E-LIB Suche - Ergebnisse für: Mao, Kelong

1

ConvSDG: Session Data Generation for Conversational Search:

, In: Companion Proceedings of the ACM on Web Conference 2024,

Mo, Fengran ; Yi, Bole ; Mao, Kelong... - p. 1634-1642 , 2024

Link: https://dl.acm.org/doi/1..

2

Learning to Relate to Previous Turns in Conversational Sear..:

, In: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,

Mo, Fengran ; Nie, Jian-Yun ; Huang, Kaiyu... - p. 1722-1732 , 2023

Link: https://dl.acm.org/doi/1..

3

Learning Denoised and Interpretable Session Representation ..:

, In: Proceedings of the ACM Web Conference 2023,

Mao, Kelong ; Qian, Hongjin ; Mo, Fengran... - p. 3193-3202 , 2023

Link: https://dl.acm.org/doi/1..

4

Curriculum Contrastive Context Denoising for Few-shot Conve..:

, In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval,

Mao, Kelong ; Dou, Zhicheng ; Qian, Hongjin - p. 176-186 , 2022

Link: https://dl.acm.org/doi/1..

5

SimpleX : A Simple and Strong Baseline for Collaborative..:

, In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management,

Mao, Kelong ; Zhu, Jieming ; Wang, Jinpeng... - p. 1243-1252 , 2021

Link: https://dl.acm.org/doi/1..

6

Byte-Label Joint Attention Learning for Packet-grained Netw..:

, In: 2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS),

Mao, Kelong ; Xiao, Xi ; Hu, Guangwu... - p. 1-10 , 2021

Link: https://doi.org/10.1109/..

7

Molecular graph enhanced transformer for retrosynthesis pre..:

Mao, Kelong ; Xiao, Xi ; Xu, Tingyang...
Neurocomputing. 457 (2021) - p. 193-202 , 2021

Link: https://doi.org/10.1016/..

8

UltraGCN : Ultra Simplification of Graph Convolutional N..:

, In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management,

Mao, Kelong ; Zhu, Jieming ; Xiao, Xi... - p. 1253-1262 , 2021

Link: https://dl.acm.org/doi/1..

9

Item Tagging for Information Retrieval: A Tripartite Graph ..:

, In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval,

Mao, Kelong ; Xiao, Xi ; Zhu, Jieming... - p. 2327-2336 , 2020

Link: https://dl.acm.org/doi/1..

10

History-Aware Conversational Dense Retrieval:

Mo, Fengran ; Qu, Chen ; Mao, Kelong...
http://arxiv.org/abs/2401.16659. , 2024

Link: http://arxiv.org/abs/240..

11

Learning to Relate to Previous Turns in Conversational Sear..:

Mo, Fengran ; Nie, Jian-Yun ; Huang, Kaiyu...
http://arxiv.org/abs/2306.02553. , 2023

Link: http://arxiv.org/abs/230..

12

ConvGQR: Generative Query Reformulation for Conversational ..:

Mo, Fengran ; Mao, Kelong ; Zhu, Yutao...
http://arxiv.org/abs/2305.15645. , 2023

Link: http://arxiv.org/abs/230..

13

Large Language Models Know Your Contextual Search Intent: A..:

Mao, Kelong ; Dou, Zhicheng ; Mo, Fengran...
http://arxiv.org/abs/2303.06573. , 2023

Link: http://arxiv.org/abs/230..

14

FinalMLP: An Enhanced Two-Stream MLP Model for CTR Predicti..:

Mao, Kelong ; Zhu, Jieming ; Su, Liangcai...
http://arxiv.org/abs/2304.00902. , 2023

Link: http://arxiv.org/abs/230..

15

SimpleX: A Simple and Strong Baseline for Collaborative Fil..:

Mao, Kelong ; Zhu, Jieming ; Wang, Jinpeng...
http://arxiv.org/abs/2109.12613. , 2021

Link: http://arxiv.org/abs/210..