Search Results for author: Jinan Sun

Found 10 papers, 1 papers with code

When Parameter-efficient Tuning Meets General-purpose Vision-language Models

1 code implementation16 Dec 2023 Yihang Zhai, Haixin Wang, Jianlong Chang, Xinlong Yang, Jinan Sun, Shikun Zhang, Qi Tian

Instruction tuning has shown promising potential for developing general-purpose AI capabilities by using large-scale pre-trained models and boosts growing research to integrate multimodal information for creative applications.

Exploiting Pseudo Image Captions for Multimodal Summarization

no code implementations9 May 2023 Chaoya Jiang, Rui Xie, Wei Ye, Jinan Sun, Shikun Zhang

Cross-modal contrastive learning in vision language pretraining (VLP) faces the challenge of (partial) false negatives.

Common Sense Reasoning Contrastive Learning +1

LION: Implicit Vision Prompt Tuning

no code implementations17 Mar 2023 Haixin Wang, Jianlong Chang, Xiao Luo, Jinan Sun, Zhouchen Lin, Qi Tian

Despite recent competitive performance across a range of vision tasks, vision Transformers still have an issue of heavy computational costs.

Transfer Learning

Prototypical Mixing and Retrieval-Based Refinement for Label Noise-Resistant Image Retrieval

no code implementations ICCV 2023 Xinlong Yang, Haixin Wang, Jinan Sun, Shikun Zhang, Chong Chen, Xian-Sheng Hua, Xiao Luo

This paper investigates a realistic but understudied problem of image retrieval under label noise, which could lead to severe overfitting or memorization of noisy samples during optimization.

Image Retrieval Memorization +1

Frequency-Aware Contrastive Learning for Neural Machine Translation

no code implementations29 Dec 2021 Tong Zhang, Wei Ye, Baosong Yang, Long Zhang, Xingzhang Ren, Dayiheng Liu, Jinan Sun, Shikun Zhang, Haibo Zhang, Wen Zhao

Inspired by the observation that low-frequency words form a more compact embedding space, we tackle this challenge from a representation learning perspective.

Contrastive Learning Machine Translation +3

FSV: Learning to Factorize Soft Value Function for Cooperative Multi-Agent Reinforcement Learning

no code implementations1 Jan 2021 Yueheng Li, Tianhao Zhang, Chen Wang, Jinan Sun, Shikun Zhang, Guangming Xie

We explore energy-based solutions for cooperative multi-agent reinforcement learning (MARL) using the idea of function factorization in centralized training with decentralized execution (CTDE).

Multi-agent Reinforcement Learning reinforcement-learning +3

Deep Dynamic Boosted Forest

no code implementations19 Apr 2018 Haixin Wang, Xingzhang Ren, Jinan Sun, Wei Ye, Long Chen, Muzhi Yu, Shikun Zhang

Specically, we propose to measure the quality of each leaf node of every decision tree in the random forest to determine hard examples.

Ensemble Learning

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