mitjanikolaus Goto Github PK

a-pytorch-tutorial-to-image-captioning

Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning

amdtk

arctic-captions

awesome-compositionality

A list of resources dedicated to compositionality

awesome-image-captioning

A curated list of image captioning and related area resources. :-)

childes-communicative-feedback

Code for Communicative Feedback corpus analyses on CHILDES. Work published at CogSci 2022 and 2023.

childes-grammaticality

childes-speech-acts

childespy

childesr

R interface to childes-db

clip2brain

Code from paper "Natural language supervision with a large and diverse dataset builds better models of human high-level visual cortex"

coco-caption

compositional-image-captioning

Code for the CoNLL 2019 paper "Compositional Generalization in Image Captioning" by Mitja Nikolaus, Mostafa Abdou, Matthew Lamm, Rahul Aralikatte and Desmond Elliott

cpc_audio

An implementation of the Contrast Predictive Coding (CPC) method to train audio features in an unsupervised fashion.

cross-situational-learning-abstract-scenes

Code for the CMCL 2021 paper "Evaluating the Acquisition of Semantic Knowledge from Cross-situational Learning in Artificial Neural Networks" by Mitja Nikolaus and Abdellah Fourtassi

django-frontend

Django Frontend is a collection of static files and templates to jumpstart Django front-end development.

egg

EGG: Emergence of lanGuage in Games

emergent_communication

Code for the ICLR 2024 paper Emergent Communication with Conversational Repair by Mitja Nikolaus.

evaluation-pipeline

Evaluation pipeline for the BabyLM Challenge 2023.

ldr-template

Latex template for the journal "Language Development Research"

lis_internship_bc

machine-analysis

library to do analysis on machine

machine-tasks

Datasets for compositional learning

magicmethods

Guide to Python's magic methods

measurediversity

Measure the diversity of image descriptions, repository for our COLING 2018 paper.

multimodal-predicate-noun-dependencies

Code for the EMNLP 2022 paper "Do Vision-and-Language Transformers Learn Grounded Predicate-Noun Dependencies?" by Mitja Nikolaus, Emmanuelle Salin, Stephane Ayache, Abdellah Fourtassi, and Benoit Favre.

multimodal-predicate-noun-dependencies-data

multimodal_seq2seq_gscan

The multi-modal sequence to sequence baseline neural models used in the Grounded SCAN paper.

oscar

Oscar and VinVL

peppa