Ivan Titov

Affiliations:
  • University of Amsterdam, The Netherlands
  • University of Edinburgh, UK
  • University of Geneva, Switzerland (PhD 2008)


According to our database1, Ivan Titov authored at least 127 papers between 2005 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Controlling What You Share: Assessing Language Model Adherence to Privacy Preferences.
CoRR, July, 2025

Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling.
CoRR, July, 2025

A Controllable Examination for Long-Context Language Models.
CoRR, June, 2025

M-Wanda: Improving One-Shot Pruning for Multilingual LLMs.
CoRR, May, 2025

Truthful or Fabricated? Using Causal Attribution to Mitigate Reward Hacking in Explanations.
CoRR, April, 2025

Joint Localization and Activation Editing for Low-Resource Fine-Tuning.
CoRR, February, 2025

Layerwise Recurrent Router for Mixture-of-Experts.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Post-hoc Reward Calibration: A Case Study on Length Bias.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Language Agents Meet Causality - Bridging LLMs and Causal World Models.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Explanation Regularisation through the Lens of Attributions.
Proceedings of the 31st International Conference on Computational Linguistics, 2025

Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert Models.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024
Disentangling Textual and Acoustic Features of Neural Speech Representations.
CoRR, 2024

Optimising Calls to Large Language Models with Uncertainty-Based Two-Tier Selection.
CoRR, 2024

Autoencoding Conditional Neural Processes for Representation Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Strengthening Structural Inductive Biases by Pre-training to Perform Syntactic Transformations.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Cache & Distil: Optimising API Calls to Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

SIP: Injecting a Structural Inductive Bias into a Seq2Seq Model by Simulation.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Generalisation First, Memorisation Second? Memorisation Localisation for Natural Language Classification Tasks.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Latent Feature-based Data Splits to Improve Generalisation Evaluation: A Hate Speech Detection Case Study.
CoRR, 2023

Injecting a Structural Inductive Bias into a Seq2Seq Model by Simulation.
CoRR, 2023

Theoretical and Practical Perspectives on what Influence Functions Do.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Compositional Generalization for Data-to-Text Generation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Subspace Chronicles: How Linguistic Information Emerges, Shifts and Interacts during Language Model Training.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Memorisation Cartography: Mapping out the Memorisation-Generalisation Continuum in Neural Machine Translation.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Compositional Generalisation with Structured Reordering and Fertility Layers.
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

Compositional Generalization without Trees using Multiset Tagging and Latent Permutations.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Hierarchical Phrase-Based Sequence-to-Sequence Learning.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Recursive Neural Networks with Bottlenecks Diagnose (Non-)Compositionality.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Sparse Interventions in Language Models with Differentiable Masking.
Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2022

Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Structured Reordering for Modeling Latent Alignments in Sequence Transduction.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning from Executions for Semantic Parsing.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Meta-Learning for Domain Generalization in Semantic Parsing.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking.
Proceedings of the 9th International Conference on Learning Representations, 2021

Sparse Attention with Linear Units.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Language Modeling, Lexical Translation, Reordering: The Training Process of NMT through the Lens of Classical SMT.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

A Differentiable Relaxation of Graph Segmentation and Alignment for AMR Parsing.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Highly Parallel Autoregressive Entity Linking with Discriminative Correction.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Editing Factual Knowledge in Language Models.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Learning Opinion Summarizers by Selecting Informative Reviews.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

On Sparsifying Encoder Outputs in Sequence-to-Sequence Models.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

Beyond Sentence-Level End-to-End Speech Translation: Context Helps.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

A Closer Look into the Robustness of Neural Dependency Parsers Using Better Adversarial Examples.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

Analyzing the Source and Target Contributions to Predictions in Neural Machine Translation.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Meta-Learning to Compositionally Generalize.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Exploring Unsupervised Pretraining Objectives for Machine Translation.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020
Few-Shot Learning for Abstractive Multi-Document Opinion Summarization.
CoRR, 2020

Preventing Posterior Collapse with Levenshtein Variational Autoencoder.
CoRR, 2020

Fast Interleaved Bidirectional Sequence Generation.
Proceedings of the Fifth Conference on Machine Translation, 2020

Obfuscation for Privacy-preserving Syntactic Parsing.
Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies, 2020

Adaptive Feature Selection for End-to-End Speech Translation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Information-Theoretic Probing with Minimum Description Length.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Graph Convolutions over Constituent Trees for Syntax-Aware Semantic Role Labeling.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial Attacks.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Few-Shot Learning for Opinion Summarization.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Unsupervised Opinion Summarization as Copycat-Review Generation.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Unsupervised Multi-Document Opinion Summarization as Copycat-Review Generation.
CoRR, 2019

The Emergence of Compositional Languages for Numeric Concepts Through Iterated Learning in Neural Agents.
CoRR, 2019

Modeling Latent Sentence Structure in Neural Machine Translation.
CoRR, 2019

Widening the Representation Bottleneck in Neural Machine Translation with Lexical Shortcuts.
Proceedings of the Fourth Conference on Machine Translation, 2019

Block Neural Autoregressive Flow.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Single Document Summarization as Tree Induction.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Question Answering by Reasoning Across Documents with Graph Convolutional Networks.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019


Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract Programs.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Context-Aware Monolingual Repair for Neural Machine Translation.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Semantic Role Labeling with Iterative Structure Refinement.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Capturing Argument Interaction in Semantic Role Labeling with Capsule Networks.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Distant Learning for Entity Linking with Automatic Noise Detection.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Boosting Entity Linking Performance by Leveraging Unlabeled Documents.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Interpretable Neural Predictions with Differentiable Binary Variables.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Modeling Relational Data with Graph Convolutional Networks.
Proceedings of the Semantic Web - 15th International Conference, 2018

Embedding Words as Distributions with a Bayesian Skip-gram Model.
Proceedings of the 27th International Conference on Computational Linguistics, 2018

Context-Aware Neural Machine Translation Learns Anaphora Resolution.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

Improving Entity Linking by Modeling Latent Relations between Mentions.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

AMR Parsing as Graph Prediction with Latent Alignment.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017
Modelling Semantic Expectation: Using Script Knowledge for Referent Prediction.
Trans. Assoc. Comput. Linguistics, 2017

Modeling Semantic Expectation: Using Script Knowledge for Referent Prediction.
CoRR, 2017

Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Graph Convolutional Encoders for Syntax-aware Neural Machine Translation.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling.
Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), 2017

Optimizing Differentiable Relaxations of Coreference Evaluation Metrics.
Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), 2017

2016
Discrete-State Variational Autoencoders for Joint Discovery and Factorization of Relations.
Trans. Assoc. Comput. Linguistics, 2016

Adapting to All Domains at Once: Rewarding Domain Invariance in SMT.
Trans. Assoc. Comput. Linguistics, 2016

Bilingual Learning of Multi-sense Embeddings with Discrete Autoencoders.
Proceedings of the NAACL HLT 2016, 2016

2015
Word Representations, Tree Models and Syntactic Functions.
CoRR, 2015

2014
Learning Semantic Script Knowledge with Event Embeddings.
Proceedings of the 2nd International Conference on Learning Representations, 2014

Improved Estimation of Entropy for Evaluation of Word Sense Induction.
Comput. Linguistics, 2014

A Hierarchical Bayesian Model for Unsupervised Induction of Script Knowledge.
Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, 2014

Inducing Neural Models of Script Knowledge.
Proceedings of the Eighteenth Conference on Computational Natural Language Learning, 2014

2013
Multilingual Joint Parsing of Syntactic and Semantic Dependencies with a Latent Variable Model.
Comput. Linguistics, 2013

Semantic Role Labeling.
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2013

Translating Video Content to Natural Language Descriptions.
Proceedings of the IEEE International Conference on Computer Vision, 2013

Predicting the Resolution of Referring Expressions from User Behavior.
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 2013

A Bayesian Model for Joint Unsupervised Induction of Sentiment, Aspect and Discourse Representations.
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, 2013

2012
A Bayesian Approach to Unsupervised Semantic Role Induction.
Proceedings of the EACL 2012, 2012

Semi-Supervised Semantic Role Labeling: Approaching from an Unsupervised Perspective.
Proceedings of the COLING 2012, 2012

Inducing Crosslingual Distributed Representations of Words.
Proceedings of the COLING 2012, 2012

Crosslingual Induction of Semantic Roles.
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, July 8-14, 2012, Jeju Island, Korea, 2012

2011
A Bayesian Model for Unsupervised Semantic Parsing.
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, 2011

2010
Unsupervised Aggregation for Classification Problems with Large Numbers of Categories.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Incremental Sigmoid Belief Networks for Grammar Learning.
J. Mach. Learn. Res., 2010

A Latent Variable Model for Generative Dependency Parsing.
Proceedings of the Trends in Parsing Technology, 2010

2009
Sequential Learning of Classifiers for Structured Prediction Problems.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Online Graph Planarisation for Synchronous Parsing of Semantic and Syntactic Dependencies.
Proceedings of the IJCAI 2009, 2009

Unsupervised Rank Aggregation with Domain-Specific Expertise.
Proceedings of the IJCAI 2009, 2009

A Latent Variable Model of Synchronous Syntactic-Semantic Parsing for Multiple Languages.
Proceedings of the Thirteenth Conference on Computational Natural Language Learning: Shared Task, 2009

2008
Exploiting non-linear probabilistic models in natural language parsing and reranking.
PhD thesis, 2008

Modeling online reviews with multi-grain topic models.
Proceedings of the 17th International Conference on World Wide Web, 2008

A Latent Variable Model of Synchronous Parsing for Syntactic and Semantic Dependencies.
Proceedings of the Twelfth Conference on Computational Natural Language Learning, 2008

A Joint Model of Text and Aspect Ratings for Sentiment Summarization.
Proceedings of the ACL 2008, 2008

2007
A Latent Variable Model for Generative Dependency Parsing.
Proceedings of the Tenth International Conference on Parsing Technologies, 2007

Incremental Bayesian networks for structure prediction.
Proceedings of the Machine Learning, 2007

Fast and Robust Multilingual Dependency Parsing with a Generative Latent Variable Model.
Proceedings of the EMNLP-CoNLL 2007, 2007

Constituent Parsing with Incremental Sigmoid Belief Networks.
Proceedings of the ACL 2007, 2007

2006
Loss Minimization in Parse Reranking.
Proceedings of the EMNLP 2006, 2006

Porting Statistical Parsers with Data-Defined Kernels.
Proceedings of the Tenth Conference on Computational Natural Language Learning, 2006

2005
Deriving kernels from MLP probability estimators for large categorization problems.
Proceedings of the IEEE International Joint Conference on Neural Networks, 2005

Data-Defined Kernels for Parse Reranking Derived from Probabilistic Models.
Proceedings of the ACL 2005, 2005


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