX ATC)
Ravi Netravali, Anirudh Sivaraman, Somak Das, Ameesh Goyal, Keith Winstein, James Mickens, and Hari Balakrishnan. 2015 · 2015
Earlier work this paper cites.
A control-theoretic approach for dynamic adaptive video streaming over http. In Proceedings of the 2015 ACM SIGCOMM Conference
Xiaoqi Yin, Abhishek Jindal, Vyas Sekar, and Bruno Sinopoli. 2015 · 2015
Earlier work this paper cites.
Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton. 2016 · 2016
Earlier work this paper cites.
Workload characterization and optimization of TPC-H queries on Apache Spark. In 2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
Tatsuhiro Chiba and Tamiya Onodera. 2016 · 2016
Earlier work this paper cites.
Raw data - measuring broadband america
Federal Communications Commission. 2016 · 2016
Earlier work this paper cites.
Reference Client 2.4.0
DASH Industry Form. 2016 · 2016
Earlier work this paper cites.
Deep reinforcement learning with double q-learning. In Proceedings of the 2016 AAAI Conference on Artificial Intelligence
Hado Van Hasselt, Arthur Guez, and David Silver. 2016 · 2016
Earlier work this paper cites.
Deep learning with Keras
Antonio Gulli and Sujit Pal. 2017 · 2017
Earlier work this paper cites.
Neural adaptive video streaming with pensieve. In Proceedings of the 2017 ACM SIGCOMM Conference
Hongzi Mao, Ravi Netravali, and Mohammad Alizadeh. 2017 · 2017
Earlier work this paper cites.
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
A dataset for exploring user behaviors in VR spherical video streaming. In Proceedings of the 8th ACM on Multimedia Systems Conference
Chenglei Wu, Zhihao Tan, Zhi Wang, and Shiqiang Yang. 2017 · 2017
Earlier work this paper cites.
Copa: Practical delay-based congestion control for the internet. In 2018 USENIX Symposium on Networked Systems Design and Implementation (NSDI)
Venkat Arun and Hari Balakrishnan. 2018 · 2018
Earlier work this paper cites.
Auto: Scaling deep reinforcement learning for datacenter-scale automatic traffic optimization. In Proceedings of the 2018 ACM SIGCOMM Conference
Li Chen, Justinas Lingys, Kai Chen, and Feng Liu. 2018 · 2018
Earlier work this paper cites.
Flare: Practical viewport-adaptive 360-degree video streaming for mobile devices. In Proceedings of the 2018 ACM Annual International Conference on Mobile Computing and Networking
Feng Qian, Bo Han, Qingyang Xiao, and Vijay Gopalakrishnan. 2018 · 2018
Earlier work this paper cites.
Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto. 2018 · 2018
Earlier work this paper cites.
bandwidth prediction in low-latency chunked streaming. In Proceedings of the 2019 ACM Workshop on Network and Operating Systems Support for Digital Audio and Video
Abdelhak Bentaleb, Christian Timmerer, Ali C. Begen, and Roger Zimmermann. 2019 · 2019
Earlier work this paper cites.
Pano: Optimizing 360 ∘ video streaming with a better understanding of quality perception. In Proceedings of the 2019 ACM SIGCOMM Conference
Yu Guan, Chengyuan Zheng, Xinggong Zhang, Zongming Guo, and Junchen Jiang. 2019 · 2019
Earlier work this paper cites.
Learning scheduling algorithms for data processing clusters
Hongzi Mao, Malte Schwarzkopf, Shaileshh Bojja Venkatakrishnan, Zili Meng, and Mohammad Alizadeh. 2019 · 2019
Earlier work this paper cites.
Relational knowledge distillation. In Proceedings of the 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Wonpyo Park, Dongju Kim, Yan Lu, and Minsu Cho. 2019 · 2019
Earlier work this paper cites.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 2019
Earlier work this paper cites.
Classic meets modern: A pragmatic learning-based congestion control for the internet. In Proceedings of the 2020 ACM SIGCOMM Conference
Soheil Abbasloo, Chen-Yu Yen, and H Jonathan Chao. 2020 · 2020
Earlier work this paper cites.
An optimistic perspective on offline reinforcement learning. In Proceedings of the 2020 International Conference on Machine Learning
Rishabh Agarwal, Dale Schuurmans, and Mohammad Norouzi. 2020 · 2020
Earlier work this paper cites.
