cisnlp Goto Github PK
Name: Deep NLP @ CIS - LMU
Type: Organization
Bio: Deep Natural Language Processing Group at Center for Language and Information Processing, University of Munich (LMU)
Location: Munich, Germany
Blog: https://cis.lmu.de
Name: Deep NLP @ CIS - LMU
Type: Organization
Bio: Deep Natural Language Processing Group at Center for Language and Information Processing, University of Munich (LMU)
Location: Munich, Germany
Blog: https://cis.lmu.de
Literature overview: gender bias in natural language processing
Homepage of cisnlp
Crosslingual Transfer Learning for Low-Resource Languages Based on Multilingual Colexification Graphs
Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages -- ACL 2023
GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages -- under review
GlotLID: Language Identification with Support for More Than 2000 Labels -- EMNLP 2023
GlotScript: A Resource and Tool for Low Resource Writing System Identification -- LREC 2024
GlotSparse: Building Corpora in Under-Resourced Languages
Children StoryBooks for 180 langauges.
GlotWeb: Web Indexing for Low-Resource Languages -- under construction.
code for EMNLP graph align paper
MaskLID: Code-Switching Language Identification through Iterative Masking -- ACL 2024
mPLM-Sim: Better Cross-Lingual Similarity and Transfer in Multilingual Pretrained Language Models
A Framework aims to wisely initialize unseen subword embeddings in PLMs for efficient large-scale continued pretraining
ParCourE - Parallel Corpus Explorer
Code for paper "Neural Semi-Markov Conditional Random Fields for Robust Character-Based Part-of-Speech Tagging"
Obtain Word Alignments using Pretrained Language Models (e.g., mBERT)
TransliCo: A Contrastive Learning Framework to Address the Script Barrier in Multilingual Pretrained Language Models
Breaking the Script Barrier in Multilingual Pre-Trained Language Models with Transliteration-Based Post-Training Alignment
TransMI: A Framework to Create Strong Baselines from Multilingual Pretrained Language Models for Transliterated Data
XAMPLER: Learning to Retrieve Cross-Lingual In-Context Examples
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