| 2026 | ACL | Controlling What You Share: Assessing Language Model Adherence to Privacy Preferences. | Guillem Ramrez, Alexandra Birch, Ivan Titov |
| 2026 | EACL | Mitigating Copy Bias in In-Context Learning through Neuron Pruning. | Ameen Ali, Lior Wolf, Ivan Titov |
| 2026 | EACL | Analyzing LLM Instruction Optimization for Tabular Fact Verification. | Xiaotang Du, Giwon Hong, Wai-Chung Kwan, Rohit Saxena, Ivan Titov, Pasquale Minervini, Emily Allaway |
| 2026 | EACL | Finding Culture-Sensitive Neurons in Vision-Language Models. | Xiutian Zhao, Rochelle Choenni, Rohit Saxena, Ivan Titov |
| 2025 | ACL | Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert Models. | Zihan Qiu, Zeyu Huang, Bo Zheng, Kaiyue Wen, Zekun Wang, Rui Men, Ivan Titov, Dayiheng Liu, Jingren Zhou, Junyang Lin |
| 2025 | CiE | Variants of Solovay Reducibility. | Ivan Titov |
| 2025 | COLING | Explanation Regularisation through the Lens of Attributions. | Pedro Ferreira, Ivan Titov, Wilker Aziz |
| 2025 | EMNLP | M-Wanda: Improving One-Shot Pruning for Multilingual LLMs. | Rochelle Choenni, Ivan Titov |
| 2025 | EMNLP | Enhancing RLHF with Human Gaze Modeling. | Karim Galliamov, Ivan Titov, Ilya Pershin |
| 2025 | ICLR | Language Agents Meet Causality - Bridging LLMs and Causal World Models. | John Gkountouras, Matthias Lindemann, Phillip Lippe, Efstratios Gavves, Ivan Titov |
| 2025 | ICLR | Post-hoc Reward Calibration: A Case Study on Length Bias. | Zeyu Huang, Zihan Qiu, Zili Wang, Edoardo M. Ponti, Ivan Titov |
| 2025 | ICLR | What's New in My Data? Novelty Exploration via Contrastive Generation. | Masaru Isonuma, Ivan Titov |
| 2025 | ICLR | Layerwise Recurrent Router for Mixture-of-Experts. | Zihan Qiu, Zeyu Huang, Shuang Cheng, Yizhi Zhou, Zili Wang, Ivan Titov, Jie Fu |
| 2025 | ICML | Joint Localization and Activation Editing for Low-Resource Fine-Tuning. | Wen Lai, Alexander Fraser, Ivan Titov |
| 2025 | IJCNLP | Enhancing Long Document Long Form Summarisation with Self-Planning. | Xiaotang Du, Rohit Saxena, Laura Perez-Beltrachini, Pasquale Minervini, Ivan Titov |
| 2025 | MFCS | Relative Randomness and Continuous Translation Functions. | Ivan Titov |
| 2024 | ACL | Generalisation First, Memorisation Second? Memorisation Localisation for Natural Language Classification Tasks. | Verna Dankers, Ivan Titov |
| 2024 | ACL | Unlearning Traces the Influential Training Data of Language Models. | Masaru Isonuma, Ivan Titov |
| 2024 | ACL | SIP: Injecting a Structural Inductive Bias into a Seq2Seq Model by Simulation. | Matthias Lindemann, Alexander Koller, Ivan Titov |
| 2024 | ACL | Cache & Distil: Optimising API Calls to Large Language Models. | Guillem Ramrez, Matthias Lindemann, Alexandra Birch, Ivan Titov |
| 2024 | EMNLP | Strengthening Structural Inductive Biases by Pre-training to Perform Syntactic Transformations. | Matthias Lindemann, Alexander Koller, Ivan Titov |
| 2024 | ICML | Autoencoding Conditional Neural Processes for Representation Learning. | Victor Prokhorov, Ivan Titov, N. Siddharth |
| 2023 | ACL | Compositional Generalization without Trees using Multiset Tagging and Latent Permutations. | Matthias Lindemann, Alexander Koller, Ivan Titov |
| 2023 | EACL | Compositional Generalisation with Structured Reordering and Fertility Layers. | Matthias Lindemann, Alexander Koller, Ivan Titov |
| 2023 | EMNLP | Cross-Modal Conceptualization in Bottleneck Models. | Danis Alukaev, Semen Kiselev, Ilya Pershin, Bulat Ibragimov, Vladimir Ivanov, Alexey Kornaev, Ivan Titov |
| 2023 | EMNLP | Memorisation Cartography: Mapping out the Memorisation-Generalisation Continuum in Neural Machine Translation. | Verna Dankers, Ivan Titov, Dieuwke Hupkes |
