Blog(1)

• GenDCI: Generative AI Empowered Scheduling and Light Downlink Control Information Design

  In 6G era, the tremendous devices and the emerging applications require the spectral efficiency improvement.

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Publications(5)

• Efficient Compositional Multi-tasking for On-device Large Language Models

  AuthorOndrej Bohdal, Mete Ozay, Jijoong Moon, Kyeng-Hun Lee, Hyeonmok Ko

  PublishedThe 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP)

  Date2025-11-04

• Network GDT: GenAI Based Digital Twin for Automated Network Performance Evaluation

  AuthorSukhdeep Singh, Swaraj Kumar, Moonki Hong, Ashish Jain, Madhan Raj Kanagarahinam

  PublishedIEEE International Conference on Communications (ICC)

  Date2025-09-26

• Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers

  AuthorJunhan Kim, Chungman Lee, Eulrang Cho, Kyungphil Park, Ho-young Kim, Joonyoung Kim, Yongkweon Jeon

  PublishedNeural Information Processing Systems (NeurIPS)

  Date2024-12-11

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News(8)

• [Blog] GenDCI: Generative AI Empowered Scheduling and Light Downlink Control Information Design

  In 6G era, the tremendous devices and the emerging applications require the spectral efficiency improvement.

• [Blog] Reimagining Wireless Channel Modeling with Generative AI

  Precise channel modeling has always been the cornerstone of wireless communication system design.

• [Blog] Efficient Compositional Multi-tasking for On-device Large Language Models

  Adapter parameters [2] provide a mechanism to modify the behaviour of machine learning models and have gained significant popularity in the context of large language models (LLMs) and generative AI.

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