Search Results for author: Zhongyi Liu

Found 15 papers, 7 papers with code

SEMINAR: Search Enhanced Multi-modal Interest Network and Approximate Retrieval for Lifelong Sequential Recommendation

no code implementations15 Jul 2024 Kaiming Shen, Xichen Ding, Zixiang Zheng, Yuqi Gong, Qianqian Li, Zhongyi Liu, Guannan Zhang

To address these challenges, we propose a unified lifelong multi-modal sequence model called SEMINAR-Search Enhanced Multi-Modal Interest Network and Approximate Retrieval.

Click-Through Rate Prediction Quantization +2

Feature-based Low-Rank Compression of Large Language Models via Bayesian Optimization

1 code implementation17 May 2024 Yixin Ji, Yang Xiang, Juntao Li, Wei Chen, Zhongyi Liu, Kehai Chen, Min Zhang

To address the challenges of low-rank compression in LLMs, we conduct empirical research on the low-rank characteristics of large models.

Bayesian Optimization Low-rank compression

Multi-Intent Attribute-Aware Text Matching in Searching

no code implementations12 Feb 2024 Mingzhe Li, Xiuying Chen, Jing Xiang, Qishen Zhang, Changsheng Ma, Chenchen Dai, Jinxiong Chang, Zhongyi Liu, Guannan Zhang

Since attributes from two ends are often not aligned in terms of number and type, we propose to exploit the benefit of attributes by multiple-intent modeling.

Attribute Text Matching

A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval

1 code implementation5 Dec 2023 Xiaojie Sun, Keping Bi, Jiafeng Guo, Sihui Yang, Qishen Zhang, Zhongyi Liu, Guannan Zhang, Xueqi Cheng

Dense retrieval methods have been mostly focused on unstructured text and less attention has been drawn to structured data with various aspects, e. g., products with aspects such as category and brand.

Language Modelling Retrieval +1

Dual-Modal Attention-Enhanced Text-Video Retrieval with Triplet Partial Margin Contrastive Learning

1 code implementation20 Sep 2023 Chen Jiang, Hong Liu, Xuzheng Yu, Qing Wang, Yuan Cheng, Jia Xu, Zhongyi Liu, Qingpei Guo, Wei Chu, Ming Yang, Yuan Qi

We thereby present a new Triplet Partial Margin Contrastive Learning (TPM-CL) module to construct partial order triplet samples by automatically generating fine-grained hard negatives for matched text-video pairs.

Contrastive Learning Retrieval +3

An Unified Search and Recommendation Foundation Model for Cold-Start Scenario

no code implementations16 Sep 2023 Yuqi Gong, Xichen Ding, Yehui Su, Kaiming Shen, Zhongyi Liu, Guannan Zhang

With the development of large language models, LLM can extract global domain-invariant text features that serve both search and recommendation tasks.

Recommendation Systems Transfer Learning

Harnessing the Power of David against Goliath: Exploring Instruction Data Generation without Using Closed-Source Models

no code implementations24 Aug 2023 Yue Wang, Xinrui Wang, Juntao Li, Jinxiong Chang, Qishen Zhang, Zhongyi Liu, Guannan Zhang, Min Zhang

Instruction tuning is instrumental in enabling Large Language Models~(LLMs) to follow user instructions to complete various open-domain tasks.

Pre-training with Aspect-Content Text Mutual Prediction for Multi-Aspect Dense Retrieval

1 code implementation22 Aug 2023 Xiaojie Sun, Keping Bi, Jiafeng Guo, Xinyu Ma, Fan Yixing, Hongyu Shan, Qishen Zhang, Zhongyi Liu

Extensive experiments on two real-world datasets (product and mini-program search) show that our approach can outperform competitive baselines both treating aspect values as classes and conducting the same MLM for aspect and content strings.

Language Modelling Masked Language Modeling +1

Beyond Semantics: Learning a Behavior Augmented Relevance Model with Self-supervised Learning

1 code implementation10 Aug 2023 Zeyuan Chen, Wei Chen, Jia Xu, Zhongyi Liu, Wei zhang

Drawing inspiration from this, we devise a novel Behavior Augmented Relevance Learning model for Alipay Search (BARL-ASe) that leverages neighbor queries of target item and neighbor items of target query to complement target query-item semantic matching.

Self-Supervised Learning Semantic Similarity +1

VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs

1 code implementation4 Aug 2023 Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin Cui, Muhan Zhang, Jure Leskovec

To address this issue, we propose to learn a new powerful graph representation space by directly labeling nodes' diverse local structures for GNN-to-MLP distillation.

Knowledge Distillation Quantization +1

Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization

1 code implementation28 Jun 2023 Ling Yang, Jiayi Zheng, Heyuan Wang, Zhongyi Liu, Zhilin Huang, Shenda Hong, Wentao Zhang, Bin Cui

To remove class spurious feature caused by distribution shifts, we propose Individual Graph Information Bottleneck (I-GIB) which discards irrelevant information by minimizing the mutual information between the input graph and its embeddings.

Graph Learning Out-of-Distribution Generalization

GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning

no code implementations25 Apr 2023 Weifan Wang, Binbin Hu, Zhicheng Peng, Mingjie Zhong, Zhiqiang Zhang, Zhongyi Liu, Guannan Zhang, Jun Zhou

At last, we conduct extensive experiments on both offline and online environments, which demonstrates the superior capability of GARCIA in improving tail queries and overall performance in service search scenarios.

Contrastive Learning Transfer Learning

Automatic Expert Selection for Multi-Scenario and Multi-Task Search

no code implementations28 May 2022 Xinyu Zou, Zhi Hu, Yiming Zhao, Xuchu Ding, Zhongyi Liu, Chenliang Li, Aixin Sun

At each multi-scenario/multi-task layer, a novel expert selection algorithm is proposed to automatically identify scenario-/task-specific and shared experts for each input.

Multi-Task Learning

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