Intrinsic dimensionality explains the effectiveness of language model fine-tuning
Armen Aghajanyan, Luke Zettlemoyer, and Sonal Gupta. 2020 · 2020
Earlier work this paper cites.
Model compression and hardware acceleration for neural networks: A comprehensive survey
Lei Deng, Guoqi Li, Song Han, Luping Shi, and Yuan Xie. 2020 · 2020
Earlier work this paper cites.
Vivo: Visibility-aware mobile volumetric video streaming. In Proceedings of the 2020 ACM Annual International Conference on Mobile Computing and Networking
Bo Han, Yu Liu, and Feng Qian. 2020 · 2020
Earlier work this paper cites.
Offline reinforcement learning: Tutorial, review, and perspectives on open problems
Sergey Levine, Aviral Kumar, George Tucker, and Justin Fu. 2020 · 2020
Earlier work this paper cites.
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. In Advances in Neural Information Processing Systems
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2020 · 2020
Earlier work this paper cites.
Realtime mobile bandwidth prediction using lstm neural network and bayesian fusion
Lifan Mei, Runchen Hu, Houwei Cao, Yong Liu, Zifan Han, Feng Li, and Jin Li. 2020 · 2020
Earlier work this paper cites.
Interpreting deep learning-based networking systems. In Proceedings of the 2020 ACM SIGCOMM Conference
Zili Meng, Minhu Wang, Jiasong Bai, Mingwei Xu, Hongzi Mao, and Hongxin Hu. 2020 · 2020
Cited alongside, same era.
Improved knowledge distillation via teacher assistant. In Proceedings of the 2020 AAAI Conference on Artificial Intelligence
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Ang Li, Nir Levine, Akihiro Matsukawa, and Hassan Ghasemzadeh. 2020 · 2020
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
Cited alongside, same era.
Supervised learning in spiking neural networks: A review of algorithms and evaluations
Xiangwen Wang, Xianghong Lin, and Xiaochao Dang. 2020 · 2020
Cited alongside, same era.
A spherical convolution approach for learning long term viewport prediction in 360 immersive video. In Proceedings of the 2020 AAAI Conference on Artificial Intelligence
Parameter-efficient fine-tuning of large-scale pre-trained language models
Ning Ding, Yujia Qin, Guang Yang, Fuchao Wei, Zonghan Yang, Yusheng Su, Shengding Hu, Yulin Chen, Chi-Min Chan, Weize Chen, et al · 2023
Later among the works it cites.
Palm-e: An embodied multimodal language model
Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, and Pete Florence. 2023 · 2023
Later among the works it cites.
Sparsegpt: Massive language models can be accurately pruned in one-shot. In Proceedings of the 2023 International Conference on Machine Learning
Elias Frantar and Dan Alistarh. 2023 · 2023
Later among the works it cites.
Mme: A comprehensive evaluation benchmark for multimodal large language models
Chaoyou Fu, Peixian Chen, Yunhang Shen, Yulei Qin, Mengdan Zhang, Xu Lin, Jinrui Yang, Xiawu Zheng, Ke Li, Xing Sun, et al · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Chenglei Wu, Ruixiao Zhang, Zhi Wang, and Lifeng Sun. 2020 · 2020
Cited alongside, same era.
Learning in situ: A randomized experiment in video streaming. In 2020 USENIX Symposium on Networked Systems Design and Implementation (NSDI)
Francis Y Yan, Hudson Ayers, Chenzhi Zhu, Sadjad Fouladi, James Hong, Keyi Zhang, Philip Levis, and Keith Winstein. 2020 · 2020
Cited alongside, same era.
Wanna make your tcp scheme great for cellular networks? Let machines do it for you!
Soheil Abbasloo, Chen-Yu Yen, and H. Jonathan Chao. 2021 · 2021
Cited alongside, same era.
Ecco: An open source library for the explainability of transformer language models. In Proceedings of the 59th Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations
J Alammar. 2021 · 2021
Cited alongside, same era.
Decision transformer: Reinforcement learning via sequence modeling
Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Misha Laskin, Pieter Abbeel, Aravind Srinivas, and Igor Mordatch. 2021a · 2021
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby. 2021 · 2021
Cited alongside, same era.
