Systematic Generalization
66 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
Most implemented papers
Multi-Object Representation Learning with Iterative Variational Inference
deepmind/deepmind-research
•
•
Human perception is structured around objects which form the basis for our higher-level cognition and impressive systematic generalization abilities.
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text
The recent success of natural language understanding (NLU) systems has been troubled by results highlighting the failure of these models to generalize in a systematic and robust way.
A Benchmark for Systematic Generalization in Grounded Language Understanding
In this paper, we introduce a new benchmark, gSCAN, for evaluating compositional generalization in situated language understanding.
Prioritized Level Replay
facebookresearch/level-replay
•
•
Environments with procedurally generated content serve as important benchmarks for testing systematic generalization in deep reinforcement learning.
CLOSURE: Assessing Systematic Generalization of CLEVR Models
rizar/CLOSURE
•
•
In this work, we study how systematic the generalization of such models is, that is to which extent they are capable of handling novel combinations of known linguistic constructs.
The NetHack Learning Environment
Here, we present the NetHack Learning Environment (NLE), a scalable, procedurally generated, stochastic, rich, and challenging environment for RL research based on the popular single-player terminal-based roguelike game, NetHack.
Conditional Object-Centric Learning from Video
google-research/slot-attention-video
•
•
ICLR 2022
Object-centric representations are a promising path toward more systematic generalization by providing flexible abstractions upon which compositional world models can be built.
Systematic Generalization: What Is Required and Can It Be Learned?
rizar/systematic-generalization-sqoop
•
•
ICLR 2019
Numerous models for grounded language understanding have been recently proposed, including (i) generic models that can be easily adapted to any given task and (ii) intuitively appealing modular models that require background knowledge to be instantiated.
Revisit Systematic Generalization via Meaningful Learning
shininglab/systematic-generalization-via-meaningful-learning
•
•
Humans can systematically generalize to novel compositions of existing concepts.
Systematic Generalization on gSCAN with Language Conditioned Embedding
HQ01/gSCAN_with_language_conditioned_embedding
•
•
Asian Chapter of the Association for Computational Linguistics 2020
Systematic Generalization refers to a learning algorithm's ability to extrapolate learned behavior to unseen situations that are distinct but semantically similar to its training data.
