(* means corresponding author)

Preprints

[R1] BufferGA:Buffer-based Gradient Adjustment for Continual Federated Learning
          S. Dai, B. Chen, J. Sohn, S. Alam, R. Balakrishnan, S. Banerjee, N, Himayat and K. Lee
          Under review (preliminary version accepted in MLSys 2023 Workshop)

Conferences (AI/ML)

[A12] Memorization Capacity for Additive Fine-Tuning [arxiv]
              J. Sohn, D. Kwon, S. An and K. Lee
              UAI 2024

[A11] Analysis of Using Sigmoid Loss for Contrastive Learning [arxiv]
              C. Lee, J. Chang and J. Sohn*
              AISTATS 2024

[A10] Looped Transformers as Programmable Computers  [arxiv]
              A. Giannou, S. Rajput, J. Sohn, K. Lee, J. D. Lee and D. Papailiopoulos
              ICML 2023

[A9] Equal Improvability: A New Fairness Notion Considering the Long-term Impact [arxiv] [github]
          O. Guldogan, Y. Zeng, J. Sohn, R. Pedarsani, K. Lee
          ICLR 2023

[A8] Can We Find Strong Lottery Tickets in Generative Models? [project page]
          S. Yeo, Y. Jang, J. Sohn, D. Han and J. Yoo
          AAAI 2023

[A7] Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment [arxiv] [twitter] [github]
          T. Dinh, J. Sohn, S. Rajput, T. Ossowski, Y. Ming, J. Hu, D. Papailiopoulos and K. Lee
          Findings of EMNLP 2022

[A6] LIFT: Language-Interfaced FineTuning for Non-Language Machine Learning Tasks [arxiv] [twitter] [github]
          T. Dinh, Y. Zeng, R. Zhang, Z. Lin, M. Gira, S. Rajput, J. Sohn, D. Papailiopoulos and K. Lee
          NeurIPS 2022 

[A5] Rare Gems: Finding Lottery Tickets at Initialization [arxiv] [twitter]
          K. Sreenivasan, J. Sohn, L. Yang, M. Grinde, A. Nagle, H. Wang, K. Lee and D. Papailiopoulos
          NeurIPS 2022

[A4] GenLabel: Mixup Relabeling using Generative Models [arxiv] [github]
          J. Sohn, L. Shang, H. Chen, J. Moon, D. Papailiopoulos and K. Lee
          ICML 2022 

[A3] Finding Everything within Random Binary Networks
          K. Sreenivasan, S. Rajput, J. Sohn and D. Papailiopoulos
          AISTATS 2022

[A2] Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks
          J. Sohn, D. -J. Han, B. Choi, and J. Moon
          NeurIPS 2020

[A1] Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
          H. Wang, K. Sreenivasan, S. Rajput, H. Vishwakarma, S. Agarwal, J. Sohn, K. Lee, and D. Papailiopoulos
          NeurIPS 2020

[W7] Can Separators Improve Chain-of-Thought Prompting? [arxiv]
          Y. Park, H. Kim, C. Choi, J. Kim and J. Sohn*
          IEEE International Conference on Foundation and Large Language Models (FLLM)

[W6] Improving Multi-lingual Alignment Through Soft Contrastive Learning
          M. Park, S. Choi, C. Choi, J. Kim* and J. Sohn*
          NAACL 2024 Workshop

[W5] ERD: A Framework for Improving LLM Reasoning for Cognitive Distortion Classification [arxiv]
          S. Lim, Y. Kim, C.-H. Choi, J. Sohn* and B.-H. Kim*
          NAACL 2024 Workshop

[W4] Re-Ex: Revising after Explanation Reduces the Factual Errors in LLM Responses [arxiv]
          J. Kim, J. Lee, Y. Chang, C. Choi, J. Kim* and J. Sohn*
          ICLR 2024 Workshop

[W3] Retrieval-based Evaluation for LLMs: A Case Study in Korean Legal QA [paper]
          C. Ryu, S. Lee, S. Pang, C. Choi, H. Choi, M. Min and J. Sohn*
          EMNLP 2023 Workshop

[W2] Super Seeds: Extreme Model Compression by Trading off Storage and Computation
          N. Lee, J. Sohn, S. Rajput, H. Wang, A. Nagle, E. P. Xing, K. Lee, and D. Papailiopoulos
          ICML 2022 Workshop (spotlight)

[W1] GAN-mixup: Augmenting Across Data Manifolds for Improved Robustness
          J. Sohn, K. Lee, J. Moon and D. Papailiopoulos
          ICML 2020 Workshop 

Journals 

[J9] Aligning Large Language Models for Enhancing Psychiatric Interviews through Symptom Delineation and Summarization [arxiv] [github]
          J. So, J. Chang, E. Kim, J. Na, J. Choi, J. Sohn*, B.-H. Kim* and S. H. Chu*
          JMIR Formative Research, accepted at Oct., 2024.

[J8] Mini-Batch Optimization of Contrastive Loss [arxiv] [github]
          J. Cho, K. Sreenivasan, K. Lee, K. Mun, S. Yi, J.-G. Lee, A. Lee, J. Sohn, D. Papailiopoulos and K. Lee
          Transactions on Machine Learning Research (preliminary version accepted in ICLR 2023 Workshop), accepted at July, 2024.

[J7] Coded Wireless Distributed Computing with Packet Losses and Retransmissions
          D. -J. Han, J. Sohn, and J. Moon
          IEEE Transactions on Wireless Communications, vol. 20, no.12, pp. 8204-8217, Dec.2021.

[J6] Hierarchical Broadcast Coding: Expediting Distributed Learning at the Wireless Edge
          D. -J. Han, J. Sohn and J. Moon
          IEEE Transactions on Wireless Communications, vol. 20, no. 4, pp. 2266-2281, Apr. 2021. 

[J5] Secure clustered distributed storage against eavesdropping
          B. Choi, J. Sohn, S. W. Yoon and J. Moon
          IEEE Transactions on Information Theory, vol. 65, no. 11, pp. 7646-7668, Nov. 2019. 

[J4] Capacity of Clustered Distributed Storage
          J. Sohn, B. Choi, S. W. Yoon and J. Moon
          IEEE Transactions on Information Theory, vol. 65, no. 1, pp. 81-107, Jan. 2019.
          (conference version won the Best Paper Award)

[J3] Combined Window-Filter Waveform Design with Transmitter-Side Channel State Information
          D. -J. Han, J. Moon, J. Sohn, S. Jo and J. Kim
          IEEE Transactions on Vehicular Technology, May. 2018. 

[J2] On Reusing Pilots Across Interfering Cells in Massive MIMO
          J. Sohn, S. W. Yoon and J. Moon
          IEEE Transactions on Wireless Communications, vol. 16, no. 12, pp. 8092-8104, Dec. 2017.

[J1] Pilot Reuse Strategy Maximizing the Weighted-Sum-Rate in Massive MIMO Systems
          J. Sohn, S. W. Yoon and J. Moon
          IEEE Journal on Selected Areas in Communications, vol. 35, no. 8, pp. 1728-1740, Aug. 2017.

Conferences (Communications)

[C10] Breaking Fair Binary Classification with Optimal Flipping Attacks [arxiv]
              C. Jo, J. Sohn and K. Lee
              ISIT 2022

[C9] TiBroco: A Fast and Secure Distributed Learning Framework for Tiered Wireless Edge Networks
          D. -J. Han, J. Sohn and J. Moon
          IEEE INFOCOM 2021

[C8] Scalable Network-Coded PBFT Consensus Algorithm
          B. Choi, J. Sohn, D. -J. Han and J. Moon
          IEEE ISIT 2019

[C7] Coded Distributed Computing over Packet Erasure Channels
          D. -J. Han, J. Sohn and J. Moon
          IEEE ISIT 2019

[C6] Coded Matrix Multiplication on a Group-Based Model
          M. Kim, J. Sohn and J. Moon
          IEEE ISIT 2019

[C5] A Class of MSR Codes for Clustered Distributed Storage
          J. Sohn, B. Choi and J. Moon
          IEEE ISIT 2018

[C4] Hierarchical Coding for Distributed Computing
          H. Park, K. Lee, J. Sohn, C. Suh and J. Moon
          IEEE ISIT 2018

[C3] Capacity of Clustered Distributed Storage
          J. Sohn, B. Choi, S. W. Yoon and J. Moon
          IEEE ICC 2017
          won the Best Paper Award of the conference [ppt slides]

[C2] Secure Clustered Distributed Storage Against Eavesdroppers
          B. Choi, J. Sohn, S. W. Yoon and J. Moon
          IEEE ICC 2017

[C1] When pilots should not be reused across interfering cells in massive MIMO
          J. Sohn, S. W. Yoon and J. Moon
          IEEE ICC 2015 Workshop on 5G & Beyond

Patents

[KR4] Agreed Data Transmit Method and Apparatus for Transmitting the Agreed Data in Network
              J. Moon, B. Choi, J. Sohn and D. -J. Han
              10-2019-0071909

[KR3] Complete Safety Encoding Method using Minimum Bandwidth based on Clustered Dispersion Storage System
              J. Moon, B. Choi and J. Sohn
              10-2018-0070803

[KR2] Minimum Bandwidth Recovery Encoding Method based on Clustered Dispersion Storage System
              J. Moon and J. Sohn
              10-2018-0070802

[KR1] Pilot Assignment Method on Multi-cell Massive MIMO System
              J. Moon, J. Sohn and S. W. Yoon
              10-2015-0150928