Hao Jiang

Orcid: 0000-0002-2306-7596

Affiliations:
  • Huawei, Distributed and Parallel Software Lab, Hangzhou, Beijing, China


According to our database1, Hao Jiang authored at least 25 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
An Analysis on Matching Mechanisms and Token Pruning for Late-interaction Models.
ACM Trans. Inf. Syst., September, 2024

Understanding Human Preferences: Towards More Personalized Video to Text Generation.
Proceedings of the ACM on Web Conference 2024, 2024

Image Retrieval with Composed Query by Multi-Scale Multi-Modal Fusion.
Proceedings of the IEEE International Conference on Acoustics, 2024

VEMO: A Versatile Elastic Multi-modal Model for Search-Oriented Multi-task Learning.
Proceedings of the Advances in Information Retrieval, 2024

2023
Going Beyond Closed Sets: A Multimodal Perspective for Video Emotion Analysis.
Proceedings of the Pattern Recognition and Computer Vision - 6th Chinese Conference, 2023

2022
PReGAN: Answer Oriented Passage Ranking with Weakly Supervised GAN.
CoRR, 2022

KMIR: A Benchmark for Evaluating Knowledge Memorization, Identification and Reasoning Abilities of Language Models.
CoRR, 2022

Webformer: Pre-training with Web Pages for Information Retrieval.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

BMU-MoCo: Bidirectional Momentum Update for Continual Video-Language Modeling.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Towards Efficient NLP: A Standard Evaluation and A Strong Baseline.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Multi-Modal Experience Inspired AI Creation.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Variance Reduction for Deep Q-Learning Using Stochastic Recursive Gradient.
Proceedings of the Neural Information Processing - 29th International Conference, 2022

Triple-Fact Retriever: An explainable reasoning retrieval model for multi-hop QA problem.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Visual Prompt Tuning for Few-Shot Text Classification.
Proceedings of the 29th International Conference on Computational Linguistics, 2022

Hyperlink-induced Pre-training for Passage Retrieval in Open-domain Question Answering.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Towards More Effective and Economic Sparsely-Activated Model.
CoRR, 2021

Towards Efficient NLP: A Standard Evaluation and A Strong Baseline.
CoRR, 2021

YES SIR!Optimizing Semantic Space of Negatives with Self-Involvement Ranker.
CoRR, 2021

Early Exiting with Ensemble Internal Classifiers.
CoRR, 2021

Emotion Eliciting Machine: Emotion Eliciting Conversation Generation based on Dual Generator.
CoRR, 2021

Proactive Retrieval-based Chatbots based on Relevant Knowledge and Goals.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Answer Complex Questions: Path Ranker Is All You Need.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Pre-training for Ad-hoc Retrieval: Hyperlink is Also You Need.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Contrastive Learning of User Behavior Sequence for Context-Aware Document Ranking.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Variance Reduction for Deep Q-Learning using Stochastic Recursive Gradient.
CoRR, 2020


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