Papers by Wuyang Zhou
TeRA: Vector-based Random Tensor Network for High-Rank Adaptation of Large Language Models (2026.acl-long)
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| Challenge: | Low-Rank Adaptation (LoRA) methods have significantly reduced the number of trainable parameters needed in fine-tuning large language models. |
| Approach: | They propose a vector-based random Tensor network for high-Rank Adaptation method that achieves high-rank weight updates while retaining parameter efficiency. |
| Outcome: | The proposed method outperforms existing PEFT methods while keeping low-rank parameters. |