Schelling points on 3D surface meshes. - Xiaobai Chen; Abulhair Saparov; Bill Pang; Thomas A. Funkhouser (ACM Trans. Graph., 2012)

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 001; Bryan Kisiel; Jayant Krishnamurthy; Ni Lao; Kathryn Mazaitis; et al. (AAAI, 2015)

CMUML System for KBP 2015 Cold Start Slot Filling. - Bryan Kisiel; Bill McDowell; Matt Gardner 001; Ndapandula Nakashole; Emmanouil A. Platanios; Abulhair Saparov; Shashank Srivastava; Derry Wijaya; Tom M. Mitchell (TAC, 2015)

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 (TAC, 2016)

A Probabilistic Generative Grammar for Semantic Parsing. - Abulhair Saparov; Tom M. Mitchell (CoRR, 2016)

A Probabilistic Generative Grammar for Semantic Parsing. - Abulhair Saparov; Vijay A. Saraswat; Tom M. Mitchell (CoNLL, 2017)

Never-ending learning. - Tom M. Mitchell; William W. Cohen; Estevam R. Hruschka Jr.; Partha P. Talukdar; Bo Yang 011; Justin Betteridge; Andrew Carlson; Bhavana Dalvi Mishra; Matt Gardner 001; Bryan Kisiel; Jayant Krishnamurthy; Ni Lao; et al. (Commun. ACM, 2018)

Jelly Bean World: A Testbed for Never-Ending Learning. - Emmanouil Antonios Platanios; Abulhair Saparov; Tom M. Mitchell (ICLR, 2020)

A Generative Symbolic Model for More General Natural Language Understanding and Reasoning. - Abulhair Saparov; Tom M. Mitchell (CoRR, 2021)

Towards General Natural Language Understanding with Probabilistic Worldbuilding. - Abulhair Saparov; Tom M. Mitchell (Trans. Assoc. Comput. Linguistics, 2022)

World Models for Math Story Problems. - Andreas Opedal; Niklas Stoehr; Abulhair Saparov; Mrinmaya Sachan (ACL (Findings), 2023)

Noisy Exemplars Make Large Language Models More Robust: A Domain-Agnostic Behavioral Analysis. - Hongyi Zheng; Abulhair Saparov (EMNLP, 2023)

Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought. - Abulhair Saparov; He He 001 (ICLR, 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 001 (NeurIPS, 2023)

Retrieval-Augmented Chain-of-Thought in Semi-structured Domains. - Vaibhav Mavi; Abulhair Saparov; Chen Zhao (CoRR, 2023)

Personas as a Way to Model Truthfulness in Language Models. - Nitish Joshi; Javier Rando; Abulhair Saparov; Najoung Kim; He He 001 (EMNLP, 2024)

LLMs Are Prone to Fallacies in Causal Inference. - Nitish Joshi; Abulhair Saparov; Yixin Wang; He He 001 (EMNLP, 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 (ICML, 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; et al. (CoRR, 2024)

A Practical Review of Mechanistic Interpretability for Transformer-Based Language Models. - Daking Rai; Yilun Zhou; Shi Feng; Abulhair Saparov; Ziyu Yao 002 (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; et al. (Trans. Mach. Learn. Res., 2024)

MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs. - Andreas Opedal; Haruki Shirakami; Bernhard Schölkopf; Abulhair Saparov; Mrinmaya Sachan (ICLR, 2025)

Transformers Struggle to Learn to Search. - Abulhair Saparov; Srushti Ajay Pawar; Shreyas Pimpalgaonkar; Nitish Joshi; Richard Yuanzhe Pang; Vishakh Padmakumar; Mehran Kazemi; Najoung Kim; He He 001 (ICLR, 2025)

Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective. - Zhoujun Cheng; Shibo Hao; Tianyang Liu 003; Fan Zhou; Yutao Xie; Feng Yao; Yuexin Bian; Yonghao Zhuang 001; Nilabjo Dey; Yuheng Zha; Yi Gu 002; Kun Zhou; et al. (CoRR, 2025)

Language Models Might Not Understand You: Evaluating Theory of Mind via Story Prompting. - Nathaniel Getachew; Abulhair Saparov (CoRR, 2025)