Mehran Kazemi

According to our database, Mehran Kazemi authored at least 48 papers between 2014 and 2024.

Collaborative distances:

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

2024

Transformers Struggle to Learn to Search.

Abulhair Saparov, Srushti Pawar, Shreyas Pimpalgaonkar, Nitish Joshi, Richard Yuanzhe Pang, Vishakh Padmakumar, Seyed Mehran Kazemi, Najoung Kim, He He

CoRR, 2024

GeoCoder: Solving Geometry Problems by Generating Modular Code through Vision-Language Models.

Aditya Sharma, Aman Dalmia, Mehran Kazemi, Amal Zouaq, Christopher J. Pal

CoRR, 2024

Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries.

Kiran Vodrahalli, Santiago Ontanon, Nilesh Tripuraneni, Kelvin Xu, Sanil Jain, Rakesh Shivanna, Jeffrey Hui, Nishanth Dikkala, Mehran Kazemi, Bahare Fatemi, Rohan Anil, Ethan Dyer, Siamak Shakeri, Roopali Vij, Harsh Mehta, Vinay V. Ramasesh, Quoc Le, Ed H. Chi, Yifeng Lu, Orhan Firat, Angeliki Lazaridou, Jean-Baptiste Lespiau, Nithya Attaluri, Kate Olszewska

CoRR, 2024

Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling.

Hritik Bansal, Arian Hosseini, Rishabh Agarwal, Vinh Q. Tran, Mehran Kazemi

CoRR, 2024

Generative Verifiers: Reward Modeling as Next-Token Prediction.

Lunjun Zhang, Arian Hosseini, Hritik Bansal, Mehran Kazemi, Aviral Kumar, Rishabh Agarwal

CoRR, 2024

SocialQuotes: Learning Contextual Roles of Social Media Quotes on the Web.

John Palowitch, Hamidreza Alvari, Mehran Kazemi, Tanvir Amin, Filip Radlinski

CoRR, 2024

ReMI: A Dataset for Reasoning with Multiple Images.

Mehran Kazemi, Nishanth Dikkala, Ankit Anand, Petar Devic, Ishita Dasgupta, Fangyu Liu, Bahare Fatemi, Pranjal Awasthi, Dee Guo, Sreenivas Gollapudi, Ahmed Qureshi

CoRR, 2024

Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning.

Bahare Fatemi, Mehran Kazemi, Anton Tsitsulin, Karishma Malkan, Jinyeong Yim, John Palowitch, Sungyong Seo, Jonathan Halcrow, Bryan Perozzi

CoRR, 2024

Understanding Transformer Reasoning Capabilities via Graph Algorithms.

Clayton Sanford, Bahare Fatemi, Ethan Hall, Anton Tsitsulin, Seyed Mehran Kazemi, Jonathan Halcrow, Bryan Perozzi, Vahab Mirrokni

CoRR, 2024

Let Your Graph Do the Talking: Encoding Structured Data for LLMs.

Bryan Perozzi, Bahare Fatemi, Dustin Zelle, Anton Tsitsulin, Seyed Mehran Kazemi, Rami Al-Rfou, Jonathan Halcrow

CoRR, 2024

In-context Learning with Retrieved Demonstrations for Language Models: A Survey.

Man Luo, Xin Xu, Yue Liu, Panupong Pasupat, Mehran Kazemi

CoRR, 2024

TaskLAMA: Probing the Complex Task Understanding of Language Models.

Quan Yuan, Mehran Kazemi, Xin Xu, Isaac Noble, Vaiva Imbrasaite, Deepak Ramachandran

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Tackling Provably Hard Representative Selection via Graph Neural Networks.

Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, MohammadHossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab Mirrokni

Trans. Mach. Learn. Res., 2023

GeomVerse: A Systematic Evaluation of Large Models for Geometric Reasoning.

Mehran Kazemi, Hamidreza Alvari, Ankit Anand, Jialin Wu, Xi Chen, Radu Soricut

CoRR, 2023

Gemini: A Family of Highly Capable Multimodal Models.

Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M. Dai, Anja Hauth, Katie Millican, David Silver, Slav Petrov, Melvin Johnson, Ioannis Antonoglou, Julian Schrittwieser, Amelia Glaese, Jilin Chen, Emily Pitler, Timothy P. Lillicrap, Angeliki Lazaridou, Orhan Firat, James Molloy, Michael Isard, Paul Ronald Barham, Tom Hennigan, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, Ryan Doherty, Eli Collins, Clemens Meyer, Eliza Rutherford, Erica Moreira, Kareem Ayoub, Megha Goel, George Tucker, Enrique Piqueras, Maxim Krikun, Iain Barr, Nikolay Savinov, Ivo Danihelka, Becca Roelofs, Anaïs White, Anders Andreassen, Tamara von Glehn, Lakshman Yagati, Mehran Kazemi, Lucas Gonzalez, Misha Khalman, Jakub Sygnowski, et al.

CoRR, 2023

UGSL: A Unified Framework for Benchmarking Graph Structure Learning.

Bahare Fatemi, Sami Abu-El-Haija, Anton Tsitsulin, Seyed Mehran Kazemi, Dustin Zelle, Neslihan Bulut, Jonathan Halcrow, Bryan Perozzi

CoRR, 2023

Dr.ICL: Demonstration-Retrieved In-context Learning.

