39 citations · 62 across the 18 of their papers we have counts for
20 papers
Embedding the Teacher: Distilling vLLM Preferences for Scalable Image Retrieval
Eric He, Akash Gupta, Adian Liusie +4
Text--image retrieval is necessary for applications such as product recommendation. Embedding-based approaches like CLIP enable efficient large-scale retrieval via vector similarit…
Finetuning LLMs for Comparative Assessment Tasks
Vatsal Raina, Adian Liusie, Mark Gales
Automated assessment in natural language generation is a challenging task. Instruction-tuned large language models (LLMs) have shown promise in reference-free evaluation, particula…
CrossCheckGPT: Universal Hallucination Ranking for Multimodal Foundation Models
Guangzhi Sun, Potsawee Manakul, Adian Liusie +4
Multimodal foundation models are prone to hallucination, generating outputs that either contradict the input or are not grounded by factual information. Given the diversity in arch…
Efficient LLM Comparative Assessment: a Product of Experts Framework for Pairwise Comparisons
Adian Liusie, Vatsal Raina, Yassir Fathullah +1
LLM-as-a-judge approaches are a practical and effective way of assessing a range of text tasks. However, when using pairwise comparisons to rank a set of candidates, the computatio…
WaterJudge: Quality-Detection Trade-off when Watermarking Large Language Models
Piotr Molenda, Adian Liusie, Mark J. F. Gales
Watermