Igor Shalyminov

Orcid: 0000-0001-9664-1774

According to our database1, Igor Shalyminov authored at least 24 papers between 2017 and 2024.

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

Timeline

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Bibliography

2024
MAGID: An Automated Pipeline for Generating Synthetic Multi-modal Datasets.
CoRR, 2024

TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization.
CoRR, 2024

TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Semi-Supervised Dialogue Abstractive Summarization via High-Quality Pseudolabel Selection.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

CERET: Cost-Effective Extrinsic Refinement for Text Generation.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

MAGID: An Automated Pipeline for Generating Synthetic Multi-modal Datasets.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Controllable Contextualized Image Captioning: Directing the Visual Narrative Through User-Defined Highlights.
Proceedings of the Computer Vision - ECCV 2024, 2024

Can Your Model Tell a Negation from an Implicature? Unravelling Challenges With Intent Encoders.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

FineSurE: Fine-grained Summarization Evaluation using LLMs.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
Enhancing Abstractiveness of Summarization Models through Calibrated Distillation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2021
GRTr: Generative-Retrieval Transformers for Data-Efficient Dialogue Domain Adaptation.
IEEE ACM Trans. Audio Speech Lang. Process., 2021

2020
Data-Efficient Methods for Dialogue Systems.
CoRR, 2020

Hybrid Generative-Retrieval Transformers for Dialogue Domain Adaptation.
CoRR, 2020

Fast Domain Adaptation for Goal-Oriented Dialogue Using a Hybrid Generative-Retrieval Transformer.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Few-Shot Dialogue Generation Without Annotated Data: A Transfer Learning Approach.
Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue, 2019

Contextual Out-of-domain Utterance Handling with Counterfeit Data Augmentation.
Proceedings of the IEEE International Conference on Acoustics, 2019

Data-Efficient Goal-Oriented Conversation with Dialogue Knowledge Transfer Networks.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018
Improving Robustness of Neural Dialog Systems in a Data-Efficient Way with Turn Dropout.
CoRR, 2018

Multi-Task Learning for Domain-General Spoken Disfluency Detection in Dialogue Systems.
CoRR, 2018

Neural Response Ranking for Social Conversation: A Data-Efficient Approach.
Proceedings of the 2nd International Workshop on Search-Oriented Conversational AI, 2018

2017
An Ensemble Model with Ranking for Social Dialogue.
CoRR, 2017

Challenging Neural Dialogue Models with Natural Data: Memory Networks Fail on Incremental Phenomena.
CoRR, 2017

Interactional dynamics and the emergence of language games.
Proceedings of the Workshop on Formal Approaches to the Dynamics of Linguistic Interaction 2017 co-located within the European Summer School on Logic, 2017

Bootstrapping incremental dialogue systems from minimal data: the generalisation power of dialogue grammars.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017


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