| 2023 | EMNLP | Subspace Chronicles: How Linguistic Information Emerges, Shifts and Interacts during Language Model Training. | Max Mller-Eberstein, Rob van der Goot, Barbara Plank, Ivan Titov |
| 2023 | EMNLP | Compositional Generalization for Data-to-Text Generation. | Xinnuo Xu, Ivan Titov, Mirella Lapata |
| 2023 | EMNLP | On the Transferability of Visually Grounded PCFGs. | Yanpeng Zhao, Ivan Titov |
| 2022 | ACL | Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation. | Verna Dankers, Christopher G. Lucas, Ivan Titov |
| 2022 | EMNLP | Recursive Neural Networks with Bottlenecks Diagnose (Non-)Compositionality. | Verna Dankers, Ivan Titov |
| 2022 | EMNLP | Hierarchical Phrase-Based Sequence-to-Sequence Learning. | Bailin Wang, Ivan Titov, Jacob Andreas, Yoon Kim |
| 2021 | ACL | Exploring Unsupervised Pretraining Objectives for Machine Translation. | Christos Baziotis, Ivan Titov, Alexandra Birch, Barry Haddow |
| 2021 | ACL | Meta-Learning to Compositionally Generalize. | Henry Conklin, Bailin Wang, Kenny Smith, Ivan Titov |
| 2021 | ACL | Analyzing the Source and Target Contributions to Predictions in Neural Machine Translation. | Elena Voita, Rico Sennrich, Ivan Titov |
| 2021 | ACL | A Closer Look into the Robustness of Neural Dependency Parsers Using Better Adversarial Examples. | Yuxuan Wang, Wanxiang Che, Ivan Titov, Shay B. Cohen, Zhilin Lei, Ting Liu |
| 2021 | ACL | Beyond Sentence-Level End-to-End Speech Translation: Context Helps. | Biao Zhang, Ivan Titov, Barry Haddow, Rico Sennrich |
| 2021 | ACL | On Sparsifying Encoder Outputs in Sequence-to-Sequence Models. | Biao Zhang, Ivan Titov, Rico Sennrich |
| 2021 | EMNLP | Learning Opinion Summarizers by Selecting Informative Reviews. | Arthur Brazinskas, Mirella Lapata, Ivan Titov |
| 2021 | EMNLP | Editing Factual Knowledge in Language Models. | Nicola De Cao, Wilker Aziz, Ivan Titov |
| 2021 | EMNLP | Highly Parallel Autoregressive Entity Linking with Discriminative Correction. | Nicola De Cao, Wilker Aziz, Ivan Titov |
| 2021 | EMNLP | A Differentiable Relaxation of Graph Segmentation and Alignment for AMR Parsing. | Chunchuan Lyu, Shay B. Cohen, Ivan Titov |
| 2021 | EMNLP | Language Modeling, Lexical Translation, Reordering: The Training Process of NMT through the Lens of Classical SMT. | Elena Voita, Rico Sennrich, Ivan Titov |
| 2021 | EMNLP | Sparse Attention with Linear Units. | Biao Zhang, Ivan Titov, Rico Sennrich |
| 2021 | ICLR | Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking. | Michael Sejr Schlichtkrull, Nicola De Cao, Ivan Titov |
| 2021 | NAACL | Meta-Learning for Domain Generalization in Semantic Parsing. | Bailin Wang, Mirella Lapata, Ivan Titov |
| 2021 | NAACL | Learning from Executions for Semantic Parsing. | Bailin Wang, Mirella Lapata, Ivan Titov |
| 2020 | ACL | Unsupervised Opinion Summarization as Copycat-Review Generation. | Arthur Brazinskas, Mirella Lapata, Ivan Titov |
| 2020 | ACL | Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation. | Biao Zhang, Philip Williams, Ivan Titov, Rico Sennrich |
| 2020 | CSR | Speedable Left-c.e. Numbers. | Wolfgang Merkle, Ivan Titov |
| 2020 | EMNLP | Few-Shot Learning for Opinion Summarization. | Arthur Brazinskas, Mirella Lapata, Ivan Titov |
| 2020 | EMNLP | How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking. | Nicola De Cao, Michael Sejr Schlichtkrull, Wilker Aziz, Ivan Titov |
| 2020 | EMNLP | Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial Attacks. | Denis Emelin, Ivan Titov, Rico Sennrich |
| 2020 | EMNLP | Graph Convolutions over Constituent Trees for Syntax-Aware Semantic Role Labeling. | Diego Marcheggiani, Ivan Titov |
| 2020 | EMNLP | Information-Theoretic Probing with Minimum Description Length. | Elena Voita, Ivan Titov |
