Hierarchical Self-Attention: Generalizing Neural Attention Mechanics to Multi-Scale Problems
Saeed Amizadeh, Sara Abdali, Yinheng Li, Kazuhito Koishida
NeurIPS 2025 | September 2025
Sara Abdali
Senior Researcher
论文与出版物
-
-
-
Self-reflecting Large Language Models: A Hegelian Dialectical Approach
Sara Abdali, Can Goksen, Michael Solodko, Saeed Amizadeh, Julie E. Maybee, Kazuhito Koishida
June 2025
-
-
-
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
Rogerio Bonatti, Dan Zhao, Francesco Bonacci, Dillon Dupont, Sara Abdali, Yinheng Li, Yadong Lu, Justin Wagle, Kazuhito Koishida, A. Bucker, Lawrence Jang, Zack Hui
ICML 2025 | September 2024
-
Decoding the AI Pen: Techniques and Challenges in Detecting AI-Generated Text
Sara Abdali, Richard Anarfi, CJ Barberan, Jia He
KDD 2024 | August 2024
-
Can LLMs be Fooled? Investigating Vulnerabilities in LLMs
Sara Abdali, Jia He, CJ Barberan, Richard Anarfi
July 2024
-
Securing Large Language Models: Threats, Vulnerabilities and Responsible Practices
Sara Abdali, Richard Anarfi, C. Barberan, Jia He, Erfan Shayegani
March 2024
-
-
-
Extracting Self-Consistent Causal Insights from Users Feedback with LLMs and In-context Learning
Sara Abdali, Anjali Parikh, Steve Lim, Emre Kiciman
ArXiv | December 2023, 第 abs/2312.06820 卷
-
-
-
Vec2Node: Self-training with Tensor Augmentation for Text Classification with Few Labels
2022 European Conference on Principles of Data Mining and Knowledge Discovery | September 2022
ECML-PKDD Scholarship Award
-
-
-
Hierarchical Self-Attention: Generalizing Neural Attention Mechanics to Multi-Scale Problems
Saeed Amizadeh, Sara Abdali, Yinheng Li, Kazuhito Koishida
NeurIPS 2025 | September 2025
-
Self-reflecting Large Language Models: A Hegelian Dialectical Approach
Sara Abdali, Can Goksen, Michael Solodko, Saeed Amizadeh, Julie E. Maybee, Kazuhito Koishida
June 2025
-
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
Rogerio Bonatti, Dan Zhao, Francesco Bonacci, Dillon Dupont, Sara Abdali, Yinheng Li, Yadong Lu, Justin Wagle, Kazuhito Koishida, A. Bucker, Lawrence Jang, Zack Hui
ICML 2025 | September 2024
-
Decoding the AI Pen: Techniques and Challenges in Detecting AI-Generated Text
Sara Abdali, Richard Anarfi, CJ Barberan, Jia He
KDD 2024 | August 2024
-
Can LLMs be Fooled? Investigating Vulnerabilities in LLMs
Sara Abdali, Jia He, CJ Barberan, Richard Anarfi
July 2024
-
Securing Large Language Models: Threats, Vulnerabilities and Responsible Practices
Sara Abdali, Richard Anarfi, C. Barberan, Jia He, Erfan Shayegani
March 2024
-
Extracting Self-Consistent Causal Insights from Users Feedback with LLMs and In-context Learning
Sara Abdali, Anjali Parikh, Steve Lim, Emre Kiciman
ArXiv | December 2023, 第 abs/2312.06820 卷
-
Vec2Node: Self-training with Tensor Augmentation for Text Classification with Few Labels
2022 European Conference on Principles of Data Mining and Knowledge Discovery | September 2022
ECML-PKDD Scholarship Award
-
-
-
Self-reflecting Large Language Models: A Hegelian Dialectical Approach
Sara Abdali, Can Goksen, Michael Solodko, Saeed Amizadeh, Julie E. Maybee, Kazuhito Koishida
June 2025
-
Decoding the AI Pen: Techniques and Challenges in Detecting AI-Generated Text
Sara Abdali, Richard Anarfi, CJ Barberan, Jia He
KDD 2024 | August 2024
-
Can LLMs be Fooled? Investigating Vulnerabilities in LLMs
Sara Abdali, Jia He, CJ Barberan, Richard Anarfi
July 2024
-
-
-
Self-reflecting Large Language Models: A Hegelian Dialectical Approach
Sara Abdali, Can Goksen, Michael Solodko, Saeed Amizadeh, Julie E. Maybee, Kazuhito Koishida
June 2025
-
-
-
Self-reflecting Large Language Models: A Hegelian Dialectical Approach
Sara Abdali, Can Goksen, Michael Solodko, Saeed Amizadeh, Julie E. Maybee, Kazuhito Koishida
June 2025
-
Decoding the AI Pen: Techniques and Challenges in Detecting AI-Generated Text
Sara Abdali, Richard Anarfi, CJ Barberan, Jia He
KDD 2024 | August 2024
-
Can LLMs be Fooled? Investigating Vulnerabilities in LLMs
Sara Abdali, Jia He, CJ Barberan, Richard Anarfi
July 2024
-
-
-
Can LLMs be Fooled? Investigating Vulnerabilities in LLMs
Sara Abdali, Jia He, CJ Barberan, Richard Anarfi
July 2024
-
Securing Large Language Models: Threats, Vulnerabilities and Responsible Practices
Sara Abdali, Richard Anarfi, C. Barberan, Jia He, Erfan Shayegani
March 2024
-
-
-
Hierarchical Self-Attention: Generalizing Neural Attention Mechanics to Multi-Scale Problems
Saeed Amizadeh, Sara Abdali, Yinheng Li, Kazuhito Koishida
NeurIPS 2025 | September 2025
-
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
Rogerio Bonatti, Dan Zhao, Francesco Bonacci, Dillon Dupont, Sara Abdali, Yinheng Li, Yadong Lu, Justin Wagle, Kazuhito Koishida, A. Bucker, Lawrence Jang, Zack Hui
ICML 2025 | September 2024
-
Decoding the AI Pen: Techniques and Challenges in Detecting AI-Generated Text
Sara Abdali, Richard Anarfi, CJ Barberan, Jia He
KDD 2024 | August 2024
-
Vec2Node: Self-training with Tensor Augmentation for Text Classification with Few Labels
2022 European Conference on Principles of Data Mining and Knowledge Discovery | September 2022
ECML-PKDD Scholarship Award
-
-
-
Self-reflecting Large Language Models: A Hegelian Dialectical Approach
Sara Abdali, Can Goksen, Michael Solodko, Saeed Amizadeh, Julie E. Maybee, Kazuhito Koishida
June 2025
-
Extracting Self-Consistent Causal Insights from Users Feedback with LLMs and In-context Learning
Sara Abdali, Anjali Parikh, Steve Lim, Emre Kiciman
ArXiv | December 2023, 第 abs/2312.06820 卷
-
-
-
Can LLMs be Fooled? Investigating Vulnerabilities in LLMs
Sara Abdali, Jia He, CJ Barberan, Richard Anarfi
July 2024
-
Securing Large Language Models: Threats, Vulnerabilities and Responsible Practices
Sara Abdali, Richard Anarfi, C. Barberan, Jia He, Erfan Shayegani
March 2024
-