Search Results for author: Zeyuan Chen

Found 33 papers, 19 papers with code

High Resolution and Fast Face Completion via Progressively Attentive GANs

no code implementations ICLR 2019 Zeyuan Chen, Shaoliang Nie, Tianfu Wu, Christopher G. Healey

Face completion is a challenging task with the difficulty level increasing significantly with respect to high resolution, the complexity of "holes" and the controllable attributes of filled-in fragments.

Facial Inpainting Vocal Bursts Intensity Prediction

OmniControlNet: Dual-stage Integration for Conditional Image Generation

no code implementations9 Jun 2024 Yilin Wang, Haiyang Xu, Xiang Zhang, Zeyuan Chen, Zhizhou Sha, ZiRui Wang, Zhuowen Tu

We provide a two-way integration for the widely adopted ControlNet by integrating external condition generation algorithms into a single dense prediction method and incorporating its individually trained image generation processes into a single model.

Conditional Image Generation Text-to-Image Generation

SQ-LLaVA: Self-Questioning for Large Vision-Language Assistant

1 code implementation17 Mar 2024 Guohao Sun, Can Qin, Jiamian Wang, Zeyuan Chen, ran Xu, Zhiqiang Tao

Recent advances in vision-language models have shown notable generalization in broad tasks through visual instruction tuning.

Language Modelling Question Answering +2

Bayesian Diffusion Models for 3D Shape Reconstruction

no code implementations CVPR 2024 Haiyang Xu, Yu Lei, Zeyuan Chen, Xiang Zhang, Yue Zhao, Yilin Wang, Zhuowen Tu

We present Bayesian Diffusion Models (BDM), a prediction algorithm that performs effective Bayesian inference by tightly coupling the top-down (prior) information with the bottom-up (data-driven) procedure via joint diffusion processes.

3D Reconstruction 3D Shape Reconstruction +1

Pattern-wise Transparent Sequential Recommendation

no code implementations18 Feb 2024 Kun Ma, Cong Xu, Zeyuan Chen, Wei zhang

However, achieving both model transparency and recommendation performance simultaneously is challenging, especially for models that take the entire sequence of items as input without screening.

Decision Making Sequential Recommendation

Comprehensive Assessment of Toxicity in ChatGPT

no code implementations3 Nov 2023 Boyang Zhang, Xinyue Shen, Wai Man Si, Zeyang Sha, Zeyuan Chen, Ahmed Salem, Yun Shen, Michael Backes, Yang Zhang

Moderating offensive, hateful, and toxic language has always been an important but challenging topic in the domain of safe use in NLP.

Dolfin: Diffusion Layout Transformers without Autoencoder

no code implementations25 Oct 2023 Yilin Wang, Zeyuan Chen, Liangjun Zhong, Zheng Ding, Zhizhou Sha, Zhuowen Tu

In this paper, we introduce a novel generative model, Diffusion Layout Transformers without Autoencoder (Dolfin), which significantly improves the modeling capability with reduced complexity compared to existing methods.

Beyond Semantics: Learning a Behavior Augmented Relevance Model with Self-supervised Learning

1 code implementation10 Aug 2023 Zeyuan Chen, Wei Chen, Jia Xu, Zhongyi Liu, Wei zhang

Drawing inspiration from this, we devise a novel Behavior Augmented Relevance Learning model for Alipay Search (BARL-ASe) that leverages neighbor queries of target item and neighbor items of target query to complement target query-item semantic matching.

Self-Supervised Learning Semantic Similarity +1

"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models

1 code implementation7 Aug 2023 Xinyue Shen, Zeyuan Chen, Michael Backes, Yun Shen, Yang Zhang

We hope that our study can facilitate the research community and LLM vendors in promoting safer and regulated LLMs.

Community Detection

Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization

1 code implementation4 Aug 2023 Weiran Yao, Shelby Heinecke, Juan Carlos Niebles, Zhiwei Liu, Yihao Feng, Le Xue, Rithesh Murthy, Zeyuan Chen, JianGuo Zhang, Devansh Arpit, ran Xu, Phil Mui, Huan Wang, Caiming Xiong, Silvio Savarese

This demonstrates that using policy gradient optimization to improve language agents, for which we believe our work is one of the first, seems promising and can be applied to optimize other models in the agent architecture to enhance agent performances over time.

Language Modelling

In ChatGPT We Trust? Measuring and Characterizing the Reliability of ChatGPT

no code implementations18 Apr 2023 Xinyue Shen, Zeyuan Chen, Michael Backes, Yang Zhang

In this paper, we perform the first large-scale measurement of ChatGPT's reliability in the generic QA scenario with a carefully curated set of 5, 695 questions across ten datasets and eight domains.

Question Answering

MGTBench: Benchmarking Machine-Generated Text Detection

3 code implementations26 Mar 2023 Xinlei He, Xinyue Shen, Zeyuan Chen, Michael Backes, Yang Zhang

Extensive evaluations on public datasets with curated texts generated by various powerful LLMs such as ChatGPT-turbo and Claude demonstrate the effectiveness of different detection methods.

