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Ivan Titov

  1. Modeling Relational Data with Graph Convolutional Networks
    2017/03/17 by Michael Schlichtkrull, Schlichtkrull, Michael, Thomas Kipf +9 · 135 citations
    Computer Science · #Advanced Graph Neural Networks #Topic Modeling #Bayesian Modeling and Causal Inference
  2. Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned
    2019/05/23 by Elena Voita, Voita, Elena, David Talbot +7 · 93 citations
    Computer Science · #Natural Language Processing Techniques #Topic Modeling #Software Engineering Research
  3. Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols
    2017/05/31 by Serhii Havrylov, Havrylov, Serhii, Ivan Titov +1 · 26 citations
    Social Sciences · Computer Science · #Language and cultural evolution #Evolutionary Algorithms and Applications #Reinforcement Learning in Robotics
  4. Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation
    2020/04/24 by Biao Zhang, Philip Williams, Zhang, Biao +5 · 25 citations
    Computer Science · #Natural Language Processing Techniques #Topic Modeling #Multimodal Machine Learning Applications
  5. The Bottom-up Evolution of Representations in the Transformer: A Study\n with Machine Translation and Language Modeling Objectives
    2019/09/03 by Elena Voita, Rico Sennrich, Voita, Elena +3 · 12 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Speech Recognition and Synthesis #Topic Modeling
  6. Block Neural Autoregressive Flow
    2019/04/09 by Nicola De Cao, Ivan Titov, De Cao, Nicola +3 · 15 citations
    Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare #Neural Networks and Applications
  7. Encoding Sentences with Graph Convolutional Networks for Semantic Role\n Labeling
    2017/03/14 by Diego Marcheggiani, Ivan Titov, Marcheggiani, Diego +1 · 9 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
  8. Subspace Chronicles: How Linguistic Information Emerges, Shifts and Interacts during Language Model Training
    2023/10/25 by Max Müller-Eberstein, Rob van der Goot, Müller-Eberstein, Max +5 · 7 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Speech and dialogue systems #Topic Modeling
  9. Unlearning Traces the Influential Training Data of Language Models
    2024/01/26 by Masaru Isonuma, Isonuma, Masaru, Ivan Titov +1 · 6 citations
    Computer Science · #Topic Modeling #Natural Language Processing Techniques
  10. Post-hoc Reward Calibration: A Case Study on Length Bias
    2024/09/25 by Zeyu Huang, Zihan Qiu, Huang, Zeyu +7 · 8 citations
    Decision Sciences · Engineering · #Advanced Statistical Process Monitoring #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Fault Detection and Control Systems #Scientific Measurement and Uncertainty Evaluation
  11. Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert Models
    2025/01/21 by Zihan Qiu, Zeyu Huang, Qiu, Zihan +17 · 8 citations
    Decision Sciences · Computer Science · #Simulation Techniques and Applications #Scientific Computing and Data Management #AI-based Problem Solving and Planning
  12. Learning Opinion Summarizers by Selecting Informative Reviews
    2021/09/09 by Arthur Bražinskas, Bražinskas, Arthur, Mirella Lapata +3 · 3 citations
    Computer Science · #Advanced Text Analysis Techniques #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Sentiment Analysis and Opinion Mining #Topic Modeling
  13. Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling
    2025/07/02 by Zeyu Huang, Tianhao Cheng, Huang, Zeyu +11 · 17 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification #Natural Language Processing Techniques #Topic Modeling
  14. How do Decisions Emerge across Layers in Neural Models? Interpretation\n with Differentiable Masking
    2020/04/30 by Nicola De Cao, De Cao, Nicola, Michael Schlichtkrull +5 · 2 citations
    Computer Science · Materials Science · #Computation and Language (cs.CL) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (stat.ML) #Machine Learning in Materials Science #Topic Modeling
