Translating Dialectal Arabic to English. - Hassan Sajjad 001; Kareem Darwish; Yonatan Belinkov (ACL (2), 2013)

arTenTen: Arabic Corpus and Word Sketches. - Tressy Arts; Yonatan Belinkov; Nizar Habash; Adam Kilgarriff; Vit Suchomel (J. King Saud Univ. Comput. Inf. Sci., 2014)

Exploring Compositional Architectures and Word Vector Representations for Prepositional Phrase Attachment. - Yonatan Belinkov; Tao Lei 001; Regina Barzilay; Amir Globerson (Trans. Assoc. Comput. Linguistics, 2014)

Arabic Diacritization with Recurrent Neural Networks. - Yonatan Belinkov; James R. Glass (EMNLP, 2015)

VectorSLU: A Continuous Word Vector Approach to Answer Selection in Community Question Answering Systems. - Yonatan Belinkov; Mitra Mohtarami; Scott Cyphers; James R. Glass (SemEval@NAACL-HLT, 2015)

Answer Selection in Arabic Community Question Answering: A Feature-Rich Approach. - Yonatan Belinkov; Alberto Barrón-Cedeño; Hamdy Mubarak (ANLP@ACL, 2015)

Erratum: "Exploring Compositional Architectures and Word Vector Representations for Prepositional Phrase Attachment". - Yonatan Belinkov; Tao Lei 001; Regina Barzilay; Amir Globerson (Trans. Assoc. Comput. Linguistics, 2015)

Neural Attention for Learning to Rank Questions in Community Question Answering. - Salvatore Romeo; Giovanni Da San Martino; Alberto Barrón-Cedeño; Alessandro Moschitti; Yonatan Belinkov; Wei-Ning Hsu; Yu Zhang 033; Mitra Mohtarami; James R. Glass (COLING, 2016)

Shamela: A Large-Scale Historical Arabic Corpus. - Yonatan Belinkov; Alexander Magidow; Maxim Romanov; Avi Shmidman; Moshe Koppel (LT4DH@COLING, 2016)

SLS at SemEval-2016 Task 3: Neural-based Approaches for Ranking in Community Question Answering. - Mitra Mohtarami; Yonatan Belinkov; Wei-Ning Hsu; Yu Zhang 033; Tao Lei; Kfir Bar; Scott Cyphers; James R. Glass (SemEval@NAACL-HLT, 2016)

Improving Sequence to Sequence Learning for Morphological Inflection Generation: The BIU-MIT Systems for the SIGMORPHON 2016 Shared Task for Morphological Reinflection. - Roee Aharoni; Yoav Goldberg; Yonatan Belinkov (SIGMORPHON, 2016)

A Character-level Convolutional Neural Network for Distinguishing Similar Languages and Dialects. - Yonatan Belinkov; James R. Glass (VarDial@COLING, 2016)

Large-Scale Machine Translation between Arabic and Hebrew: Available Corpora and Initial Results. - Yonatan Belinkov; James R. Glass (CoRR, 2016)

What do Neural Machine Translation Models Learn about Morphology? - Yonatan Belinkov; Nadir Durrani; Fahim Dalvi; Hassan Sajjad 001; James R. Glass (ACL (1), 2017)

Challenging Language-Dependent Segmentation for Arabic: An Application to Machine Translation and Part-of-Speech Tagging. - Hassan Sajjad 001; Fahim Dalvi; Nadir Durrani; Ahmed Abdelali; Yonatan Belinkov; Stephan Vogel (ACL (2), 2017)

Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks. - Yossi Adi; Einat Kermany; Yonatan Belinkov; Ofer Lavi; Yoav Goldberg (ICLR (Poster), 2017)

Evaluating Layers of Representation in Neural Machine Translation on Part-of-Speech and Semantic Tagging Tasks. - Yonatan Belinkov; Lluís Màrquez; Hassan Sajjad 001; Nadir Durrani; Fahim Dalvi; James R. Glass (IJCNLP(1), 2017)

