27 citations · 69 across the 20 of their papers we have counts for
5 papers · 1 filter
Evaluation of Attribution Bias in Generator-Aware Retrieval-Augmented Large Language Models
Amin Abolghasemi, Leif Azzopardi, Seyyed Hadi Hashemi +2
Attributing answers to source documents is an approach used to enhance the verifiability of a model's output in retrieval augmented generation (RAG). Prior work has mainly focused…
Measuring Bias in a Ranked List using Term-based Representations
Amin Abolghasemi, Leif Azzopardi, Arian Askari +2
In most recent studies, gender bias in document ranking is evaluated with the NFaiRR metric, which measures bias in a ranked list based on an aggregation over the unbiasedness scor…
CAUSE: Counterfactual Assessment of User Satisfaction Estimation in Task-Oriented Dialogue Systems
Amin Abolghasemi, Zhaochun Ren, Arian Askari +3
An important unexplored aspect in previous work on user satisfaction estimation for Task-Oriented Dialogue (TOD) systems is their evaluation in terms of robustness for the identifi…
Self-seeding and Multi-intent Self-instructing LLMs for Generating Intent-aware Information-Seeking dialogs
Arian Askari, Roxana Petcu, Chuan Meng +4
Identifying user intents in information-seeking dialogs is crucial for a system to meet user's information needs. Intent prediction (IP) is challenging and demands sufficient dialo…
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…