Man Luo, Xin Xu, Zhuyun Dai, Panupong Pasupat, Seyed Mehran Kazemi, Chitta Baral, Vaiva Imbrasaite, Vincent Y. Zhao

CoRR, 2023

Understanding Finetuning for Factual Knowledge Extraction from Language Models.

Mehran Kazemi, Sid Mittal, Deepak Ramachandran

CoRR, 2023

KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals.

Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi

Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing, 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

BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information.

Mehran Kazemi, Quan Yuan, Deepti Bhatia, Najoung Kim, Xin Xu, Vaiva Imbrasaite, Deepak Ramachandran

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

TwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs.

Aditya Sharma, Apoorv Saxena, Chitrank Gupta, Seyed Mehran Kazemi, Partha P. Talukdar, Soumen Chakrabarti

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic.

Connor Pryor, Quan Yuan, Jeremiah Z. Liu, Mehran Kazemi, Deepak Ramachandran, Tania Bedrax-Weiss, Lise Getoor

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

LAMBADA: Backward Chaining for Automated Reasoning in Natural Language.

Mehran Kazemi, Najoung Kim, Deepti Bhatia, Xin Xu, Deepak Ramachandran

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Stay Positive: Knowledge Graph Embedding Without Negative Sampling.

Ainaz Hajimoradlou, Mehran Kazemi

CoRR, 2022

2021

Structure learning for relational logistic regression: an ensemble approach.

Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan

Data Min. Knowl. Discov., 2021

SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks.

Bahare Fatemi, Layla El Asri, Seyed Mehran Kazemi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Representation Learning for Dynamic Graphs: A Survey.

Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain, Ivan Kobyzev, Akshay Sethi, Peter Forsyth, Pascal Poupart

J. Mach. Learn. Res., 2020

Out-of-Sample Representation Learning for Multi-Relational Graphs.

Marjan Albooyeh, Rishab Goel, Seyed Mehran Kazemi

CoRR, 2020

Out-of-Sample Representation Learning for Knowledge Graphs.

Marjan Albooyeh, Rishab Goel, Seyed Mehran Kazemi

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Diachronic Embedding for Temporal Knowledge Graph Completion.

Rishab Goel, Seyed Mehran Kazemi, Marcus A. Brubaker, Pascal Poupart

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Time2Vec: Learning a Vector Representation of Time.

Seyed Mehran Kazemi, Rishab Goel, Sepehr Eghbali, Janahan Ramanan, Jaspreet Sahota, Sanjay Thakur, Stella Wu, Cathal Smyth, Pascal Poupart, Marcus A. Brubaker

CoRR, 2019

Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey.

Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain, Ivan Kobyzev, Akshay Sethi, Peter Forsyth, Pascal Poupart

CoRR, 2019

2018

Bridging Weighted Rules and Graph Random Walks for Statistical Relational Models.

Seyed Mehran Kazemi, David Poole

Frontiers Robotics AI, 2018

Record Linkage to Match Customer Names: A Probabilistic Approach.

Bahare Fatemi, Seyed Mehran Kazemi, David Poole

CoRR, 2018

SimplE Embedding for Link Prediction in Knowledge Graphs.

Seyed Mehran Kazemi, David Poole

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

RelNN: A Deep Neural Model for Relational Learning.

Seyed Mehran Kazemi, David Poole

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Domain Recursion for Lifted Inference with Existential Quantifiers.

Seyed Mehran Kazemi, Angelika Kimmig, Guy Van den Broeck, David Poole

CoRR, 2017

Comparing Aggregators for Relational Probabilistic Models.

Seyed Mehran Kazemi, Bahare Fatemi, Alexandra Kim, Zilun Peng, Moumita Roy Tora, Xing Zeng, Matthew C. Dirks, David Poole

CoRR, 2017

2016

Why is Compiling Lifted Inference into a Low-Level Language so Effective?

Seyed Mehran Kazemi, David Poole

CoRR, 2016

A Learning Algorithm for Relational Logistic Regression: Preliminary Results.

Bahare Fatemi, Seyed Mehran Kazemi, David Poole

CoRR, 2016

New Liftable Classes for First-Order Probabilistic Inference.

Seyed Mehran Kazemi, Angelika Kimmig, Guy Van den Broeck, David Poole

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Knowledge Compilation for Lifted Probabilistic Inference: Compiling to a Low-Level Language.

Seyed Mehran Kazemi, David Poole

Proceedings of the Principles of Knowledge Representation and Reasoning: Proceedings of the Fifteenth International Conference, 2016

Lazy Arithmetic Circuits.

Seyed Mehran Kazemi, David Poole

Proceedings of the Beyond NP, 2016

2014

Population Size Extrapolation in Relational Probabilistic Modelling.

David Poole, David Buchman, Seyed Mehran Kazemi, Kristian Kersting, Sriraam Natarajan

Proceedings of the Scalable Uncertainty Management - 8th International Conference, 2014

Relational Logistic Regression.

Seyed Mehran Kazemi, David Buchman, Kristian Kersting, Sriraam Natarajan, David Poole

Proceedings of the Principles of Knowledge Representation and Reasoning: Proceedings of the Fourteenth International Conference, 2014

Elimination Ordering in Lifted First-Order Probabilistic Inference.

Seyed Mehran Kazemi, David Poole

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Relational Logistic Regression: The Directed Analog of Markov Logic Networks.

Seyed Mehran Kazemi, David Buchman, Kristian Kersting, Sriraam Natarajan, David Poole

Proceedings of the Statistical Relational Artificial Intelligence, 2014