A Learning Algorithm for Relational Logistic Regression: Preliminary Results. - Bahare Fatemi; 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)

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

Improved Knowledge Graph Embedding Using Background Taxonomic Information. - Bahare Fatemi; Siamak Ravanbakhsh; David Poole 001 (AAAI, 2019)

Knowledge Hypergraphs: Extending Knowledge Graphs Beyond Binary Relations. - Bahare Fatemi; Perouz Taslakian; David Vázquez 001; David Poole 001 (CoRR, 2019)

Knowledge Hypergraphs: Prediction Beyond Binary Relations. - Bahare Fatemi; Perouz Taslakian; David Vázquez 001; David Poole 001 (IJCAI, 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)

Using Graph Algorithms to Pretrain Graph Completion Transformers. - Jonathan Pilault; Michael Galkin; Bahare Fatemi; Perouz Taslakian; David Vázquez 001; Christopher Pal (CoRR, 2022)

19th International Workshop on Mining and Learning with Graphs (MLG). - Neil Shah; Shobeir Fakhraei; Da Zheng; Bahare Fatemi; Leman Akoglu (KDD, 2023)

TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs. - Phitchaya Mangpo Phothilimthana; Sami Abu-El-Haija; Kaidi Cao; Bahare Fatemi; Michael Burrows; Charith Mendis; Bryan Perozzi (NeurIPS, 2023)

SubMix: Learning to Mix Graph Sampling Heuristics. - Sami Abu-El-Haija; Joshua V. Dillon; Bahare Fatemi; Kyriakos Axiotis; Neslihan Bulut; Johannes Gasteiger; Bryan Perozzi; MohammadHossein Bateni (UAI, 2023)

Learning to Substitute Ingredients in Recipes. - Bahare Fatemi; Quentin Duval; Rohit Girdhar; Michal Drozdzal; Adriana Romero-Soriano (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)

TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs. - Phitchaya Mangpo Phothilimthana; Sami Abu-El-Haija; Kaidi Cao; Bahare Fatemi; Charith Mendis; Bryan Perozzi (CoRR, 2023)

Knowledge Hypergraph Embedding Meets Relational Algebra. - Bahare Fatemi; Perouz Taslakian; David Vázquez 001; David Poole 001 (J. Mach. Learn. Res., 2023)

Geometric deep learning of particle motion by MAGIK. - Bahare Fatemi; Jonathan Halcrow; Khuloud Jaqaman (Nat. Mac. Intell., 2023)

Talk like a Graph: Encoding Graphs for Large Language Models. - Bahare Fatemi; Jonathan Halcrow; Bryan Perozzi (ICLR, 2024)

Graph Reasoning with LLMs (GReaL). - Anton Tsitsulin; Bryan Perozzi; Bahare Fatemi; Jonathan J. Halcrow (KDD, 2024)

Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights. - Zhikai Chen; Haitao Mao; Jingzhe Liu; Yu Song; Bingheng Li; Wei Jin 009; Bahare Fatemi; Anton Tsitsulin; Bryan Perozzi; Hui Liu 031; Jiliang Tang (NeurIPS, 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)

Don't Forget to Connect! Improving RAG with Graph-based Reranking. - Jialin Dong; Bahare Fatemi; Bryan Perozzi; Lin F. Yang; Anton Tsitsulin (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)

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)

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)

CausalGraph2LLM: Evaluating LLMs for Causal Queries. - Ivaxi Sheth; Bahare Fatemi; Mario Fritz (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)

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)