11 citations · 15 across the 4 of their papers we have counts for
7 papers
GeMQuAD : Generating Multilingual Question Answering Datasets from Large Language Models using Few Shot Learning
Amani Namboori, Shivam Mangale, Andy Rosenbaum +1
The emergence of Large Language Models (LLMs) with capabilities like In-Context Learning (ICL) has ushered in new possibilities for data generation across various domains while min…
When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards
Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay +9
Large Language Model (LLM) leaderboards based on benchmark rankings are regularly used to guide practitioners in model selection. Often, the published leaderboard rankings are take…
Recipes for Sequential Pre-training of Multilingual Encoder and Seq2Seq Models
Saleh Soltan, Andy Rosenbaum, Tobias Falke +3
Pre-trained encoder-only and sequence-to-sequence (seq2seq) models each have advantages, however training both model types from scratch is computationally expensive. We explore rec…
CLASP: Few-Shot Cross-Lingual Data Augmentation for Semantic Parsing
Andy Rosenbaum, Saleh Soltan, Wael Hamza +3
A bottleneck to developing Semantic Parsing (SP) models is the need for a large volume of human-labeled training data. Given the complexity and cost of human annotation for SP, lab…
LINGUIST: Language Model Instruction Tuning to Generate Annotated Utterances for Intent Classification and Slot Tagging
Andy Rosenbaum, Saleh Soltan, Wael Hamza +2
We present LINGUIST, a method for generating annotated data for Intent Classification and Slot Tagging (IC+ST), via fine-tuning AlexaTM 5B, a 5-billion-parameter multilingual seque…
Don't Parse, Insert: Multilingual Semantic Parsing with Insertion Based Decoding
Qile Zhu, Haidar Khan, Saleh Soltan +2
Semantic parsing is one of the key components of natural language understanding systems. A successful parse transforms an input utterance to an action that is easily understood by…