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2020 – today
- 2024
[i12]Baohao Liao, Christof Monz:
ApiQ: Finetuning of 2-Bit Quantized Large Language Model. CoRR abs/2402.05147 (2024)- [i11]Baohao Liao, Christof Monz:
Is It a Free Lunch for Removing Outliers during Pretraining? CoRR abs/2402.12102 (2024) - [i10]Xinyi Chen, Baohao Liao, Jirui Qi, Panagiotis Eustratiadis, Christof Monz, Arianna Bisazza, Maarten de Rijke:
The SIFo Benchmark: Investigating the Sequential Instruction Following Ability of Large Language Models. CoRR abs/2406.19999 (2024) - [i9]Baohao Liao, Christian Herold, Shahram Khadivi, Christof Monz:
IKUN for WMT24 General MT Task: LLMs Are here for Multilingual Machine Translation. CoRR abs/2408.11512 (2024) - [i8]Baohao Liao, Christof Monz:
3-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability. CoRR abs/2409.00119 (2024) - 2023
- [c8]Baohao Liao, Yan Meng, Christof Monz:
Parameter-Efficient Fine-Tuning without Introducing New Latency. ACL (1) 2023: 4242-4260 - [c7]Quinten Bolding, Baohao Liao, Brandon James Denis, Jun Luo, Christof Monz:
Ask Language Model to Clean Your Noisy Translation Data. EMNLP (Findings) 2023: 3215-3236 - [c6]Baohao Liao, Shaomu Tan, Christof Monz:
Make Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning. NeurIPS 2023 - [i7]Baohao Liao, Yan Meng
, Christof Monz:
Parameter-Efficient Fine-Tuning without Introducing New Latency. CoRR abs/2305.16742 (2023) - [i6]Baohao Liao, Shaomu Tan, Christof Monz:
Make Your Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning. CoRR abs/2306.00477 (2023) - [i5]Quinten Bolding, Baohao Liao, Brandon James Denis, Jun Luo, Christof Monz:
Ask Language Model to Clean Your Noisy Translation Data. CoRR abs/2310.13469 (2023) - [i4]Baohao Liao, Michael Kozielski, Sanjika Hewavitharana, Jiangbo Yuan, Shahram Khadivi, Tomer Lancewicki:
ITEm: Unsupervised Image-Text Embedding Learning for eCommerce. CoRR abs/2311.02084 (2023) - 2022
- [c5]Baohao Liao, David Thulke, Sanjika Hewavitharana, Hermann Ney, Christof Monz:
Mask More and Mask Later: Efficient Pre-training of Masked Language Models by Disentangling the [MASK] Token. EMNLP (Findings) 2022: 1478-1492 - [i3]Mathis Bode, Michael Gauding, Jens Henrik Göbbert, Baohao Liao, Jenia Jitsev, Heinz Pitsch:
Towards prediction of turbulent flows at high Reynolds numbers using high performance computing data and deep learning. CoRR abs/2210.16110 (2022) - [i2]Baohao Liao, David Thulke, Sanjika Hewavitharana, Hermann Ney, Christof Monz:
Mask More and Mask Later: Efficient Pre-training of Masked Language Models by Disentangling the [MASK] Token. CoRR abs/2211.04898 (2022) - 2021
- [c4]Baohao Liao, Shahram Khadivi, Sanjika Hewavitharana:
Back-translation for Large-Scale Multilingual Machine Translation. WMT@EMNLP 2021: 418-424 - [i1]Baohao Liao, Shahram Khadivi, Sanjika Hewavitharana:
Back-translation for Large-Scale Multilingual Machine Translation. CoRR abs/2109.08712 (2021) - 2020
- [c3]Yingbo Gao, Baohao Liao, Hermann Ney:
Unifying Input and Output Smoothing in Neural Machine Translation. COLING 2020: 4361-4372 - [c2]Baohao Liao, Yingbo Gao, Hermann Ney:
Multi-Agent Mutual Learning at Sentence-Level and Token-Level for Neural Machine Translation. EMNLP (Findings) 2020: 1715-1724
2010 – 2019
- 2018
- [c1]Mathis Bode, Michael Gauding, Jens Henrik Göbbert, Baohao Liao, Jenia Jitsev, Heinz Pitsch:
Towards Prediction of Turbulent Flows at High Reynolds Numbers Using High Performance Computing Data and Deep Learning. ISC Workshops 2018: 614-623
Coauthor Index
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