Papers with neural module networks
Social Norms-Grounded Machine Ethics in Complex Narrative Situation (2022.coling-1)
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| Challenge: | Recent studies focus on data-driven methods to judge the ethics of complex real-world narratives but face two major challenges: they cannot handle dilemma situations due to a lack of basic knowledge about social norms; and they focus on sparse situation-level judgment regardless of the social norm. |
| Approach: | They propose to complement a complex situation with grounded social norms by a norm-supported ethical judgment model in line with neural module networks to alleviate dilemma situations and improve norm-level explainability. |
| Outcome: | The proposed model improves state-of-the-art performance on two narrative judgment benchmarks. |
Multi-Step Inference for Reasoning Over Paragraphs (2020.emnlp-main)
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| Challenge: | Existing models for complex reasoning use symbols or black-box transformers . a compositional model can chain together free-form predicates and logical connectives . |
| Approach: | They propose a compositional model that finds relevant sentences and then chains them together using neural modules. |
| Outcome: | The proposed model improves performance on a recently-introduced dataset. |
Paired Examples as Indirect Supervision in Latent Decision Models (2021.emnlp-main)
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| Challenge: | a new method to learn compositional structured models is needed . end-task supervision provides only a weak indirect signal on values the latent decisions should take. |
| Approach: | They propose a way to leverage paired examples that provide stronger cues for learning latent decisions . they use a DROP dataset to acquire paired questions that provide strong cue signals . |
| Outcome: | The proposed approach improves compositional question answering on a DROP dataset. |