Papers with cross-lingual setting
Addressing Issues of Cross-Linguality in Open-Retrieval Question Answering Systems For Emergent Domains (2023.eacl-demo)
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| Challenge: | a lack of cross-lingual training data in emergent domains makes it difficult to train on emerging domains. |
| Approach: | They propose a cross-lingual open-retrieval question answering system for COVID-19 . their system adopts a corpus of scientific articles to ensure that retrieved documents are reliable. |
| Outcome: | The proposed system outperforms BM25 baselines in cross-lingual settings. |
PAXQA: Generating Cross-lingual Question Answering Examples at Training Scale (2023.findings-emnlp)
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| Challenge: | Existing question answering systems rely on large, high-quality training data. |
| Approach: | They propose a synthetic data generation method which decomposes cross-lingual QA into two stages . they apply a question generation model to the English side and annotation projection to translate both questions and answers. |
| Outcome: | The proposed method outperforms existing methods on cross-lingual QA datasets. |
Sõnajaht: Definition Embeddings and Semantic Search for Reverse Dictionary Creation (2024.starsem-1)
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| Challenge: | Existing systems that use exact term matching to find words are based on information retrieval. |
| Approach: | They propose to use pre-trained language models and approximate nearest neighbors search algorithms to enhance and enrich an Estonian lexicon resource by introducing cross-lingual reverse dictionary functionality powered by semantic search. |
| Outcome: | The proposed system produces a 1 and 2 routs in the monolingual and cross-lingual settings using the unlabeled evaluation approach. |
Does Typological Blinding Impede Cross-Lingual Sharing? (2021.eacl-main)
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| Challenge: | Existing work on bridging the performance gap between high- and low-resource languages has only found minor benefits from using typological information. |
| Approach: | They propose to use typological features to train models in a cross-lingual setting to learn latent weights between languages. |
| Outcome: | The proposed model overshadows the utility of explicitly using typological features by ignoring them, and shows that encouraging sharing according to typology improves performance. |
Translate and Label! An Encoder-Decoder Approach for Cross-lingual Semantic Role Labeling (D19-1)
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| Challenge: | Unlike annotation projection techniques, our model does not need parallel data during inference time. |
| Approach: | They propose a cross-lingual Encoder-Decoder model that simultaneously translates and generates sentences with semantic role annotations in a resource-poor target language. |
| Outcome: | The proposed model can be applied in monolingual, multilingual and cross-lingual settings and produces dependency-based and span-based annotations. |
Zero-Shot Cross-Lingual Reranking with Large Language Models for Low-Resource Languages (2024.acl-short)
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| Challenge: | Large language models (LLMs) have shown impressive zero-shot capabilities in various passage ranking tasks. |
| Approach: | They analyze and compare the effectiveness of monolingual reranking using query or document translations and evaluate the effectiveness when leveraging their own generated translations. |
| Outcome: | The proposed models perform better when using their own translations than when using query or document translations. |
Our kind of people? Detecting populist references in political debates (2023.findings-eacl)
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| Challenge: | Existing literature on populism has only limited agreement on its exact properties . |
| Approach: | They propose a cross-lingual dataset to identify populist rhetoric in text . they propose 'hierarchical' annotation procedure to annotate populist references . |
| Outcome: | The proposed dataset can be used to investigate how political actors talk about The Elite and The People and to study how populist rhetoric is used as a strategic device. |
Strong Baselines for Complex Word Identification across Multiple Languages (N19-1)
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Pierre Finnimore, Elisabeth Fritzsch, Daniel King, Alison Sneyd, Aneeq Ur Rehman, Fernando Alva-Manchego, Andreas Vlachos
| Challenge: | Complex Word Identification (CWI) is the task of identifying which words or phrases in a sentence are difficult to understand by a specific type of reader. |
| Approach: | They propose to use monolingual and cross-lingual CWI models to make predictions for languages not seen during training. |
| Outcome: | The proposed models perform as well as (or better than) most models submitted to the latest CWI Shared Task. |
ConSeC: Word Sense Disambiguation as Continuous Sense Comprehension (2021.emnlp-main)
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| Challenge: | Existing systems for word Sense Disambiguation assume that each word can be disambiguated individually . a novel approach to WSD is proposed to address this limitation . |
| Approach: | They propose a supervised semantics-based approach to Word Sense Disambiguation that takes into account the senses assigned to nearby words. |
| Outcome: | The proposed approach surpasses all its competitors and sets a new state of the art on English WSD. |
Unsupervised Cross-Lingual Transfer of Structured Predictors without Source Data (2022.naacl-main)
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| Challenge: | Recent successes of NLP systems require large amounts of labelled data for structured prediction tasks. |
| Approach: | They propose a method for unsupervised transfer from multiple input models for structured prediction using a cross-lingual setup. |
| Outcome: | The proposed method produces less noisy labels for the distant supervision. |
XL-AMR: Enabling Cross-Lingual AMR Parsing with Transfer Learning Techniques (2020.emnlp-main)
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| Challenge: | Abstract Meaning Representation (AMR) is a popular formalism of natural language. |
| Approach: | They develop a cross-lingual AMR parser that can be trained on the produced data . they use transfer learning techniques to produce automatic AMR annotations across languages . |
