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ORCIDMehran Kazemi
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2020 – today
- 2024
[c21]Quan Yuan, Mehran Kazemi, Xin Xu, Isaac Noble, Vaiva Imbrasaite, Deepak Ramachandran:
TaskLAMA: Probing the Complex Task Understanding of Language Models. AAAI 2024: 19468-19476- [i37]Man Luo, Xin Xu, Yue Liu, Panupong Pasupat, Mehran Kazemi:
In-context Learning with Retrieved Demonstrations for Language Models: A Survey. CoRR abs/2401.11624 (2024) - [i36]Bryan Perozzi, Bahare Fatemi, Dustin Zelle, Anton Tsitsulin, Seyed Mehran Kazemi, Rami Al-Rfou, Jonathan Halcrow:
Let Your Graph Do the Talking: Encoding Structured Data for LLMs. CoRR abs/2402.05862 (2024) - [i35]Connor Pryor, Quan Yuan, Jeremiah Z. Liu, Mehran Kazemi, Deepak Ramachandran, Tania Bedrax-Weiss, Lise Getoor:
Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic. CoRR abs/2403.17853 (2024) - [i34]Clayton Sanford, Bahare Fatemi, Ethan Hall, Anton Tsitsulin, Seyed Mehran Kazemi, Jonathan Halcrow, Bryan Perozzi, Vahab Mirrokni:
Understanding Transformer Reasoning Capabilities via Graph Algorithms. CoRR abs/2405.18512 (2024) - [i33]Bahare Fatemi, Mehran Kazemi, Anton Tsitsulin, Karishma Malkan, Jinyeong Yim, John Palowitch, Sungyong Seo, Jonathan Halcrow, Bryan Perozzi:
Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning. CoRR abs/2406.09170 (2024) - [i32]Mehran Kazemi, Nishanth Dikkala, Ankit Anand, Petar Devic, Ishita Dasgupta, Fangyu Liu, Bahare Fatemi, Pranjal Awasthi, Dee Guo, Sreenivas Gollapudi, Ahmed Qureshi:
ReMI: A Dataset for Reasoning with Multiple Images. CoRR abs/2406.09175 (2024) - [i31]John Palowitch, Hamidreza Alvari, Mehran Kazemi, Tanvir Amin, Filip Radlinski:
SocialQuotes: Learning Contextual Roles of Social Media Quotes on the Web. CoRR abs/2407.16007 (2024) - [i30]Lunjun Zhang, Arian Hosseini, Hritik Bansal, Mehran Kazemi, Aviral Kumar, Rishabh Agarwal:
Generative Verifiers: Reward Modeling as Next-Token Prediction. CoRR abs/2408.15240 (2024) - [i29]Hritik Bansal, Arian Hosseini, Rishabh Agarwal, Vinh Q. Tran, Mehran Kazemi:
Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling. CoRR abs/2408.16737 (2024) - [i28]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:
Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries. CoRR abs/2409.12640 (2024) - [i27]Aditya Sharma, Aman Dalmia, Mehran Kazemi, Amal Zouaq, Christopher J. Pal:
GeoCoder: Solving Geometry Problems by Generating Modular Code through Vision-Language Models. CoRR abs/2410.13510 (2024) - 2023
- [j4]Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, MohammadHossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab Mirrokni:
Tackling Provably Hard Representative Selection via Graph Neural Networks. Trans. Mach. Learn. Res. 2023 (2023) - [c20]Mehran Kazemi, Najoung Kim, Deepti Bhatia, Xin Xu, Deepak Ramachandran:
LAMBADA: Backward Chaining for Automated Reasoning in Natural Language. ACL (1) 2023: 6547-6568 - [c19]Connor Pryor, Quan Yuan, Jeremiah Z. Liu, Mehran Kazemi, Deepak Ramachandran, Tania Bedrax-Weiss, Lise Getoor:
Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic. ACL (1) 2023: 7631-7652 - [c18]Aditya Sharma, Apoorv Saxena, Chitrank Gupta, Seyed Mehran Kazemi, Partha P. Talukdar, Soumen Chakrabarti:
TwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs. EACL 2023: 2041-2052 - [c17]Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi:
KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. ICLR 2023 - [c16]Mehran Kazemi, Quan Yuan, Deepti Bhatia, Najoung Kim, Xin Xu, Vaiva Imbrasaite, Deepak Ramachandran:
BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information. NeurIPS 2023 - [c15]Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Mehran Kazemi, Najoung Kim, He He:
Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples. NeurIPS 2023 - [c14]Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi:
KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. SustaiNLP 2023: 1-31 - [i26]Mehran Kazemi, Sid Mittal, Deepak Ramachandran:
Understanding Finetuning for Factual Knowledge Extraction from Language Models. CoRR abs/2301.11293 (2023) - [i25]Man Luo, Xin Xu
, Zhuyun Dai, Panupong Pasupat, Seyed Mehran Kazemi, Chitta Baral, Vaiva Imbrasaite, Vincent Y. Zhao:
Dr.ICL: Demonstration-Retrieved In-context Learning. CoRR abs/2305.14128 (2023) - [i24]Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Seyed Mehran Kazemi, Najoung Kim, He He:
Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples. CoRR abs/2305.15269 (2023) - [i23]Mehran Kazemi, Quan Yuan, Deepti Bhatia, Najoung Kim, Xin Xu, Vaiva Imbrasaite, Deepak Ramachandran:
BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information. CoRR abs/2306.07934 (2023) - [i22]Bahare Fatemi, Sami Abu-El-Haija, Anton Tsitsulin, Seyed Mehran Kazemi, Dustin Zelle, Neslihan Bulut, Jonathan Halcrow, Bryan Perozzi:
UGSL: A Unified Framework for Benchmarking Graph Structure Learning. CoRR abs/2308.10737 (2023) - [i21]Quan Yuan, Mehran Kazemi, Xin Xu, Isaac Noble, Vaiva Imbrasaite, Deepak Ramachandran:
TaskLAMA: Probing the Complex Task Understanding of Language Models. CoRR abs/2308.15299 (2023) - [i20]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.:
Gemini: A Family of Highly Capable Multimodal Models. CoRR abs/2312.11805 (2023) - [i19]Mehran Kazemi, Hamidreza Alvari, Ankit Anand, Jialin Wu, Xi Chen, Radu Soricut:
GeomVerse: A Systematic Evaluation of Large Models for Geometric Reasoning. CoRR abs/2312.12241 (2023) - 2022
- [i18]Ainaz Hajimoradlou, Mehran Kazemi:
Stay Positive: Knowledge Graph Embedding Without Negative Sampling. CoRR abs/2201.02661 (2022) - [i17]Seyed Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, MohammadHossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab S. Mirrokni:
Tackling Provably Hard Representative Selection via Graph Neural Networks. CoRR abs/2205.10403 (2022) - [i16]Aditya Sharma, Apoorv Saxena, Chitrank Gupta, Seyed Mehran Kazemi, Partha P. Talukdar, Soumen Chakrabarti:
TwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs. CoRR abs/2210.06281 (2022) - [i15]Seyed Mehran Kazemi, Najoung Kim, Deepti Bhatia, Xin Xu, Deepak Ramachandran:
LAMBADA: Backward Chaining for Automated Reasoning in Natural Language. CoRR abs/2212.13894 (2022) - 2021
- [j3]Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan:
Structure learning for relational logistic regression: an ensemble approach. Data Min. Knowl. Discov. 35(5): 2089-2111 (2021) - [c13]Bahare Fatemi, Layla El Asri, Seyed Mehran Kazemi:
SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks. NeurIPS 2021: 22667-22681 - [i14]Bahare Fatemi, Layla El Asri, Seyed Mehran Kazemi:
SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks. CoRR abs/2102.05034 (2021) - 2020
- [j2]Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain, Ivan Kobyzev, Akshay Sethi, Peter Forsyth, Pascal Poupart:
Representation Learning for Dynamic Graphs: A Survey. J. Mach. Learn. Res. 21: 70:1-70:73 (2020) - [c12]Rishab Goel, Seyed Mehran Kazemi, Marcus A. Brubaker, Pascal Poupart:
Diachronic Embedding for Temporal Knowledge Graph Completion. AAAI 2020: 3988-3995 - [c11]Marjan Albooyeh, Rishab Goel, Seyed Mehran Kazemi:
Out-of-Sample Representation Learning for Knowledge Graphs. EMNLP (Findings) 2020: 2657-2666 - [i13]Marjan Albooyeh, Rishab Goel, Seyed Mehran Kazemi:
Out-of-Sample Representation Learning for Multi-Relational Graphs. CoRR abs/2004.13230 (2020)
