2 citations · 3 across the 4 of their papers we have counts for
4 papers
SIFT-50M: A Large-Scale Multilingual Dataset for Speech Instruction Fine-Tuning
Prabhat Pandey, Rupak Vignesh Swaminathan, K V Vijay Girish +4
We introduce SIFT (Speech Instruction Fine-Tuning), a 50M-example dataset designed for instruction fine-tuning and pre-training of speech-text large language models (LLMs). SIFT-50…
Retrieval for Extremely Long Queries and Documents with RPRS: a Highly Efficient and Effective Transformer-based Re-Ranker
Arian Askari, Suzan Verberne, Amin Abolghasemi +2
Retrieval with extremely long queries and documents is a well-known and challenging task in information retrieval and is commonly known as Query-by-Document (QBD) retrieval. Specif…
Injecting the BM25 Score as Text Improves BERT-Based Re-rankers
Arian Askari, Amin Abolghasemi, Gabriella Pasi +2
In this paper we propose a novel approach for combining first-stage lexical retrieval models and Transformer-based re-rankers: we inject the relevance score of the lexical model as…
Breaking BERT: Understanding its Vulnerabilities for Named Entity Recognition through Adversarial Attack
Anne Dirkson, Suzan Verberne, Wessel Kraaij
Both generic and domain-specific BERT models are widely used for natural language processing (NLP) tasks. In this paper we investigate the vulnerability of BERT models to variation…