Estimating soft labels for out-of-domain intent detection
Out-of-Domain (OOD) intent detection is important for practical dialog systems. To alleviate
the issue of lacking OOD training samples, some works propose synthesizing pseudo OOD …
the issue of lacking OOD training samples, some works propose synthesizing pseudo OOD …
Learning discriminative representations and decision boundaries for open intent detection
Open intent detection is a significant problem in natural language understanding, which
aims to identify the unseen open intent while ensuring known intent identification …
aims to identify the unseen open intent while ensuring known intent identification …
Out-of-scope intent detection with intent-invariant data augmentation
F Sun, H Huang, P Yang, H Xu, X Mao - Knowledge-Based Systems, 2024 - Elsevier
In practical dialogue systems, it is crucial to avoid undesired responses and poor user
experiences by detecting Out-Of-Scope (OOS) intents from user utterances. Currently, to …
experiences by detecting Out-Of-Scope (OOS) intents from user utterances. Currently, to …
Few-shot out-of-scope intent classification: analyzing the robustness of prompt-based learning
Abstract Out-of-scope (OOS) intent classification is an emerging field in conversational AI
research. The goal is to detect out-of-scope user intents that do not belong to a predefined …
research. The goal is to detect out-of-scope user intents that do not belong to a predefined …
A Segment Augmentation and Prediction Consistency Framework for Multi-label Unknown Intent Detection
J Yang, M Chen, C Liu, B Dai, HT Zheng… - ACM Transactions on …, 2024 - dl.acm.org
Multi-label unknown intent detection is a challenging task where each utterance may contain
not only multiple known but also unknown intents. To tackle this challenge, pioneers …
not only multiple known but also unknown intents. To tackle this challenge, pioneers …
Multimodal Classification and Out-of-distribution Detection for Multimodal Intent Understanding
H Zhang, Q Zhou, H Xu, J Su, R Evans… - arXiv preprint arXiv …, 2024 - arxiv.org
Multimodal intent understanding is a significant research area that requires effectively
leveraging multiple modalities to analyze human language. Existing methods face two main …
leveraging multiple modalities to analyze human language. Existing methods face two main …
TK-KNN: A Balanced Distance-Based Pseudo Labeling Approach for Semi-Supervised Intent Classification
N Botzer, D Vasquez, T Weninger, I Laradji - arXiv preprint arXiv …, 2023 - arxiv.org
The ability to detect intent in dialogue systems has become increasingly important in modern
technology. These systems often generate a large amount of unlabeled data, and manually …
technology. These systems often generate a large amount of unlabeled data, and manually …
Improving Open Intent Detection via Triplet-Contrastive Learning and Adaptive Boundary
Open intent detection is a critical task within dialogue systems, aiming to effectively classify
known intents while also identifying unknown intents that have not been encountered in the …
known intents while also identifying unknown intents that have not been encountered in the …
Multi-Granularity Open Intent Classification via Adaptive Granular-Ball Decision Boundary
Open intent classification is critical for the development of dialogue systems, aiming to
accurately classify known intents into their corresponding classes while identifying unknown …
accurately classify known intents into their corresponding classes while identifying unknown …
[图书][B] Navigating Social Media Narratives
N Botzer - 2023 - search.proquest.com
As social media continues to shape modern society, understanding how individuals engage
in these online spaces and form overarching narratives is crucial. Narratives have a …
in these online spaces and form overarching narratives is crucial. Narratives have a …