10 citations · 14 across the 10 of their papers we have counts for
10 papers
BiasBusters: Uncovering and Mitigating Tool Selection Bias in Large Language Models
Thierry Blankenstein, Jialin Yu, Zixuan Li +6
Agents backed by large language models (LLMs) increasingly rely on external tools drawn from marketplaces where multiple providers offer functionally equivalent options. This raise…
TraceDet: Hallucination Detection from the Decoding Trace of Diffusion Large Language Models
Shenxu Chang, Junchi Yu, Weixing Wang +4
Diffusion large language models (D-LLMs) have recently emerged as a promising alternative to auto-regressive LLMs (AR-LLMs). However, the hallucination problem in D-LLMs remains un…
Structured Learning of Compositional Sequential Interventions
Jialin Yu, Andreas Koukorinis, Nicolò Colombo +2
We consider sequential treatment regimes where each unit is exposed to combinations of interventions over time. When interventions are described by qualitative labels, such as "clo…
Intervention Generalization: A View from Factor Graph Models
Gecia Bravo-Hermsdorff, David S. Watson, Jialin Yu +2
One of the goals of causal inference is to generalize from past experiments and observational data to novel conditions. While it is in principle possible to eventually learn a mapp…
Language as a Latent Sequence: deep latent variable models for semi-supervised paraphrase generation
Jialin Yu, Alexandra I. Cristea, Anoushka Harit +4
This paper explores deep latent variable models for semi-supervised paraphrase generation, where the missing target pair for unlabelled data is modelled as a latent paraphrase sequ…
Religion and Spirituality on Social Media in the Aftermath of the Global Pandemic
Olanrewaju Tahir Aduragba, Alexandra I. Cristea, Pete Phillips +2
During the COVID-19 pandemic, the Church closed its physical doors for the first time in about 800 years, which is, arguably, a cataclysmic event. Other religions have found themse…
Multi-task Learning for Personal Health Mention Detection on Social Media
Olanrewaju Tahir Aduragba, Jialin Yu, Alexandra I. Cristea
Detecting personal health mentions on social media is essential to complement existing health surveillance systems. However, annotating data for detecting health mentions at a larg…
Incorporating Emotions into Health Mention Classification Task on Social Media
Olanrewaju Tahir Aduragba, Jialin Yu, Alexandra I. Cristea
The health mention classification (HMC) task is the process of identifying and classifying mentions of health-related concepts in text. This can be useful for identifying and track…
INTERACTION: A Generative XAI Framework for Natural Language Inference Explanations
Jialin Yu, Alexandra I. Cristea, Anoushka Harit +4
XAI with natural language processing aims to produce human-readable explanations as evidence for AI decision-making, which addresses explainability and transparency. However, from…
Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums
Jialin Yu, Laila Alrajhi, Anoushka Harit +3
Massive Open Online Courses (MOOCs) have become a popular choice for e-learning thanks to their great flexibility. However, due to large numbers of learners and their diverse backg…