| The Language Barrier: Dissecting Safety Challenges of LLMs in Multilingual Contexts L Shen, W Tan, S Chen, Y Chen, J Zhang, H Xu, B Zheng, P Koehn, ... arXiv preprint arXiv:2401.13136, 2024 | 6 | 2024 |
| Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation H Xu, A Sharaf, Y Chen, W Tan, L Shen, B Van Durme, K Murray, YJ Kim ICML 2024, 2024 | 5 | 2024 |
| Multilingual Representation Distillation with Contrastive Learning W Tan, K Heffernan, H Schwenk, P Koehn EACL 2023, 2023 | 5 | 2023 |
| Bitext Mining for Low-Resource Languages via Contrastive Learning W Tan, P Koehn arXiv preprint arXiv:2208.11194, 2022 | 4 | 2022 |
| Narrowing the Gap between Zero-and Few-shot Machine Translation by Matching Styles W Tan, H Xu, L Shen, SS Li, K Murray, P Koehn, B Van Durme, Y Chen findings of NAACL 2024, 2023 | 1 | 2023 |
| Condensing Multilingual Knowledge with Lightweight Language-Specific Modules H Xu, W Tan, SS Li, Y Chen, B Van Durme, P Koehn, K Murray EMNLP 2023, 2023 | 1 | 2023 |
| Flatness-Aware Prompt Selection Improves Accuracy and Sample Efficiency L Shen, W Tan, B Zheng, D Khashabi findings of EMNLP 2023, 2023 | 1 | 2023 |
| Streaming Sequence Transduction through Dynamic Compression W Tan, Y Chen, T Chen, G Qin, H Xu, HC Zhang, B Van Durme, P Koehn arXiv preprint arXiv:2402.01172, 2024 | | 2024 |
| Structure-Aware Path Inference for Neural Finite State Transducers W Tan, C Lin, J Eisner NeurIPS (ICBINB workshop), 2023 | | 2023 |
| Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation W Tan, S Ding, H Khayrallah, P Koehn AMTA 2022, 2022 | | 2022 |
Philipp KoehnProfessor, Johns Hopkins UniversityBestätigte E-Mail-Adresse bei jhu.edu
