Relational Logistic Regression: The Directed Analog of Markov Logic Networks. - Seyed Mehran Kazemi; David Buchman; Kristian Kersting; Sriraam Natarajan; David Poole 001 (StarAI@AAAI, 2014)

Elimination Ordering in Lifted First-Order Probabilistic Inference. - Seyed Mehran Kazemi; David Poole 001 (AAAI, 2014)

Relational Logistic Regression. - Seyed Mehran Kazemi; David Buchman; Kristian Kersting; Sriraam Natarajan; David Poole 001 (KR, 2014)

Population Size Extrapolation in Relational Probabilistic Modelling. - David Poole 001; David Buchman; Seyed Mehran Kazemi; Kristian Kersting; Sriraam Natarajan (SUM, 2014)

Lazy Arithmetic Circuits. - Seyed Mehran Kazemi; David Poole 001 (AAAI Workshop: Beyond NP, 2016)

Knowledge Compilation for Lifted Probabilistic Inference: Compiling to a Low-Level Language. - Seyed Mehran Kazemi; David Poole 001 (KR, 2016)

New Liftable Classes for First-Order Probabilistic Inference. - Seyed Mehran Kazemi; Angelika Kimmig; Guy Van den Broeck; David Poole 001 (NIPS, 2016)

A Learning Algorithm for Relational Logistic Regression: Preliminary Results. - Bahare Fatemi; Seyed Mehran Kazemi; David Poole 001 (CoRR, 2016)

Why is Compiling Lifted Inference into a Low-Level Language so Effective? - Seyed Mehran Kazemi; David Poole 001 (CoRR, 2016)

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 001 (CoRR, 2017)

Domain Recursion for Lifted Inference with Existential Quantifiers. - Seyed Mehran Kazemi; Angelika Kimmig; Guy Van den Broeck; David Poole 001 (CoRR, 2017)

RelNN: A Deep Neural Model for Relational Learning. - Seyed Mehran Kazemi; David Poole 001 (AAAI, 2018)

SimplE Embedding for Link Prediction in Knowledge Graphs. - Seyed Mehran Kazemi; David Poole 001 (NeurIPS, 2018)

Record Linkage to Match Customer Names: A Probabilistic Approach. - Bahare Fatemi; Seyed Mehran Kazemi; David Poole 001 (CoRR, 2018)

Bridging Weighted Rules and Graph Random Walks for Statistical Relational Models. - Seyed Mehran Kazemi; David Poole 001 (Frontiers Robotics AI, 2018)

Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey. - Seyed Mehran Kazemi; Rishab Goel; Kshitij Jain 001; Ivan Kobyzev; Akshay Sethi; Peter Forsyth; Pascal Poupart (CoRR, 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)

Diachronic Embedding for Temporal Knowledge Graph Completion. - Rishab Goel; Seyed Mehran Kazemi; Marcus A. Brubaker; Pascal Poupart (AAAI, 2020)

Out-of-Sample Representation Learning for Knowledge Graphs. - Marjan Albooyeh; Rishab Goel; Seyed Mehran Kazemi (EMNLP (Findings), 2020)

Out-of-Sample Representation Learning for Multi-Relational Graphs. - Marjan Albooyeh; Rishab Goel; Seyed Mehran Kazemi (CoRR, 2020)

Representation Learning for Dynamic Graphs: A Survey. - Seyed Mehran Kazemi; Rishab Goel; Kshitij Jain 001; Ivan Kobyzev; Akshay Sethi; Peter Forsyth; Pascal Poupart (J. Mach. Learn. Res., 2020)

SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks. - Bahare Fatemi; Layla El Asri; Seyed Mehran Kazemi (NeurIPS, 2021)

Structure learning for relational logistic regression: an ensemble approach. - Nandini Ramanan; Gautam Kunapuli; Tushar Khot; Bahare Fatemi; Seyed Mehran Kazemi; David Poole 001; Kristian Kersting; Sriraam Natarajan (Data Min. Knowl. Discov., 2021)

Stay Positive: Knowledge Graph Embedding Without Negative Sampling. - Ainaz Hajimoradlou; Mehran Kazemi (CoRR, 2022)

LAMBADA: Backward Chaining for Automated Reasoning in Natural Language. - Mehran Kazemi; Najoung Kim; Deepti Bhatia; Xin Xu; Deepak Ramachandran (ACL (1), 2023)

Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic. - Connor Pryor; Quan Yuan 001; Jeremiah Z. Liu; Mehran Kazemi; Deepak Ramachandran; Tania Bedrax-Weiss; Lise Getoor (ACL (1), 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 (EACL, 2023)

BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information. - Mehran Kazemi; Quan Yuan 001; Deepti Bhatia; Najoung Kim; Xin Xu; Vaiva Imbrasaite; Deepak Ramachandran (NeurIPS, 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)

KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. - Sandeep Silwal; Sara Ahmadian; Andrew Nystrom; Andrew McCallum; Deepak Ramachandran; Seyed Mehran Kazemi (SustaiNLP, 2023)

Understanding Finetuning for Factual Knowledge Extraction from Language Models. - Mehran Kazemi; Sid Mittal; Deepak Ramachandran (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)

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; et al. (CoRR, 2023)

GeomVerse: A Systematic Evaluation of Large Models for Geometric Reasoning. - Mehran Kazemi; Hamidreza Alvari; Ankit Anand; Jialin Wu; Xi Chen 071; Radu Soricut (CoRR, 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)

TaskLAMA: Probing the Complex Task Understanding of Language Models. - Quan Yuan 001; Mehran Kazemi; Xin Xu; Isaac Noble; Vaiva Imbrasaite; Deepak Ramachandran (AAAI, 2024)

ReMI: A Dataset for Reasoning with Multiple Images. - Mehran Kazemi; Nishanth Dikkala; Ankit Anand; Petar Devic; Ishita Dasgupta 001; Fangyu Liu; Bahare Fatemi; Pranjal Awasthi; Sreenivas Gollapudi; Dee Guo; Ahmed Qureshi (NeurIPS, 2024)

Understanding Transformer Reasoning Capabilities via Graph Algorithms. - Clayton Sanford; Bahare Fatemi; Ethan Hall; Anton Tsitsulin; Mehran Kazemi; Jonathan Halcrow; Bryan Perozzi; Vahab Mirrokni (NeurIPS, 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)

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; et al. (CoRR, 2024)

Dr.ICL: Demonstration-Retrieved In-context Learning. - Man Luo 003; Xin Xu; Zhuyun Dai; Panupong Pasupat; Mehran Kazemi; Chitta Baral; Vaiva Imbrasaite; Vincent Y. Zhao (Data Intell., 2024)

In-context Learning with Retrieved Demonstrations for Language Models: A Survey. - Man Luo 003; Xin Xu; Yue Liu; Panupong Pasupat; Mehran Kazemi (Trans. Mach. Learn. Res., 2024)

BIG-Bench Extra Hard. - Mehran Kazemi; Bahare Fatemi; Hritik Bansal; John Palowitch; Chrysovalantis Anastasiou; Sanket Vaibhav Mehta; Lalit K. Jain; Virginia Aglietti; Disha Jindal; Peter Chen; Nishanth Dikkala; Gladys Tyen; et al. (ACL (1), 2025)

Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling. - Hritik Bansal; Arian Hosseini; Rishabh Agarwal; Vinh Q. Tran 002; Mehran Kazemi (ICLR, 2025)

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 (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)

Generative Verifiers: Reward Modeling as Next-Token Prediction. - Lunjun Zhang; Arian Hosseini; Hritik Bansal; Mehran Kazemi; Aviral Kumar; Rishabh Agarwal (ICLR, 2025)

SocialQuotes: Learning Contextual Roles of Social Media Quotes on the Web. - John Palowitch; Hamidreza Alvari; Mehran Kazemi; Tanvir Amin; Filip Radlinski (ICWSM, 2025)

GeoCoder: Solving Geometry Problems by Generating Modular Code through Vision-Language Models. - Aditya Sharma; Aman Dalmia; Mehran Kazemi; Amal Zouaq; Christopher Pal (NAACL (Findings), 2025)

BIG-Bench Extra Hard. - Mehran Kazemi; Bahare Fatemi; Hritik Bansal; John Palowitch; Chrysovalantis Anastasiou; Sanket Vaibhav Mehta; Kshitij Jain 001; Virginia Aglietti; Disha Jindal; Peter Chen; Nishanth Dikkala; Gladys Tyen; et al. (CoRR, 2025)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)

RADAR: Benchmarking Language Models on Imperfect Tabular Data. - Ken Gu; Zhihan Zhang 002; Kate Lin; Yuwei Zhang; Akshay Paruchuri; Hong Yu 001; Mehran Kazemi; Kumar Ayush; A. Ali Heydari; Maxwell A. Xu; Girish Narayanswamy; Yun Liu 013; et al. (CoRR, 2025)

Multi-Turn Puzzles: Evaluating Interactive Reasoning and Strategic Dialogue in LLMs. - Kartikeya Badola; Jonathan Simon; Arian Hosseini; Sara Marie Mc Carthy; Tsendsuren Munkhdalai; Abhimanyu Goyal; Tomás Kociský; Shyam Upadhyay; Bahare Fatemi; Mehran Kazemi (CoRR, 2025)