Systematic Generalization
61 papers with code • 0 benchmarks • 7 datasets
Benchmarks
These leaderboards are used to track progress in Systematic Generalization
Libraries
Use these libraries to find Systematic Generalization models and implementations
SCAN
GSCAN
Mathematics Dataset
PCFG SET
S2B
Latest papers
Slot Abstractors: Toward Scalable Abstract Visual Reasoning
slotabstractor/slotabstractor
•
•
Abstract visual reasoning is a characteristically human ability, allowing the identification of relational patterns that are abstracted away from object features, and the systematic generalization of those patterns to unseen problems.
Case-Based or Rule-Based: How Do Transformers Do the Math?
Through carefully designed intervention experiments on five math tasks, we confirm that transformers are performing case-based reasoning, no matter whether scratchpad is used, which aligns with the previous observations that transformers use subgraph matching/shortcut learning to reason.
On the generalization capacity of neural networks during generic multimodal reasoning
ibm/gcog
•
•
On the other hand, neither of these architectural features led to productive generalization, suggesting fundamental limitations of existing architectures for specific types of multimodal generalization.
Compositional Program Generation for Few-Shot Systematic Generalization
IBM/cpg
•
•
Compositional generalization is a key ability of humans that enables us to learn new concepts from only a handful examples.
D3: Data Diversity Design for Systematic Generalization in Visual Question Answering
amiroor/d3questiongenerationclevr
•
•
We demonstrate that this result is independent of the similarity between the training and testing data and applies to well-known families of neural network architectures for VQA (i. e. monolithic architectures and neural module networks).
A Hybrid System for Systematic Generalization in Simple Arithmetic Problems
Solving symbolic reasoning problems that require compositionality and systematicity is considered one of the key ingredients of human intelligence.
Learning to Substitute Spans towards Improving Compositional Generalization
Despite the rising prevalence of neural sequence models, recent empirical evidences suggest their deficiency in compositional generalization.
Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts
ema-marconato/reasoning-shortcuts
•
•
NeurIPS 2023
Neuro-Symbolic (NeSy) predictive models hold the promise of improved compliance with given constraints, systematic generalization, and interpretability, as they allow to infer labels that are consistent with some prior knowledge by reasoning over high-level concepts extracted from sub-symbolic inputs.
HICO-DET-SG and V-COCO-SG: New Data Splits for Evaluating the Systematic Generalization Performance of Human-Object Interaction Detection Models
Human-Object Interaction (HOI) detection is a task to localize humans and objects in an image and predict the interactions in human-object pairs.
Neural Compositional Rule Learning for Knowledge Graph Reasoning
vivian1993/ncrl
•
•
NCRL detects the best compositional structure of a rule body, and breaks it into small compositions in order to infer the rule head.
