Search Results for author: Zecheng Tang

Found 18 papers, 15 papers with code

OmniGuard: Hybrid Manipulation Localization via Augmented Versatile Deep Image Watermarking

no code implementations2 Dec 2024 Xuanyu Zhang, Zecheng Tang, Zhipei Xu, Runyi Li, Youmin Xu, Bin Chen, Feng Gao, Jian Zhang

To address these challenges, we propose OmniGuard, a novel augmented versatile watermarking approach that integrates proactive embedding with passive, blind extraction for robust copyright protection and tamper localization.

LOGO -- Long cOntext aliGnment via efficient preference Optimization

1 code implementation24 Oct 2024 Zecheng Tang, Zechen Sun, Juntao Li, Qiaoming Zhu, Min Zhang

To overcome the GPU memory-bound issue caused by the long sequence, LOGO employs a reference-free preference optimization strategy and adopts a position synthesis method to construct the training data.

Language Modelling MMLU

Revealing and Mitigating the Local Pattern Shortcuts of Mamba

1 code implementation21 Oct 2024 Wangjie You, Zecheng Tang, Juntao Li, Lili Yao, Min Zhang

Large language models (LLMs) have advanced significantly due to the attention mechanism, but their quadratic complexity and linear memory demands limit their performance on long-context tasks.

Mamba State Space Models

L-CiteEval: Do Long-Context Models Truly Leverage Context for Responding?

1 code implementation3 Oct 2024 Zecheng Tang, Keyan Zhou, Juntao Li, Baibei Ji, Jianye Hou, Min Zhang

Long-context models (LCMs) have made remarkable strides in recent years, offering users great convenience for handling tasks that involve long context, such as document summarization.

8k Document Summarization +2

FakeShield: Explainable Image Forgery Detection and Localization via Multi-modal Large Language Models

2 code implementations3 Oct 2024 Zhipei Xu, Xuanyu Zhang, Runyi Li, Zecheng Tang, Qing Huang, Jian Zhang

The rapid development of generative AI is a double-edged sword, which not only facilitates content creation but also makes image manipulation easier and more difficult to detect.

Face Swapping Image Forgery Detection +2

MemLong: Memory-Augmented Retrieval for Long Text Modeling

1 code implementation30 Aug 2024 Weijie Liu, Zecheng Tang, Juntao Li, Kehai Chen, Min Zhang

This work introduces MemLong: Memory-Augmented Retrieval for Long Text Generation, a method designed to enhance the capabilities of long-context language modeling by utilizing an external retriever for historical information retrieval.

4k Decoder +4

OpenBA-V2: Reaching 77.3% High Compression Ratio with Fast Multi-Stage Pruning

1 code implementation9 May 2024 Dan Qiao, Yi Su, Pinzheng Wang, Jing Ye, Wenjing Xie, Yuechi Zhou, Yuyang Ding, Zecheng Tang, Jikai Wang, Yixin Ji, Yue Wang, Pei Guo, Zechen Sun, Zikang Zhang, Juntao Li, Pingfu Chao, Wenliang Chen, Guohong Fu, Guodong Zhou, Qiaoming Zhu, Min Zhang

Large Language Models (LLMs) have played an important role in many fields due to their powerful capabilities. However, their massive number of parameters leads to high deployment requirements and incurs significant inference costs, which impedes their practical applications.

Common Sense Reasoning named-entity-recognition +2

Rethinking Negative Instances for Generative Named Entity Recognition

2 code implementations26 Feb 2024 Yuyang Ding, Juntao Li, Pinzheng Wang, Zecheng Tang, Bowen Yan, Min Zhang

In the Named Entity Recognition (NER) task, recent advancements have seen the remarkable improvement of LLMs in a broad range of entity domains via instruction tuning, by adopting entity-centric schema.

named-entity-recognition Named Entity Recognition +2

StrokeNUWA: Tokenizing Strokes for Vector Graphic Synthesis

no code implementations30 Jan 2024 Zecheng Tang, Chenfei Wu, Zekai Zhang, Mingheng Ni, Shengming Yin, Yu Liu, Zhengyuan Yang, Lijuan Wang, Zicheng Liu, Juntao Li, Nan Duan

To leverage LLMs for visual synthesis, traditional methods convert raster image information into discrete grid tokens through specialized visual modules, while disrupting the model's ability to capture the true semantic representation of visual scenes.

Vector Graphics

Beyond Hard Samples: Robust and Effective Grammatical Error Correction with Cycle Self-Augmenting

1 code implementation20 Oct 2023 Zecheng Tang, Kaifeng Qi, Juntao Li, Min Zhang

By leveraging the augmenting data from the GEC models themselves in the post-training process and introducing regularization data for cycle training, our proposed method can effectively improve the model robustness of well-trained GEC models with only a few more training epochs as an extra cost.

Adversarial Attack Grammatical Error Correction

OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch

1 code implementation19 Sep 2023 Juntao Li, Zecheng Tang, Yuyang Ding, Pinzheng Wang, Pei Guo, Wangjie You, Dan Qiao, Wenliang Chen, Guohong Fu, Qiaoming Zhu, Guodong Zhou, Min Zhang

This report provides the main details to pre-train an analogous model, including pre-training data processing, Bilingual Flan data collection, the empirical observations that inspire our model architecture design, training objectives of different stages, and other enhancement techniques.

Belebele MMLU

LayoutNUWA: Revealing the Hidden Layout Expertise of Large Language Models

1 code implementation18 Sep 2023 Zecheng Tang, Chenfei Wu, Juntao Li, Nan Duan

Graphic layout generation, a growing research field, plays a significant role in user engagement and information perception.

Code Completion Code Generation

CMD: a framework for Context-aware Model self-Detoxification

3 code implementations16 Aug 2023 Zecheng Tang, Keyan Zhou, Juntao Li, Yuyang Ding, Pinzheng Wang, Bowen Yan, Rejie Hua, Min Zhang

In view of this, we introduce a Context-aware Model self-Detoxification~(CMD) framework that pays attention to both the context and the detoxification process, i. e., first detoxifying the context and then making the language model generate along the safe context.

Language Modelling

Can Diffusion Model Achieve Better Performance in Text Generation? Bridging the Gap between Training and Inference!

1 code implementation8 May 2023 Zecheng Tang, Pinzheng Wang, Keyan Zhou, Juntao Li, Ziqiang Cao, Min Zhang

Diffusion models have been successfully adapted to text generation tasks by mapping the discrete text into the continuous space.

Text Generation

Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models

3 code implementations8 Mar 2023 Chenfei Wu, Shengming Yin, Weizhen Qi, Xiaodong Wang, Zecheng Tang, Nan Duan

To this end, We build a system called \textbf{Visual ChatGPT}, incorporating different Visual Foundation Models, to enable the user to interact with ChatGPT by 1) sending and receiving not only languages but also images 2) providing complex visual questions or visual editing instructions that require the collaboration of multiple AI models with multi-steps.

Chinese grammatical error correction based on knowledge distillation

2 code implementations31 Jul 2022 Peng Xia, Yuechi Zhou, Ziyan Zhang, Zecheng Tang, Juntao Li

In view of the poor robustness of existing Chinese grammatical error correction models on attack test sets and large model parameters, this paper uses the method of knowledge distillation to compress model parameters and improve the anti-attack ability of the model.

Grammatical Error Correction Knowledge Distillation

Cannot find the paper you are looking for? You can Submit a new open access paper.