Data-Defined Kernels for Parse Reranking Derived from Probabilistic Models. - James Henderson 001; Ivan Titov 001 (ACL, 2005)

Deriving kernels from MLP probability estimators for large categorization problems. - Ivan Titov 001; James Henderson 001 (IJCNN, 2005)

Porting Statistical Parsers with Data-Defined Kernels. - Ivan Titov 001; James Henderson 001 (CoNLL, 2006)

Loss Minimization in Parse Reranking. - Ivan Titov 001; James Henderson 001 (EMNLP, 2006)

Constituent Parsing with Incremental Sigmoid Belief Networks. - Ivan Titov 001; James Henderson 001 (ACL, 2007)

Fast and Robust Multilingual Dependency Parsing with a Generative Latent Variable Model. - Ivan Titov 001; James Henderson 001 (EMNLP-CoNLL, 2007)

Incremental Bayesian networks for structure prediction. - Ivan Titov 001; James Henderson 001 (ICML, 2007)

A Latent Variable Model for Generative Dependency Parsing. - Ivan Titov 001; James Henderson 001 (IWPT, 2007)

A Joint Model of Text and Aspect Ratings for Sentiment Summarization. - Ivan Titov 001; Ryan T. McDonald (ACL, 2008)

A Latent Variable Model of Synchronous Parsing for Syntactic and Semantic Dependencies. - James Henderson 001; Paola Merlo; Gabriele Musillo; Ivan Titov 001 (CoNLL, 2008)

Modeling online reviews with multi-grain topic models. - Ivan Titov 001; Ryan T. McDonald (WWW, 2008)

Exploiting non-linear probabilistic models in natural language parsing and reranking. - Ivan Titov 001 (2008)

A Latent Variable Model of Synchronous Syntactic-Semantic Parsing for Multiple Languages. - Andrea Gesmundo; James Henderson 001; Paola Merlo; Ivan Titov 001 (CoNLL Shared Task, 2009)

Unsupervised Rank Aggregation with Domain-Specific Expertise. - Alexandre Klementiev; Dan Roth 001; Kevin Small; Ivan Titov 001 (IJCAI, 2009)

Online Graph Planarisation for Synchronous Parsing of Semantic and Syntactic Dependencies. - Ivan Titov 001; James Henderson 001; Paola Merlo; Gabriele Musillo (IJCAI, 2009)

Sequential Learning of Classifiers for Structured Prediction Problems. - Dan Roth 001; Kevin Small; Ivan Titov 001 (AISTATS, 2009)

A Latent Variable Model for Generative Dependency Parsing. - Ivan Titov 001; James Henderson 001 (Trends in Parsing Technology, 2010)

Incremental Sigmoid Belief Networks for Grammar Learning. - James Henderson 001; Ivan Titov 001 (J. Mach. Learn. Res., 2010)

Unsupervised Aggregation for Classification Problems with Large Numbers of Categories. - Ivan Titov 001; Alexandre Klementiev; Kevin Small; Dan Roth 001 (AISTATS, 2010)

A Bayesian Model for Unsupervised Semantic Parsing. - Ivan Titov 001; Alexandre Klementiev (ACL, 2011)

Crosslingual Induction of Semantic Roles. - Ivan Titov 001; Alexandre Klementiev (ACL (1), 2012)

Inducing Crosslingual Distributed Representations of Words. - Alexandre Klementiev; Ivan Titov 001; Binod Bhattarai (COLING, 2012)

Semi-Supervised Semantic Role Labeling: Approaching from an Unsupervised Perspective. - Ivan Titov 001; Alexandre Klementiev (COLING, 2012)

A Bayesian Approach to Unsupervised Semantic Role Induction. - Ivan Titov 001; Alexandre Klementiev (EACL, 2012)

A Bayesian Model for Joint Unsupervised Induction of Sentiment, Aspect and Discourse Representations. - Angeliki Lazaridou; Ivan Titov 001; Caroline Sporleder (ACL (1), 2013)

Predicting the Resolution of Referring Expressions from User Behavior. - Nikos Engonopoulos; Martin Villalba; Ivan Titov 001; Alexander Koller (EMNLP, 2013)

Translating Video Content to Natural Language Descriptions. - Marcus Rohrbach; Wei Qiu; Ivan Titov 001; Stefan Thater; Manfred Pinkal; Bernt Schiele (ICCV, 2013)

Semantic Role Labeling. - Martha Palmer; Ivan Titov 001; Shumin Wu (HLT-NAACL, 2013)