Liveobj: Object semantics-based viewport prediction for live mobile virtual reality streaming
Xianglong Feng, Zeyang Bao, and Sheng Wei. 2021 · 2021
Cited alongside, same era.
Lora: Low-rank adaptation of large language models
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
Cited alongside, same era.
On the effectiveness of parameter-efficient fine-tuning
Zihao Fu, Haoran Yang, Anthony Man-Cho So, Wai Lam, Lidong Bing, and Nigel Collier. 2023b · 2023
Later among the works it cites.
netFound: Foundation Model for Network Security
Satyandra Guthula, Navya Battula, Roman Beltiukov, Wenbo Guo, and Arpit Gupta. 2023 · 2023
Later among the works it cites.
Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung. 2023 · 2023
Later among the works it cites.
Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2023 · 2023
Later among the works it cites.
Efficient memory management for large language model serving with pagedattention. In Proceedings of the 2023 ACM Symposium on Operating Systems Principles
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph Gonzalez, Hao Zhang, and Ion Stoica. 2023 · 2023
Later among the works it cites.
Halueval: A large-scale hallucination evaluation benchmark for large language models. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Junyi Li, Xiaoxue Cheng, Wayne Xin Zhao, Jian-Yun Nie, and Ji-Rong Wen. 2023a · 2023
Later among the works it cites.
Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi. 2023b · 2023
Later among the works it cites.
Chattwin: Toward automated digital twin generation for data center via large language models. In Proceedings of the 2023 ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
Minghao Li, Ruihang Wang, Xin Zhou, Zhaomeng Zhu, Yonggang Wen, and Rui Tan. 2023d · 2023
Later among the works it cites.
Evolutionary-scale prediction of atomic-level protein structure with a language model
Zeming Lin, Halil Akin, Roshan Rao, Brian Hie, Zhongkai Zhu, Wenting Lu, Nikita Smetanin, Robert Verkuil, Ori Kabeli, Yaniv Shmueli, Allan dos Santos Costa, Maryam Fazel-Zarandi, Tom Sercu, Salvatore Candido, and Alexander Rives. 2023 · 2023
Later among the works it cites.
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee. 2023c · 2023
Later among the works it cites.
Cav3: Cache-assisted viewport adaptive volumetric video streaming. In Proceedings of the 2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR)
Junhua Liu, Boxiang Zhu, Fangxin Wang, Yili Jin, Wenyi Zhang, Zihan Xu, and Shuguang Cui. 2023e · 2023
Later among the works it cites.
Chipnemo: Domain-adapted llms for chip design
Mingjie Liu, Teodor-Dumitru Ene, Robert Kirby, Chris Cheng, Nathaniel Pinckney, Rongjian Liang, Jonah Alben, Himyanshu Anand, Sanmitra Banerjee, Ismet Bayraktaroglu, Bonita Bhaskaran, Bryan Catanzaro, Arjun Chaudhuri, Sharon Clay, Bill Dally, Laura Dang, Parikshit Deshpande, Siddhanth Dhodhi, Sameer Halepete, Eric Hill, Jiashang Hu, Sumit Jain, Brucek Khailany, George Kokai, Kishor Kunal, Xiaowei Li, Charley Lind, Hao Liu, Stuart Oberman, Sujeet Omar, Sreedhar Pratty, Jonathan Raiman, Ambar Sarkar, Zhengjiang Shao, Hanfei Sun, Pratik P Suthar, Varun Tej, Walker Turner, Kaizhe Xu, and Haoxing Ren. 2023a · 2023
Later among the works it cites.
Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2023d · 2023
Later among the works it cites.
CacheGen: Fast Context Loading for Language Model Applications
Yuhan Liu, Hanchen Li, Kuntai Du, Jiayi Yao, Yihua Cheng, Yuyang Huang, Shan Lu, Michael Maire, Henry Hoffmann, Ari Holtzman, Ganesh Ananthanarayanan, and Junchen Jiang. 2023b · 2023
Later among the works it cites.
Netgpt: Generative pretrained transformer for network traffic
Xuying Meng, Chungang Lin, Yequan Wang, and Yujun Zhang. 2023 · 2023
Later among the works it cites.
Recent advances in natural language processing via large pre-trained language models: A survey
Bonan Min, Hayley Ross, Elior Sulem, Amir Pouran Ben Veyseh, Thien Huu Nguyen, Oscar Sainz, Eneko Agirre, Ilana Heintz, and Dan Roth. 2023 · 2023
Later among the works it cites.
OpenAI. 2023 · 2023
Later among the works it cites.
Guilherme Penedo, Quentin Malartic, Daniel Hesslow, Ruxandra Cojocaru, Alessandro Cappelli, Hamza Alobeidli, Baptiste Pannier, Ebtesam Almazrouei, and Julien Launay. 2023 · 2023
Later among the works it cites.
A survey on offline reinforcement learning: Taxonomy, review, and open problems
Rafael Figueiredo Prudencio, Marcos R. O. A. Maximo, and Esther Luna Colombini. 2023 · 2023
Later among the works it cites.
Gemini: a family of highly capable multimodal models
Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al · 2023
Later among the works it cites.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurelien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom. 2023 · 2023
Later among the works it cites.
Duo Wu, Panlong Wu, Miao Zhang, and Fangxin Wang. 2023 · 2023
Later among the works it cites.
The rise and potential of large language model based agents: A survey
Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, et al · 2023
Later among the works it cites.
A survey on model compression and acceleration for pretrained language models. In Proceedings of the 2023 AAAI Conference on Artificial Intelligence
Canwen Xu and Julian McAuley. 2023 · 2023
Later among the works it cites.
Computers Can Learn from the Heuristic Designs and Master Internet Congestion Control. In Proceedings of the 2023 ACM SIGCOMM Conference
Chen-Yu Yen, Soheil Abbasloo, and H Jonathan Chao. 2023 · 2023
Later among the works it cites.
Rt-2: Vision-language-action models transfer web knowledge to robotic control. In Proceedings of the 2023 PMLR Conference on Robot Learning (CoRL)
Brianna Zitkovich, Tianhe Yu, Sichun Xu, Peng Xu, Ted Xiao, Fei Xia, Jialin Wu, Paul Wohlhart, Stefan Welker, Ayzaan Wahid, Quan Vuong, Vincent Vanhoucke, Huong Tran, Radu Soricut, Anikait Singh, Jaspiar Singh, Pierre Sermanet, Pannag R. Sanketi, Grecia Salazar, Michael S. Ryoo, Krista Reymann, Kanishka Rao, Karl Pertsch, Igor Mordatch, Henryk Michalewski, Yao Lu, Sergey Levine, Lisa Lee, Tsang-Wei Edward Lee, Isabel Leal, Yuheng Kuang, Dmitry Kalashnikov, Ryan Julian, Nikhil J. Joshi, Alex Irpan, Brian Ichter, Jasmine Hsu, Alexander Herzog, Karol Hausman, Keerthana Gopalakrishnan, Chuyuan Fu, Pete Florence, Chelsea Finn, Kumar Avinava Dubey, Danny Driess, Tianli Ding, Krzysztof Marcin Choromanski, Xi Chen, Yevgen Chebotar, Justice Carbajal, Noah Brown, Anthony Brohan, Montserrat Gonzalez Arenas, and Kehang Han. 2023 · 2023
Later among the works it cites.
spark-sched-sim: An apache spark job scheduling simulator, implemented as a Gymnasium environment
Archie Gertsman. 2024 · 2024
Closest in time.
Evolving deep neural networks
Risto Miikkulainen, Jason Liang, Elliot Meyerson, Aditya Rawal, Dan Fink, Olivier Francon, Bala Raju, Hormoz Shahrzad, Arshak Navruzyan, Nigel Duffy, and Babak Hodjat. 2024 · 2024
Closest in time.
Unifying Large Language Models and Knowledge Graphs: A Roadmap
Shirui Pan, Linhao Luo, Yufei Wang, Chen Chen, Jiapu Wang, and Xindong Wu. 2024 · 2024
Closest in time.
Job Scheduling - Spark 3.5.0 Documentation
Apache Spark. 2024 · 2024
Closest in time.
Explainability for large language models: A survey
Haiyan Zhao, Hanjie Chen, Fan Yang, Ninghao Liu, Huiqi Deng, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, and Mengnan Du. 2024 · 2024
Closest in time.
Hao Zhou, Chengming Hu, Ye Yuan, Yufei Cui, Yili Jin, Can Chen, Haolun Wu, Dun Yuan, Li Jiang, Di Wu, et al · 2024
Closest in time.