Ivan Kobyzev

Orcid: 0000-0003-1934-4842

According to our database1, Ivan Kobyzev authored at least 27 papers between 2019 and 2024.

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

Timeline

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Bibliography

2024
Draft on the Fly: Adaptive Self-Speculative Decoding using Cosine Similarity.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Resonance RoPE: Improving Context Length Generalization of Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

OTTAWA: Optimal TransporT Adaptive Word Aligner for Hallucination and Omission Translation Errors Detection.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Hyperparameter Optimization for Large Language Model Instruction-Tuning.
CoRR, 2023

Mathematical Challenges in Deep Learning.
CoRR, 2023

Efficient Classification of Long Documents via State-Space Models.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

DyLoRA: Parameter-Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation.
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

Do we need Label Regularization to Fine-tune Pre-trained Language Models?
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

LABO: Towards Learning Optimal Label Regularization via Bi-level Optimization.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Attribute Controlled Dialogue Prompting.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
KronA: Parameter Efficient Tuning with Kronecker Adapter.
CoRR, 2022

Towards Understanding Label Regularization for Fine-tuning Pre-trained Language Models.
CoRR, 2022

Learning functions on multiple sets using multi-set transformers.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Improving Generalization of Pre-trained Language Models via Stochastic Weight Averaging.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Continuation KD: Improved Knowledge Distillation through the Lens of Continuation Optimization.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021
Normalizing Flows: An Introduction and Review of Current Methods.
IEEE Trans. Pattern Anal. Mach. Intell., 2021

Equivariant Discrete Normalizing Flows.
CoRR, 2021

A Short Study on Compressing Decoder-Based Language Models.
CoRR, 2021

Polarized-VAE: Proximity Based Disentangled Representation Learning for Text Generation.
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

2020
Representation Learning for Dynamic Graphs: A Survey.
J. Mach. Learn. Res., 2020

Generating Emotionally Aligned Responses in Dialogues using Affect Control Theory.
CoRR, 2020

Tails of Lipschitz Triangular Flows.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Normalizing Flows: Introduction and Ideas.
CoRR, 2019

A semi-holographic hyperdimensional representation system for hardware-friendly cognitive computing.
CoRR, 2019

Tails of Triangular Flows.
CoRR, 2019

Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey.
CoRR, 2019

A Categorical Approach to Cyclic Cohomology of Quasi-Hopf Algebras and Hopf Algebroids.
Appl. Categorical Struct., 2019


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