Multilingual Joint Parsing of Syntactic and Semantic Dependencies with a Latent Variable Model. - James Henderson 001; Paola Merlo; Ivan Titov 001; Gabriele Musillo (Comput. Linguistics, 2013)

Inducing Neural Models of Script Knowledge. - Ashutosh Modi; Ivan Titov 001 (CoNLL, 2014)

A Hierarchical Bayesian Model for Unsupervised Induction of Script Knowledge. - Lea Frermann; Ivan Titov 001; Manfred Pinkal (EACL, 2014)

Improved Estimation of Entropy for Evaluation of Word Sense Induction. - Linlin Li 001; Ivan Titov 001; Caroline Sporleder (Comput. Linguistics, 2014)

Learning Semantic Script Knowledge with Event Embeddings. - Ashutosh Modi; Ivan Titov 001 (ICLR (Workshop), 2014)

Word Representations, Tree Models and Syntactic Functions. - Simon Suster; Gertjan van Noord; Ivan Titov 001 (CoRR, 2015)

Bilingual Learning of Multi-sense Embeddings with Discrete Autoencoders. - Simon Suster; Ivan Titov 001; Gertjan van Noord (HLT-NAACL, 2016)

Adapting to All Domains at Once: Rewarding Domain Invariance in SMT. - Cuong Hoang; Khalil Sima'an; Ivan Titov 001 (Trans. Assoc. Comput. Linguistics, 2016)

Discrete-State Variational Autoencoders for Joint Discovery and Factorization of Relations. - Diego Marcheggiani; Ivan Titov 001 (Trans. Assoc. Comput. Linguistics, 2016)

Optimizing Differentiable Relaxations of Coreference Evaluation Metrics. - Phong Le; Ivan Titov 001 (CoNLL, 2017)

A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling. - Diego Marcheggiani; Anton Frolov 001; Ivan Titov 001 (CoNLL, 2017)

Graph Convolutional Encoders for Syntax-aware Neural Machine Translation. - Jasmijn Bastings; Ivan Titov 001; Wilker Aziz; Diego Marcheggiani; Khalil Sima'an (EMNLP, 2017)

Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling. - Diego Marcheggiani; Ivan Titov 001 (EMNLP, 2017)

Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols. - Serhii Havrylov; Ivan Titov 001 (NIPS, 2017)

Modeling Semantic Expectation: Using Script Knowledge for Referent Prediction. - Ashutosh Modi; Ivan Titov 001; Vera Demberg; Asad B. Sayeed; Manfred Pinkal (CoRR, 2017)

Modelling Semantic Expectation: Using Script Knowledge for Referent Prediction. - Ashutosh Modi; Ivan Titov 001; Vera Demberg; Asad B. Sayeed; Manfred Pinkal (Trans. Assoc. Comput. Linguistics, 2017)

AMR Parsing as Graph Prediction with Latent Alignment. - Chunchuan Lyu; Ivan Titov 001 (ACL (1), 2018)

Improving Entity Linking by Modeling Latent Relations between Mentions. - Phong Le; Ivan Titov 001 (ACL (1), 2018)

Context-Aware Neural Machine Translation Learns Anaphora Resolution. - Elena Voita; Pavel Serdyukov; Rico Sennrich; Ivan Titov 001 (ACL (1), 2018)

Embedding Words as Distributions with a Bayesian Skip-gram Model. - Arthur Brazinskas; Serhii Havrylov; Ivan Titov 001 (COLING, 2018)

Modeling Relational Data with Graph Convolutional Networks. - Michael Sejr Schlichtkrull; Thomas N. Kipf; Peter Bloem; Rianne van den Berg; Ivan Titov 001; Max Welling (ESWC, 2018)

Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks. - Diego Marcheggiani; Jasmijn Bastings; Ivan Titov 001 (NAACL-HLT (2), 2018)

Interpretable Neural Predictions with Differentiable Binary Variables. - Jasmijn Bastings; Wilker Aziz; Ivan Titov 001 (ACL (1), 2019)

Boosting Entity Linking Performance by Leveraging Unlabeled Documents. - Phong Le; Ivan Titov 001 (ACL (1), 2019)

Distant Learning for Entity Linking with Automatic Noise Detection. - Phong Le; Ivan Titov 001 (ACL (1), 2019)

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 001 (ACL (1), 2019)

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 001 (ACL (1), 2019)

Capturing Argument Interaction in Semantic Role Labeling with Capsule Networks. - Xinchi Chen; Chunchuan Lyu; Ivan Titov 001 (EMNLP/IJCNLP (1), 2019)

Semantic Role Labeling with Iterative Structure Refinement. - Chunchuan Lyu; Shay B. Cohen; Ivan Titov 001 (EMNLP/IJCNLP (1), 2019)

Context-Aware Monolingual Repair for Neural Machine Translation. - Elena Voita; Rico Sennrich; Ivan Titov 001 (EMNLP/IJCNLP (1), 2019)

The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives. - Elena Voita; Rico Sennrich; Ivan Titov 001 (EMNLP/IJCNLP (1), 2019)

Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract Programs. - Bailin Wang; Ivan Titov 001; Mirella Lapata (EMNLP/IJCNLP (1), 2019)

Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention. - Biao Zhang 006; Ivan Titov 001; Rico Sennrich (EMNLP/IJCNLP (1), 2019)

Global Under-Resourced Media Translation (GoURMET). - Alexandra Birch; Barry Haddow; Ivan Titov 001; Antonio Valerio Miceli Barone; Rachel Bawden; Felipe Sánchez-Martínez; Mikel L. Forcada; Miquel Esplà-Gomis; Víctor M. Sánchez-Cartagena; Juan Antonio Pérez-Ortiz; Wilker Aziz; Andrew Secker; et al. (MTSummit (2), 2019)

Question Answering by Reasoning Across Documents with Graph Convolutional Networks. - Nicola De Cao; Wilker Aziz; Ivan Titov 001 (NAACL-HLT (1), 2019)

Single Document Summarization as Tree Induction. - Yang Liu 124; Ivan Titov 001; Mirella Lapata (NAACL-HLT (1), 2019)

Block Neural Autoregressive Flow. - Nicola De Cao; Wilker Aziz; Ivan Titov 001 (UAI, 2019)

Widening the Representation Bottleneck in Neural Machine Translation with Lexical Shortcuts. - Denis Emelin; Ivan Titov 001; Rico Sennrich (WMT (1), 2019)

Modeling Latent Sentence Structure in Neural Machine Translation. - Jasmijn Bastings; Wilker Aziz; Ivan Titov 001; Khalil Sima'an (CoRR, 2019)

The Emergence of Compositional Languages for Numeric Concepts Through Iterated Learning in Neural Agents. - Shangmin Guo; Yi Ren; Serhii Havrylov; Stella Frank; Ivan Titov 001; Kenny Smith (CoRR, 2019)

Unsupervised Multi-Document Opinion Summarization as Copycat-Review Generation. - Arthur Brazinskas; Mirella Lapata; Ivan Titov 001 (CoRR, 2019)

Unsupervised Opinion Summarization as Copycat-Review Generation. - Arthur Brazinskas; Mirella Lapata; Ivan Titov 001 (ACL, 2020)

Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation. - Biao Zhang 006; Philip Williams; Ivan Titov 001; Rico Sennrich (ACL, 2020)

Few-Shot Learning for Opinion Summarization. - Arthur Brazinskas; Mirella Lapata; Ivan Titov 001 (EMNLP (1), 2020)

How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking. - Nicola De Cao; Michael Sejr Schlichtkrull; Wilker Aziz; Ivan Titov 001 (EMNLP (1), 2020)

Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial Attacks. - Denis Emelin; Ivan Titov 001; Rico Sennrich (EMNLP (1), 2020)

Graph Convolutions over Constituent Trees for Syntax-Aware Semantic Role Labeling. - Diego Marcheggiani; Ivan Titov 001 (EMNLP (1), 2020)

Information-Theoretic Probing with Minimum Description Length. - Elena Voita; Ivan Titov 001 (EMNLP (1), 2020)

Adaptive Feature Selection for End-to-End Speech Translation. - Biao Zhang 006; Ivan Titov 001; Barry Haddow; Rico Sennrich (EMNLP (Findings), 2020)

Obfuscation for Privacy-preserving Syntactic Parsing. - Zhifeng Hu; Serhii Havrylov; Ivan Titov 001; Shay B. Cohen (IWPT 2020, 2020)

Fast Interleaved Bidirectional Sequence Generation. - Biao Zhang 006; Ivan Titov 001; Rico Sennrich (WMT@EMNLP, 2020)

Preventing Posterior Collapse with Levenshtein Variational Autoencoder. - Serhii Havrylov; Ivan Titov 001 (CoRR, 2020)