| 2020 | EMNLP | Adaptive Feature Selection for End-to-End Speech Translation. | Biao Zhang, Ivan Titov, Barry Haddow, Rico Sennrich |
| 2020 | EMNLP | Visually Grounded Compound PCFGs. | Yanpeng Zhao, Ivan Titov |
| 2019 | ACL | Interpretable Neural Predictions with Differentiable Binary Variables. | Jasmijn Bastings, Wilker Aziz, Ivan Titov |
| 2019 | ACL | Learning Latent Trees with Stochastic Perturbations and Differentiable Dynamic Programming. | Caio Corro, Ivan Titov |
| 2019 | ACL | Boosting Entity Linking Performance by Leveraging Unlabeled Documents. | Phong Le, Ivan Titov |
| 2019 | ACL | Distant Learning for Entity Linking with Automatic Noise Detection. | Phong Le, Ivan Titov |
| 2019 | ACL | When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion. | Elena Voita, Rico Sennrich, Ivan Titov |
| 2019 | ACL | Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned. | Elena Voita, David Talbot, Fedor Moiseev, Rico Sennrich, Ivan Titov |
| 2019 | EMNLP | Capturing Argument Interaction in Semantic Role Labeling with Capsule Networks. | Xinchi Chen, Chunchuan Lyu, Ivan Titov |
| 2019 | EMNLP | Semantic Role Labeling with Iterative Structure Refinement. | Chunchuan Lyu, Shay B. Cohen, Ivan Titov |
| 2019 | EMNLP | Context-Aware Monolingual Repair for Neural Machine Translation. | Elena Voita, Rico Sennrich, Ivan Titov |
| 2019 | EMNLP | The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives. | Elena Voita, Rico Sennrich, Ivan Titov |
| 2019 | EMNLP | Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract Programs. | Bailin Wang, Ivan Titov, Mirella Lapata |
| 2019 | EMNLP | Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention. | Biao Zhang, Ivan Titov, Rico Sennrich |
| 2019 | ICLR | Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder. | Caio Corro, Ivan Titov |
| 2019 | NAACL | Question Answering by Reasoning Across Documents with Graph Convolutional Networks. | Nicola De Cao, Wilker Aziz, Ivan Titov |
| 2019 | NAACL | Single Document Summarization as Tree Induction. | Yang Liu, Ivan Titov, Mirella Lapata |
| 2019 | UAI | Block Neural Autoregressive Flow. | Nicola De Cao, Wilker Aziz, Ivan Titov |
| 2018 | ACL | AMR Parsing as Graph Prediction with Latent Alignment. | Chunchuan Lyu, Ivan Titov |
| 2018 | ACL | Improving Entity Linking by Modeling Latent Relations between Mentions. | Phong Le, Ivan Titov |
| 2018 | ACL | Context-Aware Neural Machine Translation Learns Anaphora Resolution. | Elena Voita, Pavel Serdyukov, Rico Sennrich, Ivan Titov |
| 2018 | COLING | Embedding Words as Distributions with a Bayesian Skip-gram Model. | Arthur Brazinskas, Serhii Havrylov, Ivan Titov |
| 2018 | NAACL | Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks. | Diego Marcheggiani, Jasmijn Bastings, Ivan Titov |
| 2017 | CoNLL | Optimizing Differentiable Relaxations of Coreference Evaluation Metrics. | Phong Le, Ivan Titov |
| 2017 | CoNLL | A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling. | Diego Marcheggiani, Anton Frolov, Ivan Titov |
| 2017 | EMNLP | Graph Convolutional Encoders for Syntax-aware Neural Machine Translation. | Jasmijn Bastings, Ivan Titov, Wilker Aziz, Diego Marcheggiani, Khalil Sima'an |
| 2017 | EMNLP | Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling. | Diego Marcheggiani, Ivan Titov |
| 2017 | ICLR | Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols. | Serhii Havrylov, Ivan Titov |
| 2016 | NAACL | Bilingual Learning of Multi-sense Embeddings with Discrete Autoencoders. | Simon Suster, Ivan Titov, Gertjan van Noord |
| 2015 | NAACL | Unsupervised Induction of Semantic Roles within a Reconstruction-Error Minimization Framework. | Ivan Titov, Ehsan Khoddam |
| 2014 | ACL | Cross-lingual Model Transfer Using Feature Representation Projection. | Mikhail Kozhevnikov, Ivan Titov |
| 2014 | CoNLL | Inducing Neural Models of Script Knowledge. | Ashutosh Modi, Ivan Titov |
| 2014 | EACL | A Hierarchical Bayesian Model for Unsupervised Induction of Script Knowledge. | Lea Frermann, Ivan Titov, Manfred Pinkal |
| 2013 | ACL | Cross-lingual Transfer of Semantic Role Labeling Models. | Mikhail Kozhevnikov, Ivan Titov |
| 2013 | ACL | A Bayesian Model for Joint Unsupervised Induction of Sentiment, Aspect and Discourse Representations. | Angeliki Lazaridou, Ivan Titov, Caroline Sporleder |
| 2013 | EMNLP | Predicting the Resolution of Referring Expressions from User Behavior. | Nikos Engonopoulos, Martin Villalba, Ivan Titov, Alexander Koller |
| 2013 | ICCV | Translating Video Content to Natural Language Descriptions. | Marcus Rohrbach, Wei Qiu, Ivan Titov, Stefan Thater, Manfred Pinkal, Bernt Schiele |
| 2013 | NAACL | Semantic Role Labeling. | Martha Palmer, Ivan Titov, Shumin Wu |
| 2012 | ACL | Crosslingual Induction of Semantic Roles. | Ivan Titov, Alexandre Klementiev |
| 2012 | COLING | Inducing Crosslingual Distributed Representations of Words. | Alexandre Klementiev, Ivan Titov, Binod Bhattarai |
| 2012 | COLING | Semi-Supervised Semantic Role Labeling: Approaching from an Unsupervised Perspective. | Ivan Titov, Alexandre Klementiev |
| 2012 | EACL | A Bayesian Approach to Unsupervised Semantic Role Induction. | Ivan Titov, Alexandre Klementiev |
| 2011 | ACL | Domain Adaptation by Constraining Inter-Domain Variability of Latent Feature Representation. | Ivan Titov |
| 2011 | ACL | A Bayesian Model for Unsupervised Semantic Parsing. | Ivan Titov, Alexandre Klementiev |
| 2010 | ACL | Unsupervised Discourse Segmentation of Documents with Inherently Parallel Structure. | Minwoo Jeong, Ivan Titov |
| 2010 | ACL | Bootstrapping Semantic Analyzers from Non-Contradictory Texts. | Ivan Titov, Mikhail Kozhevnikov |
| 2010 | CIKM | Multi-document topic segmentation. | Minwoo Jeong, Ivan Titov |
| 2009 | CoNLL | A Latent Variable Model of Synchronous Syntactic-Semantic Parsing for Multiple Languages. | Andrea Gesmundo, James Henderson, Paola Merlo, Ivan Titov |
| 2009 | IJCAI | Unsupervised Rank Aggregation with Domain-Specific Expertise. | Alexandre Klementiev, Dan Roth, Kevin Small, Ivan Titov |
| 2009 | IJCAI | Online Graph Planarisation for Synchronous Parsing of Semantic and Syntactic Dependencies. | Ivan Titov, James Henderson, Paola Merlo, Gabriele Musillo |
| 2008 | ACL | A Joint Model of Text and Aspect Ratings for Sentiment Summarization. | Ivan Titov, Ryan T. McDonald |
| 2008 | CoNLL | A Latent Variable Model of Synchronous Parsing for Syntactic and Semantic Dependencies. | James Henderson, Paola Merlo, Gabriele Musillo, Ivan Titov |
| 2008 | WWW | Modeling online reviews with multi-grain topic models. | Ivan Titov, Ryan T. McDonald |
| 2007 | ACL | Constituent Parsing with Incremental Sigmoid Belief Networks. | Ivan Titov, James Henderson |
| 2007 | EMNLP | Fast and Robust Multilingual Dependency Parsing with a Generative Latent Variable Model. | Ivan Titov, James Henderson |
| 2007 | ICML | Incremental Bayesian networks for structure prediction. | Ivan Titov, James Henderson |
| 2006 | CoNLL | Porting Statistical Parsers with Data-Defined Kernels. | Ivan Titov, James Henderson |
| 2006 | EMNLP | Loss Minimization in Parse Reranking. | Ivan Titov, James Henderson |
| 2005 | ACL | Data-Defined Kernels for Parse Reranking Derived from Probabilistic Models. | James Henderson, Ivan Titov |
| 2005 | IJCNN | Deriving kernels from MLP probability estimators for large categorization problems. | Ivan Titov, James Henderson |