Abulhair Saparov

According to our database, Abulhair Saparov authored at least 21 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs.

Andreas Opedal, Haruki Shirakami, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan

CoRR, 2024

A Practical Review of Mechanistic Interpretability for Transformer-Based Language Models.

Daking Rai, Yilun Zhou, Shi Feng, Abulhair Saparov, Ziyu Yao

CoRR, 2024

Foundational Challenges in Assuring Alignment and Safety of Large Language Models.

Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, José Hernández-Orallo, Lewis Hammond, Eric J. Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Zhang, Ruiqi Zhong, Seán Ó hÉigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Yoshua Bengio, Danqi Chen, Samuel Albanie, Tegan Maharaj, Jakob N. Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger

CoRR, 2024

Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners?

Andreas Opedal, Alessandro Stolfo, Haruki Shirakami, Ying Jiao, Ryan Cotterell, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

LLMs Are Prone to Fallacies in Causal Inference.

Nitish Joshi, Abulhair Saparov, Yixin Wang, He He

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Personas as a Way to Model Truthfulness in Language Models.

Nitish Joshi, Javier Rando, Abulhair Saparov, Najoung Kim, He He

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Retrieval-Augmented Chain-of-Thought in Semi-structured Domains.

Vaibhav Mavi, Abulhair Saparov, Chen Zhao

CoRR, 2023

Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples.

Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Mehran Kazemi, Najoung Kim, He He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought.

Abulhair Saparov, He He

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Noisy Exemplars Make Large Language Models More Robust: A Domain-Agnostic Behavioral Analysis.

Hongyi Zheng, Abulhair Saparov

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

World Models for Math Story Problems.

Andreas Opedal, Niklas Stoehr, Abulhair Saparov, Mrinmaya Sachan

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Towards General Natural Language Understanding with Probabilistic Worldbuilding.

Abulhair Saparov, Tom M. Mitchell

Trans. Assoc. Comput. Linguistics, 2022

2021

A Generative Symbolic Model for More General Natural Language Understanding and Reasoning.

Abulhair Saparov, Tom M. Mitchell

CoRR, 2021

2020

Jelly Bean World: A Testbed for Never-Ending Learning.

Emmanouil Antonios Platanios, Abulhair Saparov, Tom M. Mitchell

Proceedings of the 8th International Conference on Learning Representations, 2020

2018

Never-ending learning.

Tom M. Mitchell, William W. Cohen, Estevam R. Hruschka Jr., Partha P. Talukdar, Bo Yang, Justin Betteridge, Andrew Carlson, Bhavana Dalvi Mishra, Matt Gardner, Bryan Kisiel, Jayant Krishnamurthy, Ni Lao, Kathryn Mazaitis, Thahir Mohamed, Ndapandula Nakashole, Emmanouil A. Platanios, Alan Ritter, Mehdi Samadi, Burr Settles, Richard C. Wang, Derry Wijaya, Abhinav Gupta, Xinlei Chen, Abulhair Saparov, Malcolm Greaves, Joel Welling

Commun. ACM, 2018

2017

A Probabilistic Generative Grammar for Semantic Parsing.

Abulhair Saparov, Vijay A. Saraswat, Tom M. Mitchell

Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), 2017

2016

A Probabilistic Generative Grammar for Semantic Parsing.

Abulhair Saparov, Tom M. Mitchell

CoRR, 2016

CMUML Micro-Reader System for KBP 2016 Cold Start Slot Filling, Event Nugget Detection, and Event Argument Linking.

Bishan Yang, Ndapandula Nakashole, Bryan Kisiel, Emmanouil A. Platanios, Abulhair Saparov, Shashank Srivastava, Derry Wijaya, Tom M. Mitchell

Proceedings of the 2016 Text Analysis Conference, 2016

2015

CMUML System for KBP 2015 Cold Start Slot Filling.

Bryan Kisiel, Bill McDowell, Matt Gardner, Ndapandula Nakashole, Emmanouil A. Platanios, Abulhair Saparov, Shashank Srivastava, Derry Wijaya, Tom M. Mitchell

Proceedings of the 2015 Text Analysis Conference, 2015

Never-Ending Learning.

Tom M. Mitchell, William W. Cohen, Estevam R. Hruschka Jr., Partha Pratim Talukdar, Justin Betteridge, Andrew Carlson, Bhavana Dalvi Mishra, Matthew Gardner, Bryan Kisiel, Jayant Krishnamurthy, Ni Lao, Kathryn Mazaitis, Thahir Mohamed, Ndapandula Nakashole, Emmanouil A. Platanios, Alan Ritter, Mehdi Samadi, Burr Settles, Richard C. Wang, Derry Wijaya, Abhinav Gupta, Xinlei Chen, Abulhair Saparov, Malcolm Greaves, Joel Welling

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2012

Schelling points on 3D surface meshes.

Xiaobai Chen, Abulhair Saparov, Bill Pang, Thomas A. Funkhouser

ACM Trans. Graph., 2012