Search Results for author: Zexuan Qiu

Found 6 papers, 3 papers with code

Contrastive Quantization based Semantic Code for Generative Recommendation

no code implementations23 Apr 2024 mengqun Jin, Zexuan Qiu, Jieming Zhu, Zhenhua Dong, Xiu Li

Finally, we train and test semantic code with with generative retrieval on a sequential recommendation model.

Decoder Language Modelling +3

CLongEval: A Chinese Benchmark for Evaluating Long-Context Large Language Models

1 code implementation6 Mar 2024 Zexuan Qiu, Jingjing Li, Shijue Huang, Wanjun Zhong, Irwin King

Developing Large Language Models (LLMs) with robust long-context capabilities has been the recent research focus, resulting in the emergence of long-context LLMs proficient in Chinese.

HiHPQ: Hierarchical Hyperbolic Product Quantization for Unsupervised Image Retrieval

no code implementations14 Jan 2024 Zexuan Qiu, Jiahong Liu, Yankai Chen, Irwin King

Existing unsupervised deep product quantization methods primarily aim for the increased similarity between different views of the identical image, whereas the delicate multi-level semantic similarities preserved between images are overlooked.

Contrastive Learning Image Retrieval +4

Learning Summary-Worthy Visual Representation for Abstractive Summarization in Video

no code implementations8 May 2023 Zenan Xu, Xiaojun Meng, Yasheng Wang, Qinliang Su, Zexuan Qiu, Xin Jiang, Qun Liu

Multimodal abstractive summarization for videos (MAS) requires generating a concise textual summary to describe the highlights of a video according to multimodal resources, in our case, the video content and its transcript.

Abstractive Text Summarization Language Modelling

Efficient Document Retrieval by End-to-End Refining and Quantizing BERT Embedding with Contrastive Product Quantization

1 code implementation31 Oct 2022 Zexuan Qiu, Qinliang Su, Jianxing Yu, Shijing Si

Efficient document retrieval heavily relies on the technique of semantic hashing, which learns a binary code for every document and employs Hamming distance to evaluate document distances.

Quantization Retrieval

Unsupervised Hashing with Contrastive Information Bottleneck

1 code implementation13 May 2021 Zexuan Qiu, Qinliang Su, Zijing Ou, Jianxing Yu, Changyou Chen

Many unsupervised hashing methods are implicitly established on the idea of reconstructing the input data, which basically encourages the hashing codes to retain as much information of original data as possible.

Contrastive Learning

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