Benchmarking Question Answering +4

GlueGen: Plug and Play Multi-modal Encoders for X-to-image Generation

1 code implementation ICCV 2023 Can Qin, Ning Yu, Chen Xing, Shu Zhang, Zeyuan Chen, Stefano Ermon, Yun Fu, Caiming Xiong, ran Xu

Empirical results show that GlueNet can be trained efficiently and enables various capabilities beyond previous state-of-the-art models: 1) multilingual language models such as XLM-Roberta can be aligned with existing T2I models, allowing for the generation of high-quality images from captions beyond English; 2) GlueNet can align multi-modal encoders such as AudioCLIP with the Stable Diffusion model, enabling sound-to-image generation; 3) it can also upgrade the current text encoder of the latent diffusion model for challenging case generation.

Decoder Image Generation

Uni-3D: A Universal Model for Panoptic 3D Scene Reconstruction

1 code implementation ICCV 2023 Xiang Zhang, Zeyuan Chen, Fangyin Wei, Zhuowen Tu

Performing holistic 3D scene understanding from a single-view observation, involving generating instance shapes and 3D scene segmentation, is a long-standing challenge.

3D Scene Reconstruction Image Segmentation +4

Tackling Data Heterogeneity in Federated Learning with Class Prototypes

1 code implementation6 Dec 2022 Yutong Dai, Zeyuan Chen, Junnan Li, Shelby Heinecke, Lichao Sun, ran Xu

We propose FedNH, a novel method that improves the local models' performance for both personalization and generalization by combining the uniformity and semantics of class prototypes.

Personalized Federated Learning

CASA: Category-agnostic Skeletal Animal Reconstruction

no code implementations4 Nov 2022 Yuefan Wu, Zeyuan Chen, Shaowei Liu, Zhongzheng Ren, Shenlong Wang

Recovering the skeletal shape of an animal from a monocular video is a longstanding challenge.


Burn After Reading: Online Adaptation for Cross-domain Streaming Data

no code implementations8 Dec 2021 Luyu Yang, Mingfei Gao, Zeyuan Chen, ran Xu, Abhinav Shrivastava, Chetan Ramaiah

In the context of online privacy, many methods propose complex privacy and security preserving measures to protect sensitive data.

Diversity Unsupervised Domain Adaptation

Robustness Evaluation of Transformer-based Form Field Extractors via Form Attacks

1 code implementation8 Oct 2021 Le Xue, Mingfei Gao, Zeyuan Chen, Caiming Xiong, ran Xu

We propose a novel framework to evaluate the robustness of transformer-based form field extraction methods via form attacks.

Optical Character Recognition (OCR)

MC$^2$-SF: Slow-Fast Learning for Mobile-Cloud Collaborative Recommendation

no code implementations25 Sep 2021 Zeyuan Chen, Jiangchao Yao, Feng Wang, Kunyang Jia, Bo Han, Wei zhang, Hongxia Yang

With the hardware development of mobile devices, it is possible to build the recommendation models on the mobile side to utilize the fine-grained features and the real-time feedbacks.

Learning Dual Dynamic Representations on Time-Sliced User-Item Interaction Graphs for Sequential Recommendation

1 code implementation24 Sep 2021 Zeyuan Chen, Wei zhang, Junchi Yan, Gang Wang, Jianyong Wang

Sequential Recommendation aims to recommend items that a target user will interact with in the near future based on the historically interacted items.

Representation Learning Sequential Recommendation

CERL: A Unified Optimization Framework for Light Enhancement with Realistic Noise

1 code implementation1 Aug 2021 Zeyuan Chen, Yifan Jiang, Dong Liu, Zhangyang Wang

We present \underline{C}oordinated \underline{E}nhancement for \underline{R}eal-world \underline{L}ow-light Noisy Images (CERL), that seamlessly integrates light enhancement and noise suppression parts into a unified and physics-grounded optimization framework.


Graph-Based Tri-Attention Network for Answer Ranking in CQA

no code implementations5 Mar 2021 Wei zhang, Zeyuan Chen, Chao Dong, Wen Wang, Hongyuan Zha, Jianyong Wang

However, they encounter two main limitations: (1) Correlations between answers in the same question are often overlooked.

Question Answering

Towards Controllable and Interpretable Face Completion via Structure-Aware and Frequency-Oriented Attentive GANs

no code implementations25 Sep 2019 Zeyuan Chen, Shaoliang Nie, Tianfu Wu, Christopher G. Healey

The proposed frequency-oriented attentive module (FOAM) encourages GANs to attend to only finer details in the coarse-to-fine progressive training, thus enabling progressive attention to face structures.

Facial Inpainting

High Resolution Face Completion with Multiple Controllable Attributes via Fully End-to-End Progressive Generative Adversarial Networks

no code implementations23 Jan 2018 Zeyuan Chen, Shaoliang Nie, Tianfu Wu, Christopher G. Healey

It is a challenging task with the difficulty level increasing significantly with respect to high resolution, the complexity of "holes" and the controllable attributes of filled-in fragments.

Facial Inpainting

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