Weiwei Yang

Senior Director

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Publications

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- Interpretable Next-token Prediction via the Generalized Induction Head
  
  Eunji Kim, Sriya Mantena, Weiwei Yang, Chandan Singh, Sungroh Yoon, Jianfeng Gao
  
  NeurIPS 2025 | October 2025
  
  Publication
- Fast and Reliable N – k Contingency Screening with Input-Convex Neural Networks
  
  Nicolas Christianson, Wenqi Cui, Steven Low, Weiwei Yang, Baosen Zhang
  
  L4DC 2025 | June 2025
  
  Publication
- Iterative Self-Tuning LLMs for Enhanced Jailbreaking Capabilities
  
  Chung-En Sun, Xiaodong Liu, Weiwei Yang, Tsui-Wei Weng, Hao Cheng, Aidan San, Michel Galley, Jianfeng Gao
  
  NAACL 2025 | April 2025
  
  Selected for oral presentation
  
  Publication
- Multiple Network Embedding for Anomaly Detection in Time Series of Graphs
  
  Guodong Chen, Jesus Arroyo, Avanti Athreya, Joshua Cape, Joshua T. Vogelstein, Youngser Park, Chris White, Jonathan Larson, Weiwei Yang, Carey E. Priebe
  
  Computational Statistics & Data Analysis | March 2025, Vol 203
  
  Publication PDF
- Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models
  
  Xin Jin, Jonathan Larson, Weiwei Yang, Zhiqiang Lin
  
  December 2023
  
  DOI Publication Publication
- Discovering a change point and piecewise linear structure in a time series of organoid networks via the iso-mirror
  
  Tianyi Chen, Weiwei Yang, Chris White, Carey E. Priebe
  
  Applied Network Science | July 2023
  
  Publication Project
- Towards closing the data gap: A project-driven distributed energy resource dataset for the U.S. Grid
  
  Rabab Haider, Yixing Xu, Weiwei Yang
  
  AMC International conference on Future of Energy Systems | June 2023
  
  Publication Github
- A Frequency Domain Approach to Predict Power System Transients
  
  Wenqi Cui, Weiwei Yang, Baosen Zhang
  
  IEEE Transactions on Power Systems | March 2023
  
  Publication
- Distance-based Positive and Unlabeled Learning for Ranking
  
  Hayden S. Helm, Amitabh Basu, Carey E. Priebe, Jonathan Larson, Marah I Abdin, Piali Choudhury, Weiwei Yang, Chris White
  
  Pattern Recognition | October 2022
  
  Publication
- Mental State Classification Using Multi-Graph Features
  
  Guodong Chen, Hayden S. Helm, Kate Lytvynets, Weiwei Yang, Carey E. Priebe
  
  Frontiers in Human Neuroscience | June 2022
  
  Publication Project
- Inducing a hierarchy for multi-class classification problems
  
  Hayden S. Helm, Ali Geisa, Weiwei Yang, Kate Lytvynets, Oriana Riva, Sujeeth Bharadwaj, Carey E. Priebe, Chris White
  
  Arxiv | February 2021, Vol 2102.10263
  
  Publication
- A partition-based similarity for classification distributions.
  
  Hayden S. Helm, Ronak D. Mehta, Brandon Duderstadt, Ali Geisa, Weiwei Yang, Joshua T. Vogelstein, Carey E. Priebe, Chris White
  
  November 2020
  
  Publication
- Using Mobility for Electrical Load Forecasting During the COVID-19 Pandemic
  
  Yize Chen, Weiwei Yang, Baosen Zhang
  
  June 2020
  
  Publication Project
- Design of a Privacy-Preserving Data Platform for Collaboration Against Human Trafficking
  
  Darren Edge, Weiwei Yang, Harry Cook, Claire Galez-Davis, Hannah Darnton, Kate Lytvynets, Chris White
  
  May 2020
  
  Preprint PDF
- A general approach to progressive learning
  
  Joshua T. Vogelstein, Hayden S. Helm, Ronak D. Mehta, Jayanta Dey, Will LeVine, Weiwei Yang, Bryan Tower, Jonathan Larson, Carey E. Priebe, Chris White
  
  April 2020
  
  Preprint

- Interpretable Next-token Prediction via the Generalized Induction Head
  
  Eunji Kim, Sriya Mantena, Weiwei Yang, Chandan Singh, Sungroh Yoon, Jianfeng Gao
  
  NeurIPS 2025 | October 2025
  
  Publication
- Fast and Reliable N – k Contingency Screening with Input-Convex Neural Networks
  