Few-Shot Learning for Abstractive Multi-Document Opinion Summarization. - Arthur Brazinskas; Mirella Lapata; Ivan Titov 001 (CoRR, 2020)

Exploring Unsupervised Pretraining Objectives for Machine Translation. - Christos Baziotis; Ivan Titov 001; Alexandra Birch; Barry Haddow (ACL/IJCNLP (Findings), 2021)

Meta-Learning to Compositionally Generalize. - Henry Conklin; Bailin Wang; Kenny Smith; Ivan Titov 001 (ACL/IJCNLP (1), 2021)

Analyzing the Source and Target Contributions to Predictions in Neural Machine Translation. - Elena Voita; Rico Sennrich; Ivan Titov 001 (ACL/IJCNLP (1), 2021)

A Closer Look into the Robustness of Neural Dependency Parsers Using Better Adversarial Examples. - Yuxuan Wang 001; Wanxiang Che; Ivan Titov 001; Shay B. Cohen; Zhilin Lei 001; Ting Liu 001 (ACL/IJCNLP (Findings), 2021)

Beyond Sentence-Level End-to-End Speech Translation: Context Helps. - Biao Zhang 006; Ivan Titov 001; Barry Haddow; Rico Sennrich (ACL/IJCNLP (1), 2021)

On Sparsifying Encoder Outputs in Sequence-to-Sequence Models. - Biao Zhang 006; Ivan Titov 001; Rico Sennrich (ACL/IJCNLP (Findings), 2021)

Learning Opinion Summarizers by Selecting Informative Reviews. - Arthur Brazinskas; Mirella Lapata; Ivan Titov 001 (EMNLP (1), 2021)

Editing Factual Knowledge in Language Models. - Nicola De Cao; Wilker Aziz; Ivan Titov 001 (EMNLP (1), 2021)

Highly Parallel Autoregressive Entity Linking with Discriminative Correction. - Nicola De Cao; Wilker Aziz; Ivan Titov 001 (EMNLP (1), 2021)

A Differentiable Relaxation of Graph Segmentation and Alignment for AMR Parsing. - Chunchuan Lyu; Shay B. Cohen; Ivan Titov 001 (EMNLP (1), 2021)

Language Modeling, Lexical Translation, Reordering: The Training Process of NMT through the Lens of Classical SMT. - Elena Voita; Rico Sennrich; Ivan Titov 001 (EMNLP (1), 2021)

Sparse Attention with Linear Units. - Biao Zhang 006; Ivan Titov 001; Rico Sennrich (EMNLP (1), 2021)

Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking. - Michael Sejr Schlichtkrull; Nicola De Cao; Ivan Titov 001 (ICLR, 2021)

Meta-Learning for Domain Generalization in Semantic Parsing. - Bailin Wang; Mirella Lapata; Ivan Titov 001 (NAACL-HLT, 2021)

Learning from Executions for Semantic Parsing. - Bailin Wang; Mirella Lapata; Ivan Titov 001 (NAACL-HLT, 2021)

Structured Reordering for Modeling Latent Alignments in Sequence Transduction. - Bailin Wang; Mirella Lapata; Ivan Titov 001 (NeurIPS, 2021)

Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation. - Verna Dankers; Christopher G. Lucas; Ivan Titov 001 (ACL (1), 2022)

Sparse Interventions in Language Models with Differentiable Masking. - Nicola De Cao; Leon Schmid; Dieuwke Hupkes; Ivan Titov 001 (BlackboxNLP@EMNLP, 2022)

Recursive Neural Networks with Bottlenecks Diagnose (Non-)Compositionality. - Verna Dankers; Ivan Titov 001 (EMNLP (Findings), 2022)

Hierarchical Phrase-Based Sequence-to-Sequence Learning. - Bailin Wang; Ivan Titov 001; Jacob Andreas; Yoon Kim (EMNLP, 2022)

Compositional Generalization without Trees using Multiset Tagging and Latent Permutations. - Matthias Lindemann; Alexander Koller; Ivan Titov 001 (ACL (1), 2023)

Compositional Generalisation with Structured Reordering and Fertility Layers. - Matthias Lindemann; Alexander Koller; Ivan Titov 001 (EACL, 2023)

Memorisation Cartography: Mapping out the Memorisation-Generalisation Continuum in Neural Machine Translation. - Verna Dankers; Ivan Titov 001; Dieuwke Hupkes (EMNLP, 2023)

Subspace Chronicles: How Linguistic Information Emerges, Shifts and Interacts during Language Model Training. - Max Müller-Eberstein; Rob van der Goot; Barbara Plank; Ivan Titov 001 (EMNLP (Findings), 2023)

Compositional Generalization for Data-to-Text Generation. - Xinnuo Xu; Ivan Titov 001; Mirella Lapata (EMNLP (Findings), 2023)

Theoretical and Practical Perspectives on what Influence Functions Do. - Andrea Schioppa; Katja Filippova; Ivan Titov 001; Polina Zablotskaia (NeurIPS, 2023)

Injecting a Structural Inductive Bias into a Seq2Seq Model by Simulation. - Matthias Lindemann; Alexander Koller; Ivan Titov 001 (CoRR, 2023)

Latent Feature-based Data Splits to Improve Generalisation Evaluation: A Hate Speech Detection Case Study. - Maike Züfle; Verna Dankers; Ivan Titov 001 (CoRR, 2023)

Generalisation First, Memorisation Second? Memorisation Localisation for Natural Language Classification Tasks. - Verna Dankers; Ivan Titov 001 (ACL (Findings), 2024)

SIP: Injecting a Structural Inductive Bias into a Seq2Seq Model by Simulation. - Matthias Lindemann; Alexander Koller; Ivan Titov 001 (ACL (1), 2024)

Cache & Distil: Optimising API Calls to Large Language Models. - Guillem Ramírez; Matthias Lindemann; Alexandra Birch; Ivan Titov 001 (ACL (Findings), 2024)

Strengthening Structural Inductive Biases by Pre-training to Perform Syntactic Transformations. - Matthias Lindemann; Alexander Koller; Ivan Titov 001 (EMNLP, 2024)

Autoencoding Conditional Neural Processes for Representation Learning. - Victor Prokhorov; Ivan Titov 001; N. Siddharth 001 (ICML, 2024)

Optimising Calls to Large Language Models with Uncertainty-Based Two-Tier Selection. - Guillem Ramírez; Alexandra Birch; Ivan Titov 001 (CoRR, 2024)

Disentangling Textual and Acoustic Features of Neural Speech Representations. - Hosein Mohebbi; Grzegorz Chrupala; Willem H. Zuidema; Afra Alishahi; Ivan Titov 001 (CoRR, 2024)

Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert Models. - Zihan Qiu; Zeyu Huang; Bo Zheng 007; Kaiyue Wen; Zekun Wang; Rui Men; Ivan Titov 001; Dayiheng Liu; Jingren Zhou 001; Junyang Lin (ACL (1), 2025)

Explanation Regularisation through the Lens of Attributions. - Pedro Ferreira; Ivan Titov 001; Wilker Aziz (COLING, 2025)

Language Agents Meet Causality - Bridging LLMs and Causal World Models. - John Gkountouras; Matthias Lindemann; Phillip Lippe; Efstratios Gavves; Ivan Titov 001 (ICLR, 2025)

Post-hoc Reward Calibration: A Case Study on Length Bias. - Zeyu Huang; Zihan Qiu; Zili Wang; Edoardo M. Ponti; Ivan Titov 001 (ICLR, 2025)

Layerwise Recurrent Router for Mixture-of-Experts. - Zihan Qiu; Zeyu Huang; Shuang Cheng; Yizhi Zhou; Zili Wang; Ivan Titov 001; Jie Fu 001 (ICLR, 2025)

Joint Localization and Activation Editing for Low-Resource Fine-Tuning. - Wen Lai; Alexander Fraser 001; Ivan Titov 001 (CoRR, 2025)

Truthful or Fabricated? Using Causal Attribution to Mitigate Reward Hacking in Explanations. - Pedro Ferreira; Wilker Aziz; Ivan Titov 001 (CoRR, 2025)

M-Wanda: Improving One-Shot Pruning for Multilingual LLMs. - Rochelle Choenni; Ivan Titov 001 (CoRR, 2025)

A Controllable Examination for Long-Context Language Models. - Yijun Yang; Zeyu Huang; Wenhao Zhu; Zihan Qiu; Fei Yuan 006; Jeff Z. Pan; Ivan Titov 001 (CoRR, 2025)

Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling. - Zeyu Huang; Tianhao Cheng; Zihan Qiu; Zili Wang; Yinghui Xu; Edoardo M. Ponti; Ivan Titov 001 (CoRR, 2025)

Controlling What You Share: Assessing Language Model Adherence to Privacy Preferences. - Guillem Ramírez; Alexandra Birch; Ivan Titov 001 (CoRR, 2025)