Zero-shot Generalization

164 papers with code • 1 benchmarks • 1 datasets

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Datasets


Most implemented papers

Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks

brendenlake/SCAN ICML 2018

Humans can understand and produce new utterances effortlessly, thanks to their compositional skills.

Multitask Prompted Training Enables Zero-Shot Task Generalization

bigscience-workshop/promptsource ICLR 2022

Large language models have recently been shown to attain reasonable zero-shot generalization on a diverse set of tasks (Brown et al., 2020).

Learning Transferable Cooperative Behavior in Multi-Agent Teams

sumitsk/matrl 4 Jun 2019

While multi-agent interactions can be naturally modeled as a graph, the environment has traditionally been considered as a black box.

Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset

google-research-datasets/dstc8-schema-guided-dialogue 12 Sep 2019

In this work, we introduce the the Schema-Guided Dialogue (SGD) dataset, containing over 16k multi-domain conversations spanning 16 domains.

Learning the Travelling Salesperson Problem Requires Rethinking Generalization

chaitjo/learning-tsp 12 Jun 2020

End-to-end training of neural network solvers for graph combinatorial optimization problems such as the Travelling Salesperson Problem (TSP) have seen a surge of interest recently, but remain intractable and inefficient beyond graphs with few hundreds of nodes.

Convolutional Conditional Neural Processes

cambridge-mlg/convcnp ICLR 2020

We introduce the Convolutional Conditional Neural Process (ConvCNP), a new member of the Neural Process family that models translation equivariance in the data.

Compositional Generalization with Tree Stack Memory Units

ForoughA/recursiveMemNet 5 Nov 2019

We study compositional generalization, viz., the problem of zero-shot generalization to novel compositions of concepts in a domain.

The Scattering Compositional Learner: Discovering Objects, Attributes, Relationships in Analogical Reasoning

dhh1995/SCL 8 Jul 2020

In this work, we focus on an analogical reasoning task that contains rich compositional structures, Raven's Progressive Matrices (RPM).

From Images to Textual Prompts: Zero-shot VQA with Frozen Large Language Models

salesforce/lavis 21 Dec 2022

To address this issue, we propose \emph{Img2Prompt}, a plug-and-play module that provides the prompts that can bridge the aforementioned modality and task disconnections, so that LLMs can perform zero-shot VQA tasks without end-to-end training.

ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth

isl-org/ZoeDepth 23 Feb 2023

Finally, ZoeD-M12-NK is the first model that can jointly train on multiple datasets (NYU Depth v2 and KITTI) without a significant drop in performance and achieve unprecedented zero-shot generalization performance to eight unseen datasets from both indoor and outdoor domains.