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Found 6 papers, 2 papers with code
Devil’s Advocate: Novel Boosting Ensemble Method from Psychological Findings for Text Classification
We present a new form of ensemble method–Devil’s Advocate, which uses a deliberately dissenting model to force other submodels within the ensemble to better collaborate.
Learning to Write with Coherence From Negative Examples
We compare our approach with Unlikelihood (UL) training in a text continuation task on commonsense natural language inference (NLI) corpora to show which method better models the coherence by avoiding unlikely continuations.
Human-Like Active Learning: Machines Simulating the Human Learning Process
In the end, we showed not only that we can make build better machine training framework through the human experiment result, but also empirically confirm the result of human experiment through imitated machine experiments; human-like active learning have crucial effect on learning performance.
Simulating Problem Difficulty in Arithmetic Cognition Through Dynamic Connectionist Models
Problem difficulty was operationalized by the number of carries involved in solving a given problem.
Constructing Hierarchical Q&A Datasets for Video Story Understanding
Video understanding is emerging as a new paradigm for studying human-like AI.
Dual Attention Networks for Visual Reference Resolution in Visual Dialog
Specifically, REFER module learns latent relationships between a given question and a dialog history by employing a self-attention mechanism.
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Visual Dialog
on VisDial v0.9 val
