no code implementations • 24 May 2024 • Jingcheng Deng, Zihao Wei, Liang Pang, Hanxing Ding, HuaWei Shen, Xueqi Cheng
Firstly, in the layer dimension, we discard the "knowledge locating" step and treat first few layers as the key, which expand knowledge storage through layers to break the "knowledge stored locally" assumption.
2 code implementations • 7 Apr 2024 • Zihao Wei, Jingcheng Deng, Liang Pang, Hanxing Ding, HuaWei Shen, Xueqi Cheng
We evaluate the multilingual knowledge editing generalization capabilities of existing methods on MLaKE.
1 code implementation • 20 Feb 2024 • Zihao Wei, Liang Pang, Hanxing Ding, Jingcheng Deng, HuaWei Shen, Xueqi Cheng
The premise of localization results in an incomplete knowledge editing, whereas an isolated assumption may impair both other knowledge and general abilities.
1 code implementation • 23 Nov 2023 • Shicheng Xu, Danyang Hou, Liang Pang, Jingcheng Deng, Jun Xu, HuaWei Shen, Xueqi Cheng
Furthermore, our subsequent exploration reveals that the inclusion of AI-generated images in the training data of the retrieval models exacerbates the invisible relevance bias.
1 code implementation • 16 Oct 2023 • Jingcheng Deng, Liang Pang, HuaWei Shen, Xueqi Cheng
It encodes the text corpus into a latent space, capturing current and future information from both source and target text.
1 code implementation • 1 Dec 2022 • Jingcheng Deng, Hengwei Dai, Xuewei Guo, Yuanchen Ju, Wei Peng
URR aims to implicitly extract dependencies between utterances, as well as utterances and options, and make reasoning with relational graph convolutional networks.