Systematic Generalization

56 papers with code • 0 benchmarks • 7 datasets

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Use these libraries to find Systematic Generalization models and implementations

Most implemented papers

Multi-Object Representation Learning with Iterative Variational Inference

deepmind/deepmind-research 1 Mar 2019

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

facebookresearch/clutrr IJCNLP 2019

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

LauraRuis/groundedSCAN NeurIPS 2020

In this paper, we introduce a new benchmark, gSCAN, for evaluating compositional generalization in situated language understanding.

Prioritized Level Replay

facebookresearch/level-replay 8 Oct 2020

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 12 Dec 2019

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

facebookresearch/nle NeurIPS 2020

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 14 Mar 2020

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.