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20182023
most citedXTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization

299 citations · 370 across the 20 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CL2023

Single Sequence Prediction over Reasoning Graphs for Multi-hop QA

Gowtham Ramesh, Makesh Sreedhar, Junjie Hu

Recent generative approaches for multi-hop question answering (QA) utilize the fusion-in-decoder method~\cite{izacard-grave-2021-leveraging} to generate a single sequence output wh…

cs.CV2023★ 2 cited

Multimodal Prompt Retrieval for Generative Visual Question Answering

Timothy Ossowski, Junjie Hu

Recent years have witnessed impressive results of pre-trained vision-language models on knowledge-intensive tasks such as visual question answering (VQA). Despite the recent advanc…

cs.CL2023★ 2 cited

Is Fine-tuning Needed? Pre-trained Language Models Are Near Perfect for Out-of-Domain Detection

Rheeya Uppaal, Junjie Hu, Yixuan Li

Out-of-distribution (OOD) detection is a critical task for reliable predictions over text. Fine-tuning with pre-trained language models has been a de facto procedure to derive OOD…

cs.CL2023★ 20 cited

Benchmarking Machine Translation with Cultural Awareness

Binwei Yao, Ming Jiang, Tara Bobinac +2

Translating culture-related content is vital for effective cross-cultural communication. However, many culture-specific items (CSIs) often lack viable translations across languages…

cs.CL2023★ 3 cited

Domain-adapted large language models for classifying nuclear medicine reports

Zachary Huemann, Changhee Lee, Junjie Hu +2

With the growing use of transformer-based language models in medicine, it is unclear how well these models generalize to nuclear medicine which has domain-specific vocabulary and u…