Search Results for author: Zhangyin Feng

Found 15 papers, 5 papers with code

Emage: Non-Autoregressive Text-to-Image Generation

no code implementations22 Dec 2023 Zhangyin Feng, Runyi Hu, Liangxin Liu, Fan Zhang, Duyu Tang, Yong Dai, Xiaocheng Feng, Jiwei Li, Bing Qin, Shuming Shi

Compared with autoregressive baselines that needs to run one thousand times, our model only runs 16 times to generate images of competitive quality with an order of magnitude lower inference latency.

Denoising Text-to-Image Generation

Trends in Integration of Knowledge and Large Language Models: A Survey and Taxonomy of Methods, Benchmarks, and Applications

no code implementations10 Nov 2023 Zhangyin Feng, Weitao Ma, Weijiang Yu, Lei Huang, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, Ting Liu

In this paper, we propose a review to discuss the trends in integration of knowledge and large language models, including taxonomy of methods, benchmarks, and applications.

knowledge editing Retrieval

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

1 code implementation9 Nov 2023 Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, Ting Liu

The emergence of large language models (LLMs) has marked a significant breakthrough in natural language processing (NLP), leading to remarkable advancements in text understanding and generation.


Retrieval-Generation Synergy Augmented Large Language Models

1 code implementation8 Oct 2023 Zhangyin Feng, Xiaocheng Feng, Dezhi Zhao, Maojin Yang, Bing Qin

Large language models augmented with task-relevant documents have demonstrated impressive performance on knowledge-intensive tasks.

Question Answering Retrieval

SkillNet-X: A Multilingual Multitask Model with Sparsely Activated Skills

no code implementations28 Jun 2023 Zhangyin Feng, Yong Dai, Fan Zhang, Duyu Tang, Xiaocheng Feng, Shuangzhi Wu, Bing Qin, Yunbo Cao, Shuming Shi

Traditional multitask learning methods basically can only exploit common knowledge in task- or language-wise, which lose either cross-language or cross-task knowledge.

Natural Language Understanding

Improved Visual Story Generation with Adaptive Context Modeling

no code implementations26 May 2023 Zhangyin Feng, Yuchen Ren, Xinmiao Yu, Xiaocheng Feng, Duyu Tang, Shuming Shi, Bing Qin

Diffusion models developed on top of powerful text-to-image generation models like Stable Diffusion achieve remarkable success in visual story generation.

Story Generation Story Visualization +1

One Model, Multiple Modalities: A Sparsely Activated Approach for Text, Sound, Image, Video and Code

no code implementations12 May 2022 Yong Dai, Duyu Tang, Liangxin Liu, Minghuan Tan, Cong Zhou, Jingquan Wang, Zhangyin Feng, Fan Zhang, Xueyu Hu, Shuming Shi

Moreover, our model supports self-supervised pretraining with the same sparsely activated way, resulting in better initialized parameters for different modalities.

Image Retrieval Retrieval

Pretraining Chinese BERT for Detecting Word Insertion and Deletion Errors

no code implementations26 Apr 2022 Cong Zhou, Yong Dai, Duyu Tang, Enbo Zhao, Zhangyin Feng, Li Kuang, Shuming Shi

We achieve this by introducing a special token \texttt{[null]}, the prediction of which stands for the non-existence of a word.

Language Modelling Masked Language Modeling +1

GraphCodeBERT: Pre-training Code Representations with Data Flow

1 code implementation ICLR 2021 Daya Guo, Shuo Ren, Shuai Lu, Zhangyin Feng, Duyu Tang, Shujie Liu, Long Zhou, Nan Duan, Alexey Svyatkovskiy, Shengyu Fu, Michele Tufano, Shao Kun Deng, Colin Clement, Dawn Drain, Neel Sundaresan, Jian Yin, Daxin Jiang, Ming Zhou

Instead of taking syntactic-level structure of code like abstract syntax tree (AST), we use data flow in the pre-training stage, which is a semantic-level structure of code that encodes the relation of "where-the-value-comes-from" between variables.

Clone Detection Code Completion +7

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