Systematic Generalization

31 papers with code • 0 benchmarks • 4 datasets

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Greatest papers with code

Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks

google-research/google-research NeurIPS 2020

More practically, we evaluate these models on the task of learning to execute partial programs, as might arise if using the model as a heuristic function in program synthesis.

Code Completion Learning to Execute +2

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.

Representation Learning Systematic Generalization +2

Prioritized Level Replay

maximecb/gym-minigrid 8 Oct 2020

Environments with procedurally generated content serve as important benchmarks for testing systematic generalization in deep reinforcement learning.

Systematic Generalization

Systematic Generalization on gSCAN: What is Nearly Solved and What is Next?

google-research/language EMNLP 2021

We analyze the grounded SCAN (gSCAN) benchmark, which was recently proposed to study systematic generalization for grounded language understanding.

Language understanding Systematic Generalization

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.

NetHack Score Systematic Generalization

Measuring Systematic Generalization in Neural Proof Generation with Transformers

facebookresearch/clutrr NeurIPS 2020

We observe that models that are not trained to generate proofs are better at generalizing to problems based on longer proofs.

Automated Theorem Proving Systematic Generalization

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.

Inductive logic programming Language understanding +3

Structured Reordering for Modeling Latent Alignments in Sequence Transduction

berlino/tensor2struct-public NeurIPS 2021

Despite success in many domains, neural models struggle in settings where train and test examples are drawn from different distributions.

Machine Translation Semantic Parsing +2

Compositional Networks Enable Systematic Generalization for Grounded Language Understanding

LauraRuis/groundedSCAN Findings (EMNLP) 2021

Recent work has shown that while deep networks can mimic some human language abilities when presented with novel sentences, systematic variation uncovers the limitations in the language-understanding abilities of networks.

Language understanding Systematic Generalization

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.

Language understanding Systematic Generalization