  Nicolas Christianson, Wenqi Cui, Steven Low, Weiwei Yang, Baosen Zhang
  
  L4DC 2025 | June 2025
  
  Publication
- Iterative Self-Tuning LLMs for Enhanced Jailbreaking Capabilities
  
  Chung-En Sun, Xiaodong Liu, Weiwei Yang, Tsui-Wei Weng, Hao Cheng, Aidan San, Michel Galley, Jianfeng Gao
  
  NAACL 2025 | April 2025
  
  Selected for oral presentation
  
  Publication
- Multiple Network Embedding for Anomaly Detection in Time Series of Graphs
  
  Guodong Chen, Jesus Arroyo, Avanti Athreya, Joshua Cape, Joshua T. Vogelstein, Youngser Park, Chris White, Jonathan Larson, Weiwei Yang, Carey E. Priebe
  
  Computational Statistics & Data Analysis | March 2025, Vol 203
  
  Publication PDF
- Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models
  
  Xin Jin, Jonathan Larson, Weiwei Yang, Zhiqiang Lin
  
  December 2023
  
  DOI Publication Publication
- Inducing a hierarchy for multi-class classification problems
  
  Hayden S. Helm, Ali Geisa, Weiwei Yang, Kate Lytvynets, Oriana Riva, Sujeeth Bharadwaj, Carey E. Priebe, Chris White
  
  Arxiv | February 2021, Vol 2102.10263
  
  Publication
- A partition-based similarity for classification distributions.
  
  Hayden S. Helm, Ronak D. Mehta, Brandon Duderstadt, Ali Geisa, Weiwei Yang, Joshua T. Vogelstein, Carey E. Priebe, Chris White
  
  November 2020
  
  Publication
- Using Mobility for Electrical Load Forecasting During the COVID-19 Pandemic
  
  Yize Chen, Weiwei Yang, Baosen Zhang
  
  June 2020
  
  Publication Project
- A general approach to progressive learning
  
  Joshua T. Vogelstein, Hayden S. Helm, Ronak D. Mehta, Jayanta Dey, Will LeVine, Weiwei Yang, Bryan Tower, Jonathan Larson, Carey E. Priebe, Chris White
  
  April 2020
  
  Preprint
- Iterative Self-Tuning LLMs for Enhanced Jailbreaking Capabilities
  
  Chung-En Sun, Xiaodong Liu, Weiwei Yang, Tsui-Wei Weng, Hao Cheng, Aidan San, Michel Galley, Jianfeng Gao
  
  NAACL 2025 | April 2025
  
  Selected for oral presentation
  
  Publication
- Design of a Privacy-Preserving Data Platform for Collaboration Against Human Trafficking
  
  Darren Edge, Weiwei Yang, Harry Cook, Claire Galez-Davis, Hannah Darnton, Kate Lytvynets, Chris White
  
  May 2020
  
  Preprint PDF
- Multiple Network Embedding for Anomaly Detection in Time Series of Graphs
  
  Guodong Chen, Jesus Arroyo, Avanti Athreya, Joshua Cape, Joshua T. Vogelstein, Youngser Park, Chris White, Jonathan Larson, Weiwei Yang, Carey E. Priebe
  
  Computational Statistics & Data Analysis | March 2025, Vol 203
  
  Publication PDF
- Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models
  
  Xin Jin, Jonathan Larson, Weiwei Yang, Zhiqiang Lin
  
  December 2023
  
  DOI Publication Publication
- Discovering a change point and piecewise linear structure in a time series of organoid networks via the iso-mirror
  
  Tianyi Chen, Weiwei Yang, Chris White, Carey E. Priebe
  
  Applied Network Science | July 2023
  
  Publication Project
- Towards closing the data gap: A project-driven distributed energy resource dataset for the U.S. Grid
  
  Rabab Haider, Yixing Xu, Weiwei Yang
  
  AMC International conference on Future of Energy Systems | June 2023
  
  Publication Github
- A Frequency Domain Approach to Predict Power System Transients
  
  Wenqi Cui, Weiwei Yang, Baosen Zhang
  
  IEEE Transactions on Power Systems | March 2023
  
  Publication
- Distance-based Positive and Unlabeled Learning for Ranking
  
  Hayden S. Helm, Amitabh Basu, Carey E. Priebe, Jonathan Larson, Marah I Abdin, Piali Choudhury, Weiwei Yang, Chris White
  