  15. Analyzing the Source and Target Contributions to Predictions in Neural\n Machine Translation
    2020/10/21 by Elena Voita, Rico Sennrich, Voita, Elena +3 · 2 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
  16. Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation
    2022/05/30 by Verna Dankers, Dankers, Verna, Christopher G. Lucas +3 · 2 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques
  17. Language Agents Meet Causality -- Bridging LLMs and Causal World Models
    2024/10/25 by John Gkountouras, Gkountouras, John, Matthias Lindemann +7 · 4 citations
    Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Methodology (stat.ME) #Multi-Agent Systems and Negotiation #Natural Language Processing Techniques #Topic Modeling
  18. Truthful or Fabricated? Using Causal Attribution to Mitigate Reward Hacking in Explanations
    2025/04/07 by Pedro D. Ferreira, Ferreira, Pedro, Wilker Aziz +3 · 4 citations
    Computer Science · Medicine · #Explainable Artificial Intelligence (XAI) #Artificial Intelligence in Healthcare and Education #Topic Modeling
  19. A Differentiable Relaxation of Graph Segmentation and Alignment for AMR\n Parsing
    2020/10/23 by Chunchuan Lyu, Lyu, Chunchuan, Shay B. Cohen +3 · 1 citation
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Bioinformatics #Natural Language Processing Techniques #Topic Modeling
  20. On Sparsifying Encoder Outputs in Sequence-to-Sequence Models
    2020/04/24 by Biao Zhang, Zhang, Biao, Ivan Titov +3 · 2 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Speech Recognition and Synthesis #Topic Modeling
  21. Embedding Words as Distributions with a Bayesian Skip-gram Model
    2017/11/29 by Arthur Bražinskas, Serhii Havrylov, Bražinskas, Arthur +3 · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Speech Recognition and Synthesis #Topic Modeling
  22. Bilingual Learning of Multi-sense Embeddings with Discrete Autoencoders
    2016/03/30 by Simon Šuster, Šuster, Simon, Ivan Titov +3 · 1 citation
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Natural Language Processing Techniques #Speech Recognition and Synthesis #Topic Modeling
  23. Preventing Posterior Collapse with Levenshtein Variational Autoencoder
    2020/04/30 by Serhii Havrylov, Havrylov, Serhii, Ivan Titov +1 · 1 citation
    Computer Science · #Computation and Language (cs.CL) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Natural Language Processing Techniques #Topic Modeling
  24. Strengthening Structural Inductive Biases by Pre-training to Perform Syntactic Transformations
    2024/07/05 by Matthias Lindemann, Lindemann, Matthias, Alexander Koller +3 · 1 citation
    Computer Science · Neuroscience · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Intelligent Tutoring Systems and Adaptive Learning #Neural Networks and Applications #Neurobiology of Language and Bilingualism
  25. Magnetic microstructure of nanocrystalline Fe-Nb-B alloys as seen by small-angle neutron and X-ray scattering
    2024/05/23 by Venus Rai, Rai, Venus, Ivan Titov +9 · 1 citation
    Engineering · Materials Science · #FOS: Physical sciences #Magnetic Properties and Applications #Magnetic Properties of Alloys #Materials Science (cond-mat.mtrl-sci) #Mesoscale and Nanoscale Physics (cond-mat.mes-hall) #Microstructure and Mechanical Properties of Steels
  26. M-Wanda: Improving One-Shot Pruning for Multilingual LLMs
    2025/05/27 by Rochelle Choenni, Choenni, Rochelle, Ivan Titov +1 · 1 citation
    Arts and Humanities · Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Semantic Web and Ontologies #Translation Studies and Practices
  27. Memorisation Cartography: Mapping out the Memorisation-Generalisation Continuum in Neural Machine Translation
    2023/11/09 by Verna Dankers, Dankers, Verna, Ivan Titov +3 · 2 voices
    Computer Science · #Natural Language Processing Techniques #Topic Modeling #cs.CL