| 2026 | ACL | Constructing Interpretable Features from Compositional Neuron Groups. | Or David Shafran, Atticus Geiger, Mor Geva |
| 2026 | EACL | Detecting (Un)answerability in Large Language Models with Linear Directions. | Maor Juliet Lavi, Tova Milo, Mor Geva |
| 2025 | ACL | Performance Gap in Entity Knowledge Extraction Across Modalities in Vision Language Models. | Ido Cohen, Daniela Gottesman, Mor Geva, Raja Giryes |
| 2025 | ACL | Inferring Functionality of Attention Heads from their Parameters. | Amit Elhelo, Mor Geva |
| 2025 | ACL | Eliciting Textual Descriptions from Representations of Continuous Prompts. | Daniela Gottesman, Mor Geva, Dana Ramati |
| 2025 | ACL | Enhancing Automated Interpretability with Output-Centric Feature Descriptions. | Yoav Gur-Arieh, Roy Mayan, Chen Agassy, Atticus Geiger, Mor Geva |
| 2025 | ACL | Do Large Language Models Perform Latent Multi-Hop Reasoning without Exploiting Shortcuts? | Sohee Yang, Nora Kassner, Elena Gribovskaya, Sebastian Riedel, Mor Geva |
| 2025 | EMNLP | Precise In-Parameter Concept Erasure in Large Language Models. | Yoav Gur-Arieh, Clara Suslik, Yihuai Hong, Fazl Barez, Mor Geva |
| 2025 | EMNLP | Intrinsic Test of Unlearning Using Parametric Knowledge Traces. | Yihuai Hong, Lei Yu, Haiqin Yang, Shauli Ravfogel, Mor Geva |
| 2025 | EMNLP | How Well Can Reasoning Models Identify and Recover from Unhelpful Thoughts? | Sohee Yang, Sang-Woo Lee, Nora Kassner, Daniela Gottesman, Sebastian Riedel, Mor Geva |
| 2025 | ICLR | Towards Interpreting Visual Information Processing in Vision-Language Models. | Clement Neo, Luke Ong, Philip Torr, Mor Geva, David Krueger, Fazl Barez |
| 2025 | ICML | Why Is Spatial Reasoning Hard for VLMs? An Attention Mechanism Perspective on Focus Areas. | Shiqi Chen, Tongyao Zhu, Ruochen Zhou, Jinghan Zhang, Siyang Gao, Juan Carlos Niebles, Mor Geva, Junxian He, Jiajun Wu, Manling Li |
| 2025 | NAACL | Language Models Encode Numbers Using Digit Representations in Base 10. | Amit Arnold Levy, Mor Geva |
| 2024 | ACL | The Hidden Space of Transformer Language Adapters. | Jesujoba Alabi, Marius Mosbach, Matan Eyal, Dietrich Klakow, Mor Geva |
| 2024 | ACL | RAVEL: Evaluating Interpretability Methods on Disentangling Language Model Representations. | Jing Huang, Zhengxuan Wu, Christopher Potts, Mor Geva, Atticus Geiger |
| 2024 | ACL | A Chain-of-Thought Is as Strong as Its Weakest Link: A Benchmark for Verifiers of Reasoning Chains. | Alon Jacovi, Yonatan Bitton, Bernd Bohnet, Jonathan Herzig, Or Honovich, Michael Tseng, Michael Collins, Roee Aharoni, Mor Geva |
| 2024 | ACL | Do Large Language Models Latently Perform Multi-Hop Reasoning? | Sohee Yang, Elena Gribovskaya, Nora Kassner, Mor Geva, Sebastian Riedel |
| 2024 | ACL | Narrowing the Knowledge Evaluation Gap: Open-Domain Question Answering with Multi-Granularity Answers. | Gal Yona, Roee Aharoni, Mor Geva |
| 2024 | COLING | Jump to Conclusions: Short-Cutting Transformers with Linear Transformations. | Alexander Yom Din, Taelin Karidi, Leshem Choshen, Mor Geva |
| 2024 | EMNLP | Hopping Too Late: Exploring the Limitations of Large Language Models on Multi-Hop Queries. | Eden Biran, Daniela Gottesman, Sohee Yang, Mor Geva, Amir Globerson |
| 2024 | EMNLP | Estimating Knowledge in Large Language Models Without Generating a Single Token. | Daniela Gottesman, Mor Geva |
| 2024 | EMNLP | Backward Lens: Projecting Language Model Gradients into the Vocabulary Space. | Shahar Katz, Yonatan Belinkov, Mor Geva, Lior Wolf |
| 2024 | EMNLP | From Insights to Actions: The Impact of Interpretability and Analysis Research on NLP. | Marius Mosbach, Vagrant Gautam, Toms Vergara Browne, Dietrich Klakow, Mor Geva |
| 2024 | EMNLP | Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words? | Gal Yona, Roee Aharoni, Mor Geva |
| 2024 | ICLR | The Hidden Language of Diffusion Models. | Hila Chefer, Oran Lang, Mor Geva, Volodymyr Polosukhin, Assaf Shocher, Michal Irani, Inbar Mosseri, Lior Wolf |
| 2024 | ICML | Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models. | Asma Ghandeharioun, Avi Caciularu, Adam Pearce, Lucas Dixon, Mor Geva |
| 2023 | ACL | Analyzing Transformers in Embedding Space. | Guy Dar, Mor Geva, Ankit Gupta, Jonathan Berant |
| 2023 | EACL | Crawling The Internal Knowledge-Base of Language Models. | Roi Cohen, Mor Geva, Jonathan Berant, Amir Globerson |
| 2023 | EACL | Understanding Transformer Memorization Recall Through Idioms. | Adi Haviv, Ido Cohen, Jacob Gidron, Roei Schuster, Yoav Goldberg, Mor Geva |
| 2023 | EACL | Don't Blame the Annotator: Bias Already Starts in the Annotation Instructions. | Mihir Parmar, Swaroop Mishra, Mor Geva, Chitta Baral |
| 2023 | EMNLP | LM vs LM: Detecting Factual Errors via Cross Examination. | Roi Cohen, May Hamri, Mor Geva, Amir Globerson |
| 2023 | EMNLP | Dissecting Recall of Factual Associations in Auto-Regressive Language Models. | Mor Geva, Jasmijn Bastings, Katja Filippova, Amir Globerson |
| 2023 | EMNLP | In-Context Learning Creates Task Vectors. | Roee Hendel, Mor Geva, Amir Globerson |
| 2023 | EMNLP | CRoW: Benchmarking Commonsense Reasoning in Real-World Tasks. | Mete Ismayilzada, Debjit Paul, Syrielle Montariol, Mor Geva, Antoine Bosselut |
| 2023 | EMNLP | A Comprehensive Evaluation of Tool-Assisted Generation Strategies. | Alon Jacovi, Avi Caciularu, Jonathan Herzig, Roee Aharoni, Bernd Bohnet, Mor Geva |
| 2022 | EMNLP | SCROLLS: Standardized CompaRison Over Long Language Sequences. | Uri Shaham, Elad Segal, Maor Ivgi, Avia Efrat, Ori Yoran, Adi Haviv, Ankit Gupta, Wenhan Xiong, Mor Geva, Jonathan Berant, Omer Levy |
| 2022 | EMNLP | LM-Debugger: An Interactive Tool for Inspection and Intervention in Transformer-Based Language Models. | Mor Geva, Avi Caciularu, Guy Dar, Paul Roit, Shoval Sadde, Micah Shlain, Bar Tamir, Yoav Goldberg |
| 2022 | EMNLP | Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Space. | Mor Geva, Avi Caciularu, Kevin Ro Wang, Yoav Goldberg |
| 2022 | EMNLP | Inferring Implicit Relations in Complex Questions with Language Models. | Uri Katz, Mor Geva, Jonathan Berant |
| 2021 | EMNLP | What's in Your Head? Emergent Behaviour in Multi-Task Transformer Models. | Mor Geva, Uri Katz, Aviv Ben-Arie, Jonathan Berant |
| 2021 | EMNLP | Transformer Feed-Forward Layers Are Key-Value Memories. | Mor Geva, Roei Schuster, Jonathan Berant, Omer Levy |
| 2020 | ACL | Injecting Numerical Reasoning Skills into Language Models. | Mor Geva, Ankit Gupta, Jonathan Berant |
| 2019 | EMNLP | Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets. | Mor Geva, Yoav Goldberg, Jonathan Berant |
| 2019 | NAACL | DiscoFuse: A Large-Scale Dataset for Discourse-Based Sentence Fusion. | Mor Geva, Eric Malmi, Idan Szpektor, Jonathan Berant |
| 2018 | COLING | Learning to Search in Long Documents Using Document Structure. | Mor Geva, Jonathan Berant |