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Found 25 papers, 12 papers with code
It’s not Greek to mBERT: Inducing Word-Level Translations from Multilingual BERT
Recent works have demonstrated that multilingual BERT (mBERT) learns rich cross-lingual representations, that allow for transfer across languages.
MYTE: Morphology-Driven Byte Encoding for Better and Fairer Multilingual Language Modeling
A major consideration in multilingual language modeling is how to best represent languages with diverse vocabularies and scripts.
Breaking the Curse of Multilinguality with Cross-lingual Expert Language Models
Despite their popularity in non-English NLP, multilingual language models often underperform monolingual ones due to inter-language competition for model parameters.
Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmark
We introduce Universal NER (UNER), an open, community-driven project to develop gold-standard NER benchmarks in many languages.
Ranked #1 on
Named Entity Recognition (NER)
on UNER v1 (Danish)
That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context?
In experiments, we compare MT-specific models and language models for (i) their preference when given an ambiguous subsentence, (ii) their sensitivity to disambiguating context, and (iii) the performance disparity between figurative and literal source sentences.
BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer
Despite remarkable advancements in few-shot generalization in natural language processing, most models are developed and evaluated primarily in English.
Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models
Language models have graduated from being research prototypes to commercialized products offered as web APIs, and recent works have highlighted the multilingual capabilities of these products.
Dictionary-based Phrase-level Prompting of Large Language Models for Machine Translation
Large language models (LLMs) demonstrate remarkable machine translation (MT) abilities via prompting, even though they were not explicitly trained for this task.
XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models
Large multilingual language models typically rely on a single vocabulary shared across 100+ languages.
Toward Human Readable Prompt Tuning: Kubrick's The Shining is a good movie, and a good prompt too?
Large language models can perform new tasks in a zero-shot fashion, given natural language prompts that specify the desired behavior.
Demystifying Prompts in Language Models via Perplexity Estimation
Language models can be prompted to perform a wide variety of zero- and few-shot learning problems.
Prompting Language Models for Linguistic Structure
Although pretrained language models (PLMs) can be prompted to perform a wide range of language tasks, it remains an open question how much this ability comes from generalizable linguistic understanding versus surface-level lexical patterns.
Analyzing the Mono- and Cross-Lingual Pretraining Dynamics of Multilingual Language Models
The emergent cross-lingual transfer seen in multilingual pretrained models has sparked significant interest in studying their behavior.
Analyzing Gender Representation in Multilingual Models
Multilingual language models were shown to allow for nontrivial transfer across scripts and languages.
Simple, Interpretable and Stable Method for Detecting Words with Usage Change across Corpora
The problem of comparing two bodies of text and searching for words that differ in their usage between them arises often in digital humanities and computational social science.
Identifying Helpful Sentences in Product Reviews
This task is closely related to the task of Multi Document Summarization in the product reviews domain but differs in its objective and its level of conciseness.
Pick a Fight or Bite your Tongue: Investigation of Gender Differences in Idiomatic Language Usage
A large body of research on gender-linked language has established foundations regarding cross-gender differences in lexical, emotional, and topical preferences, along with their sociological underpinnings.
It's not Greek to mBERT: Inducing Word-Level Translations from Multilingual BERT
Recent works have demonstrated that multilingual BERT (mBERT) learns rich cross-lingual representations, that allow for transfer across languages.
Automatically Identifying Gender Issues in Machine Translation using Perturbations
The successful application of neural methods to machine translation has realized huge quality advances for the community.
Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection
The ability to control for the kinds of information encoded in neural representation has a variety of use cases, especially in light of the challenge of interpreting these models.
How does Grammatical Gender Affect Noun Representations in Gender-Marking Languages?
Many natural languages assign grammatical gender also to inanimate nouns in the language.
It's All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitution
An alternative approach is Counterfactual Data Augmentation (CDA), in which a corpus is duplicated and augmented to remove bias, e. g. by swapping all inherently-gendered words in the copy.
Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
Word embeddings are widely used in NLP for a vast range of tasks.
Language Modeling for Code-Switching: Evaluation, Integration of Monolingual Data, and Discriminative Training
We focus on the problem of language modeling for code-switched language, in the context of automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Semi Supervised Preposition-Sense Disambiguation using Multilingual Data
Prepositions are very common and very ambiguous, and understanding their sense is critical for understanding the meaning of the sentence.
