Search Results for author: Zhilin Wang

Found 19 papers, 6 papers with code

How to be Helpful on Online Support Forums?

no code implementations NAACL (WNU) 2022 Zhilin Wang, Pablo E. Torres

Internet forums such as Reddit offer people a platform to ask for advice when they encounter various issues at work, school or in relationships.

Uncovering Surprising Event Boundaries in Narratives

no code implementations NAACL (WNU) 2022 Zhilin Wang, Anna Jafarpour, Maarten Sap

It is important to define meaningful and interpretable automatic evaluation metrics for open-domain dialog research.

Open-Domain Dialog Text Generation

NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment

1 code implementation2 May 2024 Gerald Shen, Zhilin Wang, Olivier Delalleau, Jiaqi Zeng, Yi Dong, Daniel Egert, Shengyang Sun, Jimmy Zhang, Sahil Jain, Ali Taghibakhshi, Markel Sanz Ausin, Ashwath Aithal, Oleksii Kuchaiev

However, building efficient tools to perform alignment can be challenging, especially for the largest and most competent LLMs which often contain tens or hundreds of billions of parameters.

HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM

no code implementations16 Nov 2023 Zhilin Wang, Yi Dong, Jiaqi Zeng, Virginia Adams, Makesh Narsimhan Sreedhar, Daniel Egert, Olivier Delalleau, Jane Polak Scowcroft, Neel Kant, Aidan Swope, Oleksii Kuchaiev

To alleviate this problem, we collect HelpSteer, a multi-attribute helpfulness dataset annotated for the various aspects that make responses helpful.

Attribute

Can We Trust the Similarity Measurement in Federated Learning?

no code implementations20 Oct 2023 Zhilin Wang, Qin Hu, Xukai Zou

We first uncover the deficiencies of similarity metrics that high-dimensional local models, including benign and poisoned models, may be evaluated to have the same similarity while being significantly different in the parameter values.

Federated Learning Model Poisoning

Humanoid Agents: Platform for Simulating Human-like Generative Agents

1 code implementation9 Oct 2023 Zhilin Wang, Yu Ying Chiu, Yu Cheung Chiu

Just as computational simulations of atoms, molecules and cells have shaped the way we study the sciences, true-to-life simulations of human-like agents can be valuable tools for studying human behavior.

Unity

SteerLM: Attribute Conditioned SFT as an (User-Steerable) Alternative to RLHF

no code implementations9 Oct 2023 Yi Dong, Zhilin Wang, Makesh Narsimhan Sreedhar, Xianchao Wu, Oleksii Kuchaiev

Model alignment with human preferences is an essential step in making Large Language Models (LLMs) helpful and consistent with human values.

Attribute

Deepfake Text Detection in the Wild

2 code implementations22 May 2023 Yafu Li, Qintong Li, Leyang Cui, Wei Bi, Zhilin Wang, Longyue Wang, Linyi Yang, Shuming Shi, Yue Zhang

In practical scenarios, however, the detector faces texts from various domains or LLMs without knowing their sources.

Face Swapping Story Generation +1

FVQA 2.0: Introducing Adversarial Samples into Fact-based Visual Question Answering

no code implementations19 Mar 2023 Weizhe Lin, Zhilin Wang, Bill Byrne

The widely used Fact-based Visual Question Answering (FVQA) dataset contains visually-grounded questions that require information retrieval using common sense knowledge graphs to answer.

Common Sense Reasoning Information Retrieval +4

Transformer-Empowered Content-Aware Collaborative Filtering

no code implementations2 Apr 2022 Weizhe Lin, Linjun Shou, Ming Gong, Pei Jian, Zhilin Wang, Bill Byrne, Daxin Jiang

Knowledge graph (KG) based Collaborative Filtering is an effective approach to personalizing recommendation systems for relatively static domains such as movies and books, by leveraging structured information from KG to enrich both item and user representations.

Collaborative Filtering Contrastive Learning +1

Incentive Mechanism Design for Joint Resource Allocation in Blockchain-based Federated Learning

no code implementations18 Feb 2022 Zhilin Wang, Qin Hu, Ruinian Li, Minghui Xu, Zehui Xiong

Since each client has a limited amount of computing resources, the problem of allocating computing resources into training and mining needs to be carefully addressed.

Federated Learning

Blockchain and Federated Edge Learning for Privacy-Preserving Mobile Crowdsensing

no code implementations16 Oct 2021 Qin Hu, Zhilin Wang, Minghui Xu, Xiuzhen Cheng

Mobile crowdsensing (MCS) counting on the mobility of massive workers helps the requestor accomplish various sensing tasks with more flexibility and lower cost.

Federated Learning Privacy Preserving

Blockchain-based Federated Learning: A Comprehensive Survey

no code implementations5 Oct 2021 Zhilin Wang, Qin Hu

Then, we analyze the concrete functions of BCFL from the perspective of mechanism design and illustrate what problems blockchain addresses specifically for FL.

BIG-bench Machine Learning Federated Learning

Extracting and Inferring Personal Attributes from Dialogue

1 code implementation NLP4ConvAI (ACL) 2022 Zhilin Wang, Xuhui Zhou, Rik Koncel-Kedziorski, Alex Marin, Fei Xia

Personal attributes represent structured information about a person, such as their hobbies, pets, family, likes and dislikes.

Attribute Language Modelling

Learning Similarity between Movie Characters and Its Potential Implications on Understanding Human Experiences

no code implementations NAACL (NUSE) 2021 Zhilin Wang, Weizhe Lin, Xiaodong Wu

While many different aspects of human experiences have been studied by the NLP community, none has captured its full richness.

NASNet: A Neuron Attention Stage-by-Stage Net for Single Image Deraining

3 code implementations6 Dec 2019 Xu Qin, Zhilin Wang

In this paper, we propose a novel end-to-end Neuron Attention Stage-by-Stage Net (NASNet), which can solve all types of rain model tasks efficiently.

Single Image Deraining

FFA-Net: Feature Fusion Attention Network for Single Image Dehazing

3 code implementations18 Nov 2019 Xu Qin, Zhilin Wang, Yuanchao Bai, Xiaodong Xie, Huizhu Jia

The FFA-Net architecture consists of three key components: 1) A novel Feature Attention (FA) module combines Channel Attention with Pixel Attention mechanism, considering that different channel-wise features contain totally different weighted information and haze distribution is uneven on the different image pixels.

Image Dehazing Single Image Dehazing

No, you're not alone: A better way to find people with similar experiences on Reddit

no code implementations WS 2019 Zhilin Wang, Elena Rastorgueva, Weizhe Lin, Xiaodong Wu

This model is built upon the BERT Next Sentence Prediction model and reduces the time complexity for clustering all posts in a corpus from O(n{\^{}}2) to O(n) with respect to the number of posts.

Clustering Sentence

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