  Pattern Recognition | October 2022
  
  Publication
- Mental State Classification Using Multi-Graph Features
  
  Guodong Chen, Hayden S. Helm, Kate Lytvynets, Weiwei Yang, Carey E. Priebe
  
  Frontiers in Human Neuroscience | June 2022
  
  Publication Project
- Design of a Privacy-Preserving Data Platform for Collaboration Against Human Trafficking
  
  Darren Edge, Weiwei Yang, Harry Cook, Claire Galez-Davis, Hannah Darnton, Kate Lytvynets, Chris White
  
  May 2020
  
  Preprint PDF
- Multiple Network Embedding for Anomaly Detection in Time Series of Graphs
  
  Guodong Chen, Jesus Arroyo, Avanti Athreya, Joshua Cape, Joshua T. Vogelstein, Youngser Park, Chris White, Jonathan Larson, Weiwei Yang, Carey E. Priebe
  
  Computational Statistics & Data Analysis | March 2025, Vol 203
  
  Publication PDF
- Using Mobility for Electrical Load Forecasting During the COVID-19 Pandemic
  
  Yize Chen, Weiwei Yang, Baosen Zhang
  
  June 2020
  
  Publication Project
- Design of a Privacy-Preserving Data Platform for Collaboration Against Human Trafficking
  
  Darren Edge, Weiwei Yang, Harry Cook, Claire Galez-Davis, Hannah Darnton, Kate Lytvynets, Chris White
  
  May 2020
  
  Preprint PDF

- Interpretable Next-token Prediction via the Generalized Induction Head
  
  Eunji Kim, Sriya Mantena, Weiwei Yang, Chandan Singh, Sungroh Yoon, Jianfeng Gao
  
  NeurIPS 2025 | October 2025
  
  Publication
- Fast and Reliable N – k Contingency Screening with Input-Convex Neural Networks
  
  Nicolas Christianson, Wenqi Cui, Steven Low, Weiwei Yang, Baosen Zhang
  
  L4DC 2025 | June 2025
  
  Publication
- Iterative Self-Tuning LLMs for Enhanced Jailbreaking Capabilities
  
  Chung-En Sun, Xiaodong Liu, Weiwei Yang, Tsui-Wei Weng, Hao Cheng, Aidan San, Michel Galley, Jianfeng Gao
  
  NAACL 2025 | April 2025
  
  Selected for oral presentation
  
  Publication
- Towards closing the data gap: A project-driven distributed energy resource dataset for the U.S. Grid
  
  Rabab Haider, Yixing Xu, Weiwei Yang
  
  AMC International conference on Future of Energy Systems | June 2023
  
  Publication Github
- Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models
  
  Xin Jin, Jonathan Larson, Weiwei Yang, Zhiqiang Lin
  
  December 2023
  
  DOI Publication Publication
- A partition-based similarity for classification distributions.
  
  Hayden S. Helm, Ronak D. Mehta, Brandon Duderstadt, Ali Geisa, Weiwei Yang, Joshua T. Vogelstein, Carey E. Priebe, Chris White
  
  November 2020
  
  Publication
- Design of a Privacy-Preserving Data Platform for Collaboration Against Human Trafficking
  
  Darren Edge, Weiwei Yang, Harry Cook, Claire Galez-Davis, Hannah Darnton, Kate Lytvynets, Chris White
  
  May 2020
  
  Preprint PDF
- A general approach to progressive learning
  
  Joshua T. Vogelstein, Hayden S. Helm, Ronak D. Mehta, Jayanta Dey, Will LeVine, Weiwei Yang, Bryan Tower, Jonathan Larson, Carey E. Priebe, Chris White
  
  April 2020
  
  Preprint
- Multiple Network Embedding for Anomaly Detection in Time Series of Graphs
  
  Guodong Chen, Jesus Arroyo, Avanti Athreya, Joshua Cape, Joshua T. Vogelstein, Youngser Park, Chris White, Jonathan Larson, Weiwei Yang, Carey E. Priebe
  
  Computational Statistics & Data Analysis | March 2025, Vol 203
  
  Publication PDF
- Discovering a change point and piecewise linear structure in a time series of organoid networks via the iso-mirror
  
  Tianyi Chen, Weiwei Yang, Chris White, Carey E. Priebe
  
  Applied Network Science | July 2023
  
  Publication Project
- A Frequency Domain Approach to Predict Power System Transients
  
