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20232026
most citedTuning Large language model for End-to-end Speech Translation

2 citations · 2 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.CL2024

MPN: Leveraging Multilingual Patch Neuron for Cross-lingual Model Editing

Nianwen Si, Hao Zhang, Weiqiang Zhang

Large language models are known for encoding a vast amount of factual knowledge, but they often becomes outdated due to the ever-changing nature of external information. A promisin…

cs.CL2023

Knowledge Unlearning for LLMs: Tasks, Methods, and Challenges

Nianwen Si, Hao Zhang, Heyu Chang +3

In recent years, large language models (LLMs) have spurred a new research paradigm in natural language processing. Despite their excellent capability in knowledge-based question an…

cs.CL20232 cited

Tuning Large language model for End-to-end Speech Translation

Hao Zhang, Nianwen Si, Yaqi Chen +4

With the emergence of large language models (LLMs), multimodal models based on LLMs have demonstrated significant potential. Models such as LLaSM, X-LLM, and SpeechGPT exhibit an i…

cs.CL202318 cited

Improving Speech Translation by Cross-Modal Multi-Grained Contrastive Learning

Hao Zhang, Nianwen Si, Yaqi Chen +4

The end-to-end speech translation (E2E-ST) model has gradually become a mainstream paradigm due to its low latency and less error propagation. However, it is non-trivial to train s…

cs.CL2023

Decouple Non-parametric Knowledge Distillation For End-to-end Speech Translation

Hao Zhang, Nianwen Si, Yaqi Chen +4

Existing techniques often attempt to make knowledge transfer from a powerful machine translation (MT) to speech translation (ST) model with some elaborate techniques, which often r…