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Papers › Unsupervised Deep Structured Semantic Models for Commonsense Reasoning

Unsupervised Deep Structured Semantic Models for Commonsense Reasoning

3 Apr 2019NAACL 2019 6arXiv:1904.01938archive 2025-07-28

Shuohang Wang, Sheng Zhang, Yelong Shen, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Jing Jiang

Commonsense reasoning is fundamental to natural language understanding. While traditional methods rely heavily on human-crafted features and knowledge bases, we explore learning commonsense knowledge from a large amount of raw text via unsupervised learning. We propose two neural network models based on the Deep Structured Semantic Models (DSSM) framework to tackle two classic commonsense reasoning tasks, Winograd Schema challenges (WSC) and Pronoun Disambiguation (PDP). Evaluation shows that the proposed models effectively capture contextual information in the sentence and co-reference information between pronouns and nouns, and achieve significant improvement over previous state-of-the-art approaches.

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Tasks

Common Sense ReasoningCoreference ResolutionNatural Language UnderstandingSentence

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Coreference Resolution Winograd Schema Challenge DSSM Accuracy 63.0 #47 of 82 Archive leaderboard report
Coreference Resolution Winograd Schema Challenge UDSSM-II (ensemble) Accuracy 62.4 #50 of 82 Archive leaderboard report
Coreference Resolution Winograd Schema Challenge UDSSM-II Accuracy 59.2 #60 of 82 Archive leaderboard report
Coreference Resolution Winograd Schema Challenge UDSSM-I (ensemble) Accuracy 57.1 #65 of 82 Archive leaderboard report
Coreference Resolution Winograd Schema Challenge UDSSM-I Accuracy 54.5 #72 of 82 Archive leaderboard report
Natural Language Understanding PDP60 UDSSM-II (ensemble) Accuracy 78.3 #3 of 13 Archive leaderboard report
Natural Language Understanding PDP60 UDSSM-I (ensemble) Accuracy 76.7 #4 of 13 Archive leaderboard report
Natural Language Understanding PDP60 DSSM Accuracy 75.0 #5 of 13 Archive leaderboard report
Natural Language Understanding PDP60 UDSSM-II Accuracy 75 #6 of 13 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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