  Wenqi Cui, Weiwei Yang, Baosen Zhang
  
  IEEE Transactions on Power Systems | March 2023
  
  Publication
- Distance-based Positive and Unlabeled Learning for Ranking
  
  Hayden S. Helm, Amitabh Basu, Carey E. Priebe, Jonathan Larson, Marah I Abdin, Piali Choudhury, Weiwei Yang, Chris White
  
  Pattern Recognition | October 2022
  
  Publication
- Mental State Classification Using Multi-Graph Features
  
  Guodong Chen, Hayden S. Helm, Kate Lytvynets, Weiwei Yang, Carey E. Priebe
  
  Frontiers in Human Neuroscience | June 2022
  
  Publication Project
- Inducing a hierarchy for multi-class classification problems
  
  Hayden S. Helm, Ali Geisa, Weiwei Yang, Kate Lytvynets, Oriana Riva, Sujeeth Bharadwaj, Carey E. Priebe, Chris White
  
  Arxiv | February 2021, Vol 2102.10263
  
  Publication
- Using Mobility for Electrical Load Forecasting During the COVID-19 Pandemic
  
  Yize Chen, Weiwei Yang, Baosen Zhang
  
  June 2020
  
  Publication Project

Weiwei Yang

Publications

Interpretable Next-token Prediction via the Generalized Induction Head

Fast and Reliable N – k Contingency Screening with Input-Convex Neural Networks

Iterative Self-Tuning LLMs for Enhanced Jailbreaking Capabilities

Multiple Network Embedding for Anomaly Detection in Time Series of Graphs

Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models

Discovering a change point and piecewise linear structure in a time series of organoid networks via the iso-mirror

Towards closing the data gap: A project-driven distributed energy resource dataset for the U.S. Grid

A Frequency Domain Approach to Predict Power System Transients

Distance-based Positive and Unlabeled Learning for Ranking

Mental State Classification Using Multi-Graph Features

Inducing a hierarchy for multi-class classification problems

A partition-based similarity for classification distributions.

Using Mobility for Electrical Load Forecasting During the COVID-19 Pandemic

Design of a Privacy-Preserving Data Platform for Collaboration Against Human Trafficking

A general approach to progressive learning

Interpretable Next-token Prediction via the Generalized Induction Head

Fast and Reliable N – k Contingency Screening with Input-Convex Neural Networks

Iterative Self-Tuning LLMs for Enhanced Jailbreaking Capabilities

Multiple Network Embedding for Anomaly Detection in Time Series of Graphs

Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models

Inducing a hierarchy for multi-class classification problems

A partition-based similarity for classification distributions.

Using Mobility for Electrical Load Forecasting During the COVID-19 Pandemic

A general approach to progressive learning

Iterative Self-Tuning LLMs for Enhanced Jailbreaking Capabilities

Design of a Privacy-Preserving Data Platform for Collaboration Against Human Trafficking

Multiple Network Embedding for Anomaly Detection in Time Series of Graphs

Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models

Discovering a change point and piecewise linear structure in a time series of organoid networks via the iso-mirror

Towards closing the data gap: A project-driven distributed energy resource dataset for the U.S. Grid

A Frequency Domain Approach to Predict Power System Transients

Distance-based Positive and Unlabeled Learning for Ranking

Mental State Classification Using Multi-Graph Features

Design of a Privacy-Preserving Data Platform for Collaboration Against Human Trafficking

Multiple Network Embedding for Anomaly Detection in Time Series of Graphs

Using Mobility for Electrical Load Forecasting During the COVID-19 Pandemic

Design of a Privacy-Preserving Data Platform for Collaboration Against Human Trafficking

Interpretable Next-token Prediction via the Generalized Induction Head

Fast and Reliable N – k Contingency Screening with Input-Convex Neural Networks

Iterative Self-Tuning LLMs for Enhanced Jailbreaking Capabilities

Towards closing the data gap: A project-driven distributed energy resource dataset for the U.S. Grid

Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models

A partition-based similarity for classification distributions.

Design of a Privacy-Preserving Data Platform for Collaboration Against Human Trafficking

A general approach to progressive learning

Multiple Network Embedding for Anomaly Detection in Time Series of Graphs

Discovering a change point and piecewise linear structure in a time series of organoid networks via the iso-mirror

A Frequency Domain Approach to Predict Power System Transients

Distance-based Positive and Unlabeled Learning for Ranking

Mental State Classification Using Multi-Graph Features

Inducing a hierarchy for multi-class classification problems

Using Mobility for Electrical Load Forecasting During the COVID-19 Pandemic