Understanding and Improving Morphological Learning in the Neural Machine Translation Decoder. - Fahim Dalvi; Nadir Durrani; Hassan Sajjad 001; Yonatan Belinkov; Stephan Vogel (IJCNLP(1), 2017)

QMDIS: QCRI-MIT Advanced Dialect Identification System. - Sameer Khurana; Maryam Najafian; Ahmed Ali 002; Tuka Al Hanai; Yonatan Belinkov; James R. Glass (INTERSPEECH, 2017)

Neural Machine Translation Training in a Multi-Domain Scenario. - Hassan Sajjad 001; Nadir Durrani; Fahim Dalvi; Yonatan Belinkov; Stephan Vogel (IWSLT, 2017)

Analyzing Hidden Representations in End-to-End Automatic Speech Recognition Systems. - Yonatan Belinkov; James R. Glass (NIPS, 2017)

Analysis of sentence embedding models using prediction tasks in natural language processing. - Yossi Adi; Einat Kermany; Yonatan Belinkov; Ofer Lavi; Yoav Goldberg (IBM J. Res. Dev., 2017)

Synthetic and Natural Noise Both Break Neural Machine Translation. - Yonatan Belinkov; Yonatan Bisk (ICLR, 2018)

On the Evaluation of Semantic Phenomena in Neural Machine Translation Using Natural Language Inference. - Adam Poliak; Yonatan Belinkov; James R. Glass; Benjamin Van Durme (NAACL-HLT (2), 2018)

On Evaluating the Generalization of LSTM Models in Formal Languages. - Mirac Suzgun; Yonatan Belinkov; Stuart M. Shieber (CoRR, 2018)

On internal language representations in deep learning: an analysis of machine translation and speech recognition. - Yonatan Belinkov (2018)

What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models. - Fahim Dalvi; Nadir Durrani; Hassan Sajjad 001; Yonatan Belinkov; Anthony Bau; James R. Glass (AAAI, 2019)

NeuroX: A Toolkit for Analyzing Individual Neurons in Neural Networks. - Fahim Dalvi; Avery Nortonsmith; Anthony Bau; Yonatan Belinkov; Hassan Sajjad 001; Nadir Durrani; James R. Glass (AAAI, 2019)

Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference. - Yonatan Belinkov; Adam Poliak; Stuart M. Shieber; Benjamin Van Durme; Alexander M. Rush (ACL (1), 2019)

Improving Neural Language Models by Segmenting, Attending, and Predicting the Future. - Hongyin Luo; Lan Jiang; Yonatan Belinkov; James R. Glass (ACL (1), 2019)

Analyzing the Structure of Attention in a Transformer Language Model. - Jesse Vig; Yonatan Belinkov (BlackboxNLP@ACL, 2019)

Character-based Surprisal as a Model of Reading Difficulty in the Presence of Errors. - Michael Hahn 001; Frank Keller; Yonatan Bisk; Yonatan Belinkov (CogSci, 2019)

Identifying and Controlling Important Neurons in Neural Machine Translation. - Anthony Bau; Yonatan Belinkov; Hassan Sajjad 001; Nadir Durrani; Fahim Dalvi; James R. Glass (ICLR (Poster), 2019)

Analyzing Phonetic and Graphemic Representations in End-to-End Automatic Speech Recognition. - Yonatan Belinkov; Ahmed Ali 002; James R. Glass (INTERSPEECH, 2019)

One Size Does Not Fit All: Comparing NMT Representations of Different Granularities. - Nadir Durrani; Fahim Dalvi; Hassan Sajjad 001; Yonatan Belinkov; Preslav Nakov (NAACL-HLT (1), 2019)

Linguistic Knowledge and Transferability of Contextual Representations. - Nelson F. Liu; Matt Gardner 001; Yonatan Belinkov; Matthew E. Peters; Noah A. Smith (NAACL-HLT (1), 2019)

On Adversarial Removal of Hypothesis-only Bias in Natural Language Inference. - Yonatan Belinkov; Adam Poliak; Stuart M. Shieber; Benjamin Van Durme; Alexander M. Rush (*SEM@NAACL-HLT, 2019)

Findings of the First Shared Task on Machine Translation Robustness. - Xian Li 003; Paul Michel; Antonios Anastasopoulos; Yonatan Belinkov; Nadir Durrani; Orhan Firat; Philipp Koehn; Graham Neubig; Juan Miguel Pino; Hassan Sajjad 001 (WMT (2), 2019)

Character-based Surprisal as a Model of Human Reading in the Presence of Errors. - Michael Hahn 001; Frank Keller; Yonatan Bisk; Yonatan Belinkov (CoRR, 2019)

LSTM Networks Can Perform Dynamic Counting. - Mirac Suzgun; Sebastian Gehrmann; Yonatan Belinkov; Stuart M. Shieber (CoRR, 2019)

Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects. - Gabriel Grand; Yonatan Belinkov (CoRR, 2019)

Memory-Augmented Recurrent Neural Networks Can Learn Generalized Dyck Languages. - Mirac Suzgun; Sebastian Gehrmann; Yonatan Belinkov; Stuart M. Shieber (CoRR, 2019)

Language processing and learning models for community question answering in Arabic. - Salvatore Romeo; Giovanni Da San Martino; Yonatan Belinkov; Alberto Barrón-Cedeño; Mohamed Eldesouki; Kareem Darwish; Hamdy Mubarak; James R. Glass; Alessandro Moschitti (Inf. Process. Manag., 2019)

Studying the history of the Arabic language: language technology and a large-scale historical corpus. - Yonatan Belinkov; Alexander Magidow; Alberto Barrón-Cedeño; Avi Shmidman; Maxim Romanov (Lang. Resour. Evaluation, 2019)

Analysis Methods in Neural Language Processing: A Survey. - Yonatan Belinkov; James R. Glass (Trans. Assoc. Comput. Linguistics, 2019)

The Sensitivity of Language Models and Humans to Winograd Schema Perturbations. - Mostafa Abdou; Vinit Ravishankar; Maria Barrett; Yonatan Belinkov; Desmond Elliott; Anders Søgaard (ACL, 2020)

Interpretability and Analysis in Neural NLP. - Yonatan Belinkov; Sebastian Gehrmann; Ellie Pavlick (ACL (tutorial), 2020)

End-to-End Bias Mitigation by Modelling Biases in Corpora. - Rabeeh Karimi Mahabadi; Yonatan Belinkov; James Henderson 001 (ACL, 2020)

Similarity Analysis of Contextual Word Representation Models. - John M. Wu; Yonatan Belinkov; Hassan Sajjad 001; Nadir Durrani; Fahim Dalvi; James R. Glass (ACL, 2020)

Analyzing Redundancy in Pretrained Transformer Models. - Fahim Dalvi; Hassan Sajjad 001; Nadir Durrani; Yonatan Belinkov (EMNLP (1), 2020)

Analyzing Individual Neurons in Pre-trained Language Models. - Nadir Durrani; Hassan Sajjad 001; Fahim Dalvi; Yonatan Belinkov (EMNLP (1), 2020)

A Constructive Prediction of the Generalization Error Across Scales. - Jonathan S. Rosenfeld; Amir Rosenfeld; Yonatan Belinkov; Nir Shavit (ICLR, 2020)

Investigating Gender Bias in Language Models Using Causal Mediation Analysis. - Jesse Vig; Sebastian Gehrmann; Yonatan Belinkov; Sharon Qian; Daniel Nevo; Yaron Singer; Stuart M. Shieber (NeurIPS, 2020)

Findings of the WMT 2020 Shared Task on Machine Translation Robustness. - Lucia Specia; Zhenhao Li 003; Juan Miguel Pino; Vishrav Chaudhary; Francisco Guzmán; Graham Neubig; Nadir Durrani; Yonatan Belinkov; Philipp Koehn; Hassan Sajjad 001; Paul Michel; Xian Li 003 (WMT@EMNLP, 2020)

On the Linguistic Representational Power of Neural Machine Translation Models. - Yonatan Belinkov; Nadir Durrani; Fahim Dalvi; Hassan Sajjad 001; James R. Glass (Comput. Linguistics, 2020)

Exploiting Redundancy in Pre-trained Language Models for Efficient Transfer Learning. - Fahim Dalvi; Hassan Sajjad 001; Nadir Durrani; Yonatan Belinkov (CoRR, 2020)

Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias. - Jesse Vig; Sebastian Gehrmann; Yonatan Belinkov; Sharon Qian; Daniel Nevo; Yaron Singer; Stuart M. Shieber (CoRR, 2020)

Probing Neural Dialog Models for Conversational Understanding. - Abdelrhman Saleh; Tovly Deutsch; Stephen Casper; Yonatan Belinkov; Stuart M. Shieber (CoRR, 2020)

Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models. - Matthew Finlayson; Aaron Mueller; Sebastian Gehrmann; Stuart M. Shieber; Tal Linzen; Yonatan Belinkov (ACL/IJCNLP (1), 2021)

Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance? - Abhilasha Ravichander; Yonatan Belinkov; Eduard H. Hovy (EACL, 2021)

Debiasing Methods in Natural Language Understanding Make Bias More Accessible. - Michael Mendelson; Yonatan Belinkov (EMNLP (1), 2021)

Similarity Analysis of Self-Supervised Speech Representations. - Yu-An Chung; Yonatan Belinkov; James R. Glass (ICASSP, 2021)

Variational Information Bottleneck for Effective Low-Resource Fine-Tuning. - Rabeeh Karimi Mahabadi; Yonatan Belinkov; James Henderson 001 (ICLR, 2021)

Learning from others' mistakes: Avoiding dataset biases without modeling them. - Victor Sanh; Thomas Wolf 008; Yonatan Belinkov; Alexander M. Rush (ICLR, 2021)

IRM - when it works and when it doesn't: A test case of natural language inference. - Yana Dranker; He He 001; Yonatan Belinkov (NeurIPS, 2021)

Probing Classifiers: Promises, Shortcomings, and Alternatives. - Yonatan Belinkov (CoRR, 2021)

Natural Language Inference with a Human Touch: Using Human Explanations to Guide Model Attention. - Joe Stacey; Yonatan Belinkov; Marek Rei (CoRR, 2021)

Supervising Model Attention with Human Explanations for Robust Natural Language Inference. - Joe Stacey; Yonatan Belinkov; Marek Rei (AAAI, 2022)

A Multilingual Perspective Towards the Evaluation of Attribution Methods in Natural Language Inference. - Kerem Zaman; Yonatan Belinkov (EMNLP, 2022)

On the Pitfalls of Analyzing Individual Neurons in Language Models. - Omer Antverg; Yonatan Belinkov (ICLR, 2022)

How Gender Debiasing Affects Internal Model Representations, and Why It Matters. - Hadas Orgad; Seraphina Goldfarb-Tarrant; Yonatan Belinkov (NAACL-HLT, 2022)

Measures of Information Reflect Memorization Patterns. - Rachit Bansal; Danish Pruthi; Yonatan Belinkov (NeurIPS, 2022)

Locating and Editing Factual Associations in GPT. - Kevin Meng; David Bau; Alex Andonian; Yonatan Belinkov (NeurIPS, 2022)

A Generative Approach for Mitigating Structural Biases in Natural Language Inference. - Dimion Asael; Zachary M. Ziegler; Yonatan Belinkov (*SEM@NAACL-HLT, 2022)

Probing Classifiers: Promises, Shortcomings, and Advances. - Yonatan Belinkov (Comput. Linguistics, 2022)

Locating and Editing Factual Knowledge in GPT. - Kevin Meng; David Bau; Alex Andonian; Yonatan Belinkov (CoRR, 2022)

MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning. - Ehud Karpas; Omri Abend; Yonatan Belinkov; Barak Lenz; Opher Lieber; Nir Ratner; Yoav Shoham; Hofit Bata; Yoav Levine; Kevin Leyton-Brown; Dor Muhlgay; Noam Rozen; et al. (CoRR, 2022)

IDANI: Inference-time Domain Adaptation via Neuron-level Interventions. - Omer Antverg; Eyal Ben-David; Yonatan Belinkov (CoRR, 2022)

Measuring Causal Effects of Data Statistics on Language Model's 'Factual' Predictions. - Yanai Elazar; Nora Kassner; Shauli Ravfogel; Amir Feder; Abhilasha Ravichander; Marius Mosbach; Yonatan Belinkov; Hinrich Schütze; Yoav Goldberg (CoRR, 2022)

Choose Your Lenses: Flaws in Gender Bias Evaluation. - Hadas Orgad; Yonatan Belinkov (CoRR, 2022)

Debiasing NLP Models Without Demographic Information. - Hadas Orgad; Yonatan Belinkov (CoRR, 2022)

Parallel Context Windows Improve In-Context Learning of Large Language Models. - Nir Ratner; Yoav Levine; Yonatan Belinkov; Ori Ram; Omri Abend; Ehud Karpas; Amnon Shashua; Kevin Leyton-Brown; Yoav Shoham (CoRR, 2022)

Emergent Quantized Communication. - Boaz Carmeli; Ron Meir; Yonatan Belinkov (AAAI, 2023)

Shielded Representations: Protecting Sensitive Attributes Through Iterative Gradient-Based Projection. - Shadi Iskander; Kira Radinsky; Yonatan Belinkov (ACL (Findings), 2023)

BLIND: Bias Removal With No Demographics. - Hadas Orgad; Yonatan Belinkov (ACL (1), 2023)

What Are You Token About? Dense Retrieval as Distributions Over the Vocabulary. - Ori Ram; Liat Bezalel; Adi Zicher; Yonatan Belinkov; Jonathan Berant; Amir Globerson (ACL (1), 2023)

Parallel Context Windows for Large Language Models. - Nir Ratner; Yoav Levine; Yonatan Belinkov; Ori Ram; Inbal Magar; Omri Abend; Ehud Karpas; Amnon Shashua; Kevin Leyton-Brown; Yoav Shoham (ACL (1), 2023)

FigureOut - Automatic Detection of Metaphors in Hebrew Across the Eras. - Ophir Münz-Manor; Michael Toker; Oren Mishali; Benny Kimelfeld; Yonatan Belinkov; Adir Cohen (DH, 2023)

When Language Models Fall in Love: Animacy Processing in Transformer Language Models. - Michael Hanna 001; Yonatan Belinkov; Sandro Pezzelle (EMNLP, 2023)

VISIT: Visualizing and Interpreting the Semantic Information Flow of Transformers. - Shahar Katz; Yonatan Belinkov (EMNLP (Findings), 2023)

A Mechanistic Interpretation of Arithmetic Reasoning in Language Models using Causal Mediation Analysis. - Alessandro Stolfo; Yonatan Belinkov; Mrinmaya Sachan (EMNLP, 2023)

Editing Implicit Assumptions in Text-to-Image Diffusion Models. - Hadas Orgad; Bahjat Kawar; Yonatan Belinkov (ICCV, 2023)

Multiple sequence alignment as a sequence-to-sequence learning problem. - Edo Dotan; Yonatan Belinkov; Oren Avram; Elya Wygoda; Noa Ecker; Michael Alburquerque; Omri Keren; Gil Loewenthal; Tal Pupko (ICLR, 2023)

Mass-Editing Memory in a Transformer. - Kevin Meng; Arnab Sen Sharma; Alex J. Andonian; Yonatan Belinkov; David Bau (ICLR, 2023)

ContraSim - A Similarity Measure Based on Contrastive Learning. - Adir Rahamim; Yonatan Belinkov (CoRR, 2023)

Interpreting Transformer's Attention Dynamic Memory and Visualizing the Semantic Information Flow of GPT. - Shahar Katz; Yonatan Belinkov (CoRR, 2023)

Understanding Arithmetic Reasoning in Language Models using Causal Mediation Analysis. - Alessandro Stolfo; Yonatan Belinkov; Mrinmaya Sachan (CoRR, 2023)

Instructed to Bias: Instruction-Tuned Language Models Exhibit Emergent Cognitive Bias. - Itay Itzhak; Gabriel Stanovsky; Nir Rosenfeld; Yonatan Belinkov (CoRR, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Accelerating the Global Aggregation of Local Explanations. - Alon Mor; Yonatan Belinkov; Benny Kimelfeld (AAAI, 2024)

Concept-Best-Matching: Evaluating Compositionality In Emergent Communication. - Boaz Carmeli; Yonatan Belinkov; Ron Meir (ACL (Findings), 2024)

Diffusion Lens: Interpreting Text Encoders in Text-to-Image Pipelines. - Michael Toker; Hadas Orgad; Mor Ventura; Dana Arad; Yonatan Belinkov (ACL (1), 2024)

Generating Benchmarks for Factuality Evaluation of Language Models. - Dor Muhlgay; Ori Ram; Inbal Magar; Yoav Levine; Nir Ratner; Yonatan Belinkov; Omri Abend; Kevin Leyton-Brown; Amnon Shashua; Yoav Shoham (EACL (1), 2024)

A Dataset for Metaphor Detection in Early Medieval Hebrew Poetry. - Michael Toker; Oren Mishali; Ophir Münz-Manor; Benny Kimelfeld; Yonatan Belinkov (EACL (2), 2024)

Backward Lens: Projecting Language Model Gradients into the Vocabulary Space. - Shahar Katz; Yonatan Belinkov; Mor Geva; Lior Wolf (EMNLP, 2024)

Fast Forwarding Low-Rank Training. - Adir Rahamim; Naomi Saphra; Sara Kangaslahti; Yonatan Belinkov (EMNLP, 2024)

Linearity of Relation Decoding in Transformer Language Models. - Evan Hernandez; Arnab Sen Sharma; Tal Haklay; Kevin Meng; Martin Wattenberg; Jacob Andreas; Yonatan Belinkov; David Bau (ICLR, 2024)

Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking. - Nikhil Prakash; Tamar Rott Shaham; Tal Haklay; Yonatan Belinkov; David Bau (ICLR, 2024)

ReFACT: Updating Text-to-Image Models by Editing the Text Encoder. - Dana Arad; Hadas Orgad; Yonatan Belinkov (NAACL-HLT, 2024)

Leveraging Prototypical Representations for Mitigating Social Bias without Demographic Information. - Shadi Iskander; Kira Radinsky; Yonatan Belinkov (NAACL (Short Papers), 2024)

ContraSim - Analyzing Neural Representations Based on Contrastive Learning. - Adir Rahamim; Yonatan Belinkov (NAACL-HLT, 2024)

Confidence Regulation Neurons in Language Models. - Alessandro Stolfo; Ben Wu 001; Wes Gurnee; Yonatan Belinkov; Xingyi Song; Mrinmaya Sachan; Neel Nanda (NeurIPS, 2024)

Semantics and Spatiality of Emergent Communication. - Rotem Ben Zion; Boaz Carmeli; Orr Paradise; Yonatan Belinkov (NeurIPS, 2024)

Unified Concept Editing in Diffusion Models. - Rohit Gandikota; Hadas Orgad; Yonatan Belinkov; Joanna Materzynska; David Bau (WACV, 2024)

Effect of tokenization on transformers for biological sequences. - Edo Dotan; Gal Jaschek; Tal Pupko; Yonatan Belinkov (Bioinform., 2024)

Have Faith in Faithfulness: Going Beyond Circuit Overlap When Finding Model Mechanisms. - Michael Hanna 001; Sandro Pezzelle; Yonatan Belinkov (CoRR, 2024)

Jamba: A Hybrid Transformer-Mamba Language Model. - Opher Lieber; Barak Lenz; Hofit Bata; Gal Cohen; Jhonathan Osin; Itay Dalmedigos; Erez Safahi; Shaked Meirom; Yonatan Belinkov; Shai Shalev-Shwartz; Omri Abend; Raz Alon; et al. (CoRR, 2024)

Constructing Benchmarks and Interventions for Combating Hallucinations in LLMs. - Adi Simhi; Jonathan Herzig; Idan Szpektor; Yonatan Belinkov (CoRR, 2024)

DEPTH: Discourse Education through Pre-Training Hierarchically. - Zachary Bamberger; Ofek Glick; Chaim Baskin; Yonatan Belinkov (CoRR, 2024)

Answer, Assemble, Ace: Understanding How Transformers Answer Multiple Choice Questions. - Sarah Wiegreffe; Oyvind Tafjord; Yonatan Belinkov; Hannaneh Hajishirzi; Ashish Sabharwal (CoRR, 2024)

The Quest for the Right Mediator: A History, Survey, and Theoretical Grounding of Causal Interpretability. - Aaron Mueller; Jannik Brinkmann; Millicent L. Li; Samuel Marks; Koyena Pal; Nikhil Prakash; Can Rager; Aruna Sankaranarayanan; Arnab Sen Sharma; Jiuding Sun; Eric Todd; David Bau; et al. (CoRR, 2024)

Jamba-1.5: Hybrid Transformer-Mamba Models at Scale. - Barak Lenz; Alan Arazi; Amir Bergman; Avshalom Manevich; Barak Peleg; Ben Aviram; Chen Almagor; Clara Fridman; Dan Padnos; Daniel Gissin; Daniel Jannai; Dor Muhlgay; et al. (CoRR, 2024)

Context-aware Prompt Tuning: Advancing In-Context Learning with Adversarial Methods. - Tsachi Blau; Moshe Kimhi; Yonatan Belinkov; Alexander M. Bronstein; Chaim Baskin (CoRR, 2024)

Distinguishing Ignorance from Error in LLM Hallucinations. - Adi Simhi; Jonathan Herzig; Idan Szpektor; Yonatan Belinkov (CoRR, 2024)

Growing a Tail: Increasing Output Diversity in Large Language Models. - Michal Shur-Ofry; Bar Horowitz-Amsalem; Adir Rahamim; Yonatan Belinkov (CoRR, 2024)

Unsupervised Translation of Emergent Communication. - Ido Levy; Orr Paradise; Boaz Carmeli; Ron Meir; Shafi Goldwasser; Yonatan Belinkov (AAAI, 2025)

REVS: Unlearning Sensitive Information in Language Models via Rank Editing in the Vocabulary Space. - Tomer Ashuach; Martin Tutek; Yonatan Belinkov (ACL (Findings), 2025)

Position-aware Automatic Circuit Discovery. - Tal Haklay; Hadas Orgad; David Bau; Aaron Mueller; Yonatan Belinkov (ACL (1), 2025)

CtD: Composition through Decomposition in Emergent Communication. - Boaz Carmeli; Ron Meir; Yonatan Belinkov (ICLR, 2025)

Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models. - Samuel Marks; Can Rager; Eric J. Michaud; Yonatan Belinkov; David Bau; Aaron Mueller (ICLR, 2025)

Arithmetic Without Algorithms: Language Models Solve Math with a Bag of Heuristics. - Yaniv Nikankin; Anja Reusch; Aaron Mueller; Yonatan Belinkov (ICLR, 2025)

LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations. - Hadas Orgad; Michael Toker; Zorik Gekhman; Roi Reichart; Idan Szpektor; Hadas Kotek; Yonatan Belinkov (ICLR, 2025)

Answer, Assemble, Ace: Understanding How LMs Answer Multiple Choice Questions. - Sarah Wiegreffe; Oyvind Tafjord; Yonatan Belinkov; Hannaneh Hajishirzi; Ashish Sabharwal (ICLR, 2025)

Padding Tone: A Mechanistic Analysis of Padding Tokens in T2I Models. - Michael Toker; Ido Galil; Hadas Orgad; Rinon Gal; Yoad Tewel; Gal Chechik; Yonatan Belinkov (NAACL (Long Papers), 2025)

Reverse-Engineering the Retrieval Process in GenIR Models. - Anja Reusch; Yonatan Belinkov (SIGIR, 2025)

Back Attention: Understanding and Enhancing Multi-Hop Reasoning in Large Language Models. - Zeping Yu; Yonatan Belinkov; Sophia Ananiadou (CoRR, 2025)

Trust Me, I'm Wrong: High-Certainty Hallucinations in LLMs. - Adi Simhi; Itay Itzhak; Fazl Barez; Gabriel Stanovsky; Yonatan Belinkov (CoRR, 2025)

Measuring Faithfulness of Chains of Thought by Unlearning Reasoning Steps. - Martin Tutek; Fateme Hashemi Chaleshtori; Ana Marasovic; Yonatan Belinkov (CoRR, 2025)

Are formal and functional linguistic mechanisms dissociated in language models? - Michael Hanna 001; Yonatan Belinkov; Sandro Pezzelle (CoRR, 2025)

Inside-Out: Hidden Factual Knowledge in LLMs. - Zorik Gekhman; Eyal Ben-David; Hadas Orgad; Eran Ofek; Yonatan Belinkov; Idan Szpektor; Jonathan Herzig; Roi Reichart (CoRR, 2025)

How Generative IR Retrieves Documents Mechanistically. - Anja Reusch; Yonatan Belinkov (CoRR, 2025)

Follow the Flow: On Information Flow Across Textual Tokens in Text-to-Image Models. - Guy Kaplan; Michael Toker; Yuval Reif; Yonatan Belinkov; Roy Schwartz 001 (CoRR, 2025)

MIB: A Mechanistic Interpretability Benchmark. - Aaron Mueller; Atticus Geiger; Sarah Wiegreffe; Dana Arad; Iván Arcuschin; Adam Belfki; Yik Siu Chan; Jaden Fiotto-Kaufman; Tal Haklay; Michael Hanna 001; Jing Huang; Rohan Gupta; et al. (CoRR, 2025)

Language Models use Lookbacks to Track Beliefs. - Nikhil Prakash; Natalie Shapira; Arnab Sen Sharma; Christoph Riedl; Yonatan Belinkov; Tamar Rott Shaham; David Bau; Atticus Geiger (CoRR, 2025)

SAEs Are Good for Steering - If You Select the Right Features. - Dana Arad; Aaron Mueller; Yonatan Belinkov (CoRR, 2025)

Same Task, Different Circuits: Disentangling Modality-Specific Mechanisms in VLMs. - Yaniv Nikankin; Dana Arad; Yossi Gandelsman; Yonatan Belinkov (CoRR, 2025)

Planted in Pretraining, Swayed by Finetuning: A Case Study on the Origins of Cognitive Biases in LLMs. - Itay Itzhak; Yonatan Belinkov; Gabriel Stanovsky (CoRR, 2025)

CRISP: Persistent Concept Unlearning via Sparse Autoencoders. - Tomer Ashuach; Dana Arad; Aaron Mueller; Martin Tutek; Yonatan Belinkov (CoRR, 2025)