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Found 8 papers, 2 papers with code
CLEVR-POC: Reasoning-Intensive Visual Question Answering in Partially Observable Environments
In CLEVR-POC, knowledge in the form of logical constraints needs to be leveraged to generate plausible answers to questions about a hidden object in a given partial scene.
REDAffectiveLM: Leveraging Affect Enriched Embedding and Transformer-based Neural Language Model for Readers' Emotion Detection
Towards this, we leverage context-specific and affect enriched representations by using a transformer-based pre-trained language model in tandem with affect enriched Bi-LSTM+Attention.
CLEVR-Math: A Dataset for Compositional Language, Visual and Mathematical Reasoning
We introduce CLEVR-Math, a multi-modal math word problems dataset consisting of simple math word problems involving addition/subtraction, represented partly by a textual description and partly by an image illustrating the scenario.
Why are NLP Models Fumbling at Elementary Math? A Survey of Deep Learning based Word Problem Solvers
From the latter half of the last decade, there has been a growing interest in developing algorithms for automatically solving mathematical word problems (MWP).
Compositional Generalization and Neuro-Symbolic Architectures
Compositional generalization is the ability to understand novel combinations of known concepts.
Representativity Fairness in Clustering
We illustrate the importance of representativity fairness in real-world decision making scenarios involving clustering and provide ways of quantifying objects' representativity and fairness over it.
Fair Outlier Detection
Being a novel task, we develop an evaluation framework for fair outlier detection, and use that to benchmark FairLOF on quality and fairness of results.
Fairness in Clustering with Multiple Sensitive Attributes
Our experimental evaluation illustrates that the clusters generated by FairKM fare significantly better on both clustering quality and fair representation of sensitive attribute groups compared to the clusters from a state-of-the-art baseline fair clustering method.
