17 citations · 61 across the 15 of their papers we have counts for
17 papers
Through the LLM Looking Glass: A Socratic Probing of Donkeys, Elephants, and Markets
Molly Kennedy, Ayyoob Imani, Timo Spinde +2
Large Language Models (LLMs) are widely used for text generation, making it crucial to address potential bias. This study investigates ideological framing bias in LLM-generated art…
DeltaLLM: Compress LLMs with Low-Rank Deltas between Shared Weights
Liana Mikaelyan, Ayyoob Imani, Mathew Salvaris +2
We introduce DeltaLLM, a new post-training compression technique to reduce the memory footprint of LLMs. We propose an alternative way of structuring LLMs with weight sharing betwe…
MURI: High-Quality Instruction Tuning Datasets for Low-Resource Languages via Reverse Instructions
Abdullatif Köksal, Marion Thaler, Ayyoob Imani +3
Instruction tuning enhances large language models (LLMs) by aligning them with human preferences across diverse tasks. Traditional approaches to create instruction tuning datasets…
How Transliterations Improve Crosslingual Alignment
Yihong Liu, Mingyang Wang, Amir Hossein Kargaran +6
Recent studies have shown that post-aligning multilingual pretrained language models (mPLMs) using alignment objectives on both original and transliterated data can improve crossli…
MemLLM: Finetuning LLMs to Use An Explicit Read-Write Memory
Ali Modarressi, Abdullatif Köksal, Ayyoob Imani +2
While current large language models (LLMs) perform well on many knowledge-related tasks, they are limited by relying on their parameters as an implicit storage mechanism. As a resu…
GlotLID: Language Identification for Low-Resource Languages
Amir Hossein Kargaran, Ayyoob Imani, François Yvon +1
Several recent papers have published good solutions for language identification (LID) for about 300 high-resource and medium-resource languages. However, there is no LID available…
Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages
Ayyoob Imani, Peiqin Lin, Amir Hossein Kargaran +8
The NLP community has mainly focused on scaling Large Language Models (LLMs) vertically, i.e., making them better for about 100 languages. We instead scale LLMs horizontally: we cr…
RET-LLM: Towards a General Read-Write Memory for Large Language Models
Ali Modarressi, Ayyoob Imani, Mohsen Fayyaz +1
Large language models (LLMs) have significantly advanced the field of natural language processing (NLP) through their extensive parameters and comprehensive data utilization. Howev…
Taxi1500: A Multilingual Dataset for Text Classification in 1500 Languages
Chunlan Ma, Ayyoob ImaniGooghari, Haotian Ye +3
While natural language processing tools have been developed extensively for some of the world's languages, a significant portion of the world's over 7000 languages are still neglec…
Graph-Based Multilingual Label Propagation for Low-Resource Part-of-Speech Tagging
Ayyoob Imani, Silvia Severini, Masoud Jalili Sabet +2
Part-of-Speech (POS) tagging is an important component of the NLP pipeline, but many low-resource languages lack labeled data for training. An established method for training a POS…
-DARTS: Mitigating Performance Collapse by Harmonizing Operation Selection among Cells
Sajad Movahedi, Melika Adabinejad, Ayyoob Imani +4
Differentiable neural architecture search (DARTS) is a popular method for neural architecture search (NAS), which performs cell-search and utilizes continuous relaxation to improve…
Graph Neural Networks for Multiparallel Word Alignment
Ayyoob Imani, Lütfi Kerem Şenel, Masoud Jalili Sabet +2
After a period of decrease, interest in word alignments is increasing again for their usefulness in domains such as typological research, cross-lingual annotation projection, and m…
Towards a Broad Coverage Named Entity Resource: A Data-Efficient Approach for Many Diverse Languages
Silvia Severini, Ayyoob Imani, Philipp Dufter +1
Parallel corpora are ideal for extracting a multilingual named entity (MNE) resource, i.e., a dataset of names translated into multiple languages. Prior work on extracting MNE data…
Graph Algorithms for Multiparallel Word Alignment
Ayyoob Imani, Masoud Jalili Sabet, Lütfi Kerem Şenel +3
With the advent of end-to-end deep learning approaches in machine translation, interest in word alignments initially decreased; however, they have again become a focus of research…
ParCourE: A Parallel Corpus Explorer for a Massively Multilingual Corpus
Ayyoob Imani, Masoud Jalili Sabet, Philipp Dufter +2
With more than 7000 languages worldwide, multilingual natural language processing (NLP) is essential both from an academic and commercial perspective. Researching typological prope…
An Axiomatic Study of Query Terms Order in Ad-hoc Retrieval
Ayyoob Imani, Amir Vakili, Ali Montazer +1
Classic retrieval methods use simple bag-of-word representations for queries and documents. This representation fails to capture the full semantic richness of queries and documents…
Deep Neural Networks for Query Expansion using Word Embeddings
Ayyoob Imani, Amir Vakili, Ali Montazer +1
Query expansion is a method for alleviating the vocabulary mismatch problem present in information retrieval tasks. Previous works have shown that terms selected for query expansio…