Elamur Research
☰
home / papers / Large-scale text pre-training helps with dialogue… / cited by

Who cites «Large-scale text pre-training helps with dialogue act recognition, but not without fine-tuning»

7 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

  1. Investigating the Representation of Backchannels and Fillers in Fine-tuned Language Models — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  2. Emergent Wisdom at BEA 2025 Shared Task: From Lexical Understanding to Reflective Reasoning for Pedagogical Ability Assessment — 2025 · Proceedings of the 20th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2025)
  3. Conversational Feedback in Scripted versus Spontaneous Dialogues: A Comparative Analysis — 2024 · Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue
  4. Dual Process Masking for Dialogue Act Recognition — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  5. Do dialogue representations align with perception? An empirical study — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  6. Dialogue Act and Slot Recognition in Italian Complex Dialogues — 2022 · Proceedings of the Workshop on Resources and Technologies for Indigenous, Endangered and Lesser-resourced Languages in Eurasia within the 13th Language Resources and Evaluation Conference
  7. Improving Dialogue Act Recognition with Augmented Data — 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)