Papers › Discovering New Intents with Deep Aligned Clustering

Discovering New Intents with Deep Aligned Clustering

16 Dec 2020arXiv:2012.08987archive 2025-07-28

Hanlei Zhang, Hua Xu, Ting-En Lin, Rui Lyu

Discovering new intents is a crucial task in dialogue systems. Most existing methods are limited in transferring the prior knowledge from known intents to new intents. They also have difficulties in providing high-quality supervised signals to learn clustering-friendly features for grouping unlabeled intents. In this work, we propose an effective method, Deep Aligned Clustering, to discover new intents with the aid of the limited known intent data. Firstly, we leverage a few labeled known intent samples as prior knowledge to pre-train the model. Then, we perform k-means to produce cluster assignments as pseudo-labels. Moreover, we propose an alignment strategy to tackle the label inconsistency problem during clustering assignments. Finally, we learn the intent representations under the supervision of the aligned pseudo-labels. With an unknown number of new intents, we predict the number of intent categories by eliminating low-confidence intent-wise clusters. Extensive experiments on two benchmark datasets show that our method is more robust and achieves substantial improvements over the state-of-the-art methods. The codes are released at https://github.com/thuiar/DeepAligned-Clustering.

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Code

hanleizhang/DeepAligned-Clustering officialmentioned in papermentioned on GitHubpytorch report

thuiar/DeepAligned-Clustering officialmentioned in papermentioned on GitHubpytorch report

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Tasks

Clustering Open Intent Discovery Short Text Clustering Text Clustering

Results from the paper archive 2025-07-28

Task	Dataset	Model	Metric	Value	Rank at snapshot	Leaderboard	Report
Open Intent Discovery	BANKING77	DeepAligned	ACC	64.9	#2 of 2	Archive leaderboard	report
Open Intent Discovery	BANKING77	DeepAligned	ARI	0.5364	#2 of 2	Archive leaderboard	report
Open Intent Discovery	BANKING77	DeepAligned	NMI	0.7956	#2 of 2	Archive leaderboard	report
Open Intent Discovery	CLINC150	DeepAligned	ACC	86.49	#2 of 2	Archive leaderboard	report
Open Intent Discovery	CLINC150	DeepAligned	ARI	0.7975	#2 of 2	Archive leaderboard	report
Open Intent Discovery	CLINC150	DeepAligned	NMI	0.9389	#2 of 2	Archive leaderboard	report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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