no code implementations • 30 May 2024 • Zhuang Qi, Lei Meng, Weihao He, Ruohan Zhang, Yu Wang, Xin Qi, Xiangxu Meng
Federated learning benefits from cross-training strategies, which enables models to train on data from distinct sources to improve the generalization capability.
no code implementations • 25 May 2024 • Yun Zhu, Jia-Chen Gu, Caitlin Sikora, Ho Ko, Yinxiao Liu, Chu-Cheng Lin, Lei Shu, Liangchen Luo, Lei Meng, Bang Liu, Jindong Chen
However, the input length grows linearly in the number of retrieved documents, causing a dramatic increase in latency.
no code implementations • 22 Apr 2024 • Yihang Wu, Xiao Cao, Kaixin Li, Zitan Chen, Haonan Wang, Lei Meng, Zhiyong Huang
To achieve this, we incorporate a temperature control mechanism within the early phases of the self-attention modules to mitigate entity leakage issues.
no code implementations • 14 Jan 2024 • Meng Cao, Lei Shu, Lei Yu, Yun Zhu, Nevan Wichers, Yinxiao Liu, Lei Meng
We investigate this approach under two different settings: one where the policy model is smaller and is paired with a more powerful critic model, and another where a single language model fulfills both roles.
1 code implementation • 5 Jan 2024 • Haokai Ma, Ruobing Xie, Lei Meng, Xin Chen, Xu Zhang, Leyu Lin, Zhanhui Kang
To address this issue, this paper presents a novel Plug-in Diffusion Model for Recommendation (PDRec) framework, which employs the diffusion model as a flexible plugin to jointly take full advantage of the diffusion-generating user preferences on all items.
no code implementations • 15 Nov 2023 • Yun Zhu, Nevan Wichers, Chu-Cheng Lin, Xinyi Wang, Tianlong Chen, Lei Shu, Han Lu, Canoee Liu, Liangchen Luo, Jindong Chen, Lei Meng
Parameter Efficient Tuning has been an prominent approach to adapt the Large Language Model to downstream tasks.
no code implementations • 15 Nov 2023 • Lei Shu, Nevan Wichers, Liangchen Luo, Yun Zhu, Yinxiao Liu, Jindong Chen, Lei Meng
Evaluating natural language systems poses significant challenges, particularly in the realms of natural language understanding and high-level reasoning.
no code implementations • 7 Oct 2023 • Liangchen Luo, Zi Lin, Yinxiao Liu, Lei Shu, Yun Zhu, Jingbo Shang, Lei Meng
In the era of large language models (LLMs), this study explores the ability of LLMs to deliver accurate critiques across various tasks.
no code implementations • 22 Aug 2023 • Yun Zhu, Yinxiao Liu, Felix Stahlberg, Shankar Kumar, Yu-Hui Chen, Liangchen Luo, Lei Shu, Renjie Liu, Jindong Chen, Lei Meng
Large Language Models (LLMs) have demonstrated impressive capabilities for text rewriting.
1 code implementation • 8 Aug 2023 • Zitan Chen, Zhuang Qi, Xiao Cao, Xiangxian Li, Xiangxu Meng, Lei Meng
Representation learning for images has been advanced by recent progress in more complex neural models such as the Vision Transformers and new learning theories such as the structural causal models.
1 code implementation • 7 Aug 2023 • Zhuang Qi, Lei Meng, Zitan Chen, Han Hu, Hui Lin, Xiangxu Meng
To address this issue, this paper presents a cross-silo prototypical calibration method (FedCSPC), which takes additional prototype information from the clients to learn a unified feature space on the server side.
1 code implementation • 25 May 2023 • Lei Shu, Liangchen Luo, Jayakumar Hoskere, Yun Zhu, Yinxiao Liu, Simon Tong, Jindong Chen, Lei Meng
In this work, we develop new strategies for instruction tuning and reinforcement learning to better align LLMs for cross-sentence rewriting tasks using diverse wording and structures expressed through natural languages including 1) generating rewriting instruction data from Wiki edits and public corpus through instruction generation and chain-of-thought prompting; 2) collecting comparison data for reward model training through a new ranking function.
no code implementations • 11 Apr 2023 • Haokai Ma, Ruobing Xie, Lei Meng, Xin Chen, Xu Zhang, Leyu Lin, Jie zhou
To address this issue, we present a novel framework, termed triple sequence learning for cross-domain recommendation (Tri-CDR), which jointly models the source, target, and mixed behavior sequences to highlight the global and target preference and precisely model the triple correlation in CDR.
1 code implementation • 26 Sep 2022 • Xiao Cao, Zitan Chen, Canyu Le, Lei Meng
On top of this dataset, we design an effective baseline specificlly for video chapters generation task.
no code implementations • 22 Aug 2022 • Yuqing Wang, Xiangxian Li, Zhuang Qi, Jingyu Li, Xuelong Li, Xiangxu Meng, Lei Meng
Causal inference has become a powerful tool to handle the out-of-distribution (OOD) generalization problem, which aims to extract the invariant features.
no code implementations • 12 Jan 2020 • Chuang Lin, Sicheng Zhao, Lei Meng, Tat-Seng Chua
Existing domain adaptation methods on visual sentiment classification typically are investigated under the single-source scenario, where the knowledge learned from a source domain of sufficient labeled data is transferred to the target domain of loosely labeled or unlabeled data.
no code implementations • 13 Sep 2017 • Vipin Vijayan, Shawn Gu, Eric Krebs, Lei Meng, Tijana Milenkovic
Just as the recent trend in the NA field, we also focus on global NA, which can be pairwise (PNA) and multiple (MNA).