2010 – 2019
- 2019
- [i12]Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain, Ivan Kobyzev, Akshay Sethi, Peter Forsyth, Pascal Poupart:
Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey. CoRR abs/1905.11485 (2019) - [i11]Rishab Goel, Seyed Mehran Kazemi, Marcus A. Brubaker, Pascal Poupart:
Diachronic Embedding for Temporal Knowledge Graph Completion. CoRR abs/1907.03143 (2019) - [i10]Seyed Mehran Kazemi, Rishab Goel, Sepehr Eghbali, Janahan Ramanan, Jaspreet Sahota, Sanjay Thakur, Stella Wu, Cathal Smyth, Pascal Poupart, Marcus A. Brubaker:
Time2Vec: Learning a Vector Representation of Time. CoRR abs/1907.05321 (2019) - 2018
- [j1]Seyed Mehran Kazemi, David Poole:
Bridging Weighted Rules and Graph Random Walks for Statistical Relational Models. Frontiers Robotics AI 5: 8 (2018) - [c10]Seyed Mehran Kazemi, David Poole:
RelNN: A Deep Neural Model for Relational Learning. AAAI 2018: 6367-6375 - [c9]Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan:
Structure Learning for Relational Logistic Regression: An Ensemble Approach. KR 2018: 661-662 - [c8]Seyed Mehran Kazemi, David Poole:
SimplE Embedding for Link Prediction in Knowledge Graphs. NeurIPS 2018: 4289-4300 - [i9]Seyed Mehran Kazemi, David Poole:
SimplE Embedding for Link Prediction in Knowledge Graphs. CoRR abs/1802.04868 (2018) - [i8]Bahare Fatemi, Seyed Mehran Kazemi, David Poole:
Record Linkage to Match Customer Names: A Probabilistic Approach. CoRR abs/1806.10928 (2018) - [i7]Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan:
Structure Learning for Relational Logistic Regression: An Ensemble Approach. CoRR abs/1808.02123 (2018) - 2017
- [i6]Seyed Mehran Kazemi, Angelika Kimmig, Guy Van den Broeck, David Poole:
Domain Recursion for Lifted Inference with Existential Quantifiers. CoRR abs/1707.07763 (2017) - [i5]Seyed Mehran Kazemi, Bahare Fatemi, Alexandra Kim, Zilun Peng, Moumita Roy Tora, Xing Zeng, Matthew C. Dirks, David Poole:
Comparing Aggregators for Relational Probabilistic Models. CoRR abs/1707.07785 (2017) - [i4]Seyed Mehran Kazemi, David Poole:
RelNN: A Deep Neural Model for Relational Learning. CoRR abs/1712.02831 (2017) - 2016
- [c7]Seyed Mehran Kazemi, David Poole:
Lazy Arithmetic Circuits. AAAI Workshop: Beyond NP 2016 - [c6]Seyed Mehran Kazemi, David Poole:
Knowledge Compilation for Lifted Probabilistic Inference: Compiling to a Low-Level Language. KR 2016: 561-564 - [c5]Seyed Mehran Kazemi, Angelika Kimmig, Guy Van den Broeck, David Poole:
New Liftable Classes for First-Order Probabilistic Inference. NIPS 2016: 3117-3125 - [i3]Seyed Mehran Kazemi, David Poole:
Why is Compiling Lifted Inference into a Low-Level Language so Effective? CoRR abs/1606.04512 (2016) - [i2]Bahare Fatemi, Seyed Mehran Kazemi, David Poole:
A Learning Algorithm for Relational Logistic Regression: Preliminary Results. CoRR abs/1606.08531 (2016) - [i1]Seyed Mehran Kazemi, Angelika Kimmig, Guy Van den Broeck, David Poole:
New Liftable Classes for First-Order Probabilistic Inference. CoRR abs/1610.08445 (2016) - 2014
- [c4]Seyed Mehran Kazemi, David Buchman, Kristian Kersting, Sriraam Natarajan, David Poole:
Relational Logistic Regression: The Directed Analog of Markov Logic Networks. StarAI@AAAI 2014 - [c3]Seyed Mehran Kazemi, David Poole:
Elimination Ordering in Lifted First-Order Probabilistic Inference. AAAI 2014: 863-870 - [c2]Seyed Mehran Kazemi, David Buchman, Kristian Kersting, Sriraam Natarajan, David Poole:
Relational Logistic Regression. KR 2014 - [c1]David Poole, David Buchman, Seyed Mehran Kazemi, Kristian Kersting, Sriraam Natarajan:
Population Size Extrapolation in Relational Probabilistic Modelling. SUM 2014: 292-305
Coauthor Index
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