| Outcome: | The proposed parser significantly surpasses those reported in Chinese, German, Italian and Spanish. |
Empowering Dual-Encoder with Query Generator for Cross-Lingual Dense Retrieval (2022.emnlp-main)
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| Challenge: | Existing methods to distill knowledge from cross-encoder re-ranker to dual-encoding retriever are lacking in the cross-lingual setting. |
| Approach: | They propose to use a query generator as the teacher in the cross-lingual setting to distill knowledge to a dual-encoder retrieval model. |
| Outcome: | The proposed method outperforms state-of-the-art methods on two benchmark datasets. |
Constrained Regeneration for Cross-Lingual Query-Focused Extractive Summarization (2022.coling-1)
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Elsbeth Turcan, David Wan, Faisal Ladhak, Petra Galuscakova, Sukanta Sen, Svetlana Tchistiakova, Weijia Xu, Marine Carpuat, Kenneth Heafield, Douglas Oard, Kathleen McKeown
| Challenge: | Query-focused summarization of foreign-language documents can help a user understand whether a document is relevant to a query term. |
| Approach: | They propose to use machine translation and post-editing to improve human relevance judgments . they include a query term in a summary when its translation appears in the source document . |
| Outcome: | The proposed approach improves human relevance judgments by including a query term in a summary when its translation appears in the source document. |
A Deep Transfer Learning Method for Cross-Lingual Natural Language Inference (2022.lrec-1)
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| Challenge: | Natural Language Inference (NLI) is a crucial task in AI and natural language processing. |
| Approach: | They propose an effective transfer learning approach for cross-lingual NLI . they perform experiments on English-Hindi language pairs in cross-linguistic setting . |
| Outcome: | The proposed model improves the baseline model by 10% over the state-of-the-art model. |
Multilingual LLMs are Better Cross-lingual In-context Learners with Alignment (2023.acl-long)
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| Challenge: | a handful of studies have explored ICL in a cross-lingual setting . emergence of large-scale, pretrained, Transformer-based language models has marked the commencement of an avant-garde era in NLP. |
| Approach: | They propose a novel prompt construction strategy to bridge the gap between ICL and cross-lingual text classification. |
| Outcome: | The proposed approach outperforms random prompt selection by a large margin across three tasks using 44 different cross-lingual pairs. |
Does Meta-learning Help mBERT for Few-shot Question Generation in a Cross-lingual Transfer Setting for Indic Languages? (2022.coling-1)
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Aniruddha Roy, Rupak Kumar Thakur, Isha Sharma, Ashim Gupta, Amrith Krishna, Sudeshna Sarkar, Pawan Goyal
| Challenge: | Existing approaches to few-shot Question Generation (QG) are limited and require manual annotation. |
| Approach: | They propose to use multilingual BERT to perform few-shot question generation with cross-lingual transfer. |
| Outcome: | The proposed model improves in few-shot QG and human evaluation confirms it. |
Measuring Cross-lingual Transfer in Bytes (2024.naacl-long)
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| Challenge: | Multilingual pretraining models can transfer knowledge to target languages with minimal or no examples . underlying mechanisms for this transfer remain unclear, with hypotheses ranging from language contamination to syntactic similarity. |
| Approach: | They conducted an experiment to investigate whether multilingual models transfer knowledge to target languages . they found that models initialized from diverse languages perform similarly to a target language . |
| Outcome: | a new study shows that models initialized from diverse languages perform similarly to a target language in a cross-lingual setting. |
Event Extraction in Basque: Typologically Motivated Cross-Lingual Transfer-Learning Analysis (2024.lrec-main)
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| Challenge: | Using a multilingual language model, Event Extraction tasks require humans to follow complicated guidelines and follow complicated rules. |
| Approach: | They propose a multilingual multilingual language model that is trained in a source language and applied to a target language. |
| Outcome: | The proposed model is based on a multilingual event extraction dataset for Basque . it shows that the shared linguistic characteristic between source and target languages does have an impact on transfer quality. |
Deep Exploration of Cross-Lingual Zero-Shot Generalization in Instruction Tuning (2024.findings-acl)
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| Challenge: | Recent studies have focused on instruction tuning to show cross-lingual generalization . a novel non-English meta-dataset is used to study instruction tuning . |
| Approach: | They perform instruction tuning individually for two distinct language meta-datasets and assess the performance on unseen tasks in a non-English language. |
| Outcome: | The proposed model outperforms baseline training in English and Korean by 20.7% and 13.6%. |
Definition Generation for Word Meaning Modeling: Monolingual, Multilingual, and Cross-Lingual Perspectives (2025.emnlp-main)
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| Challenge: | Recent advances in text generation have opened up new opportunities for word meaning modeling. |
| Approach: | They extend definition generation task beyond English to a suite of 22 languages . they use Llama-based models to evaluate models in monolingual, multilingual, cross-lingual settings . |
| Outcome: | The proposed model outperforms pretrained models in monolingual, multilingual, and cross-lingual settings. |
LLMs are Brittle to Simple Code Transformations: Introducing CETBench – A Benchmark for Code-Equivalence Checking (2026.findings-acl)
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| Challenge: | a new benchmarking tool for code equivalence checks the performance of LLMs. |
| Approach: | They propose a code-equivalence with transformations benchmark built from a repository of programs that may solve the same or different tasks. |
| Outcome: | The proposed approach boosts performance on the transformed pairs of programs. |