Dialogue Understanding
29 papers with code • 0 benchmarks • 9 datasets
Benchmarks
These leaderboards are used to track progress in Dialogue Understanding
Datasets
Doc2Dial
ProsocialDialog
DiaASQ
WDC-Dialogue
Emotional Dialogue Acts
The Mafia Dataset
Most implemented papers
Learning Dialogue Representations from Consecutive Utterances
amazon-research/dse
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NAACL 2022
In this paper, we introduce Dialogue Sentence Embedding (DSE), a self-supervised contrastive learning method that learns effective dialogue representations suitable for a wide range of dialogue tasks.
Semantic-based Pre-training for Dialogue Understanding
goodbai-nlp/sem-plm
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COLING 2022
However, these models are typically trained on surface dialogue text, thus are proven to be weak in understanding the main semantic meaning of a dialogue context.
DialoGen: Generalized Long-Range Context Representation for Dialogue Systems
In this work, we propose DialoGen, a novel encoder-decoder based framework for dialogue generation with a generalized context representation that can look beyond the last-$k$ utterances.
Hierarchical Dialogue Understanding with Special Tokens and Turn-level Attention
shawx825/hidialog
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Tiny Papers @ ICLR 2023
We evaluate our model on various dialogue understanding tasks including dialogue relation extraction, dialogue emotion recognition, and dialogue act classification.
Medical Dialogue Generation via Dual Flow Modeling
kaishxu/DFMed
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It extracts the medical entities and dialogue acts used in the dialogue history and models their transitions with an entity-centric graph flow and a sequential act flow, respectively.
VSTAR: A Video-grounded Dialogue Dataset for Situated Semantic Understanding with Scene and Topic Transitions
Video-grounded dialogue understanding is a challenging problem that requires machine to perceive, parse and reason over situated semantics extracted from weakly aligned video and dialogues.
Revisit Input Perturbation Problems for LLMs: A Unified Robustness Evaluation Framework for Noisy Slot Filling Task
To address these challenges, we propose a unified robustness evaluation framework based on the slot-filling task to systematically evaluate the dialogue understanding capability of LLMs in diverse input perturbation scenarios.
From Multilingual Complexity to Emotional Clarity: Leveraging Commonsense to Unveil Emotions in Code-Mixed Dialogues
Recognizing that emotional intelligence encompasses a comprehension of worldly knowledge, we propose an innovative approach that integrates commonsense information with dialogue context to facilitate a deeper understanding of emotions.
PromptCBLUE: A Chinese Prompt Tuning Benchmark for the Medical Domain
Biomedical language understanding benchmarks are the driving forces for artificial intelligence applications with large language model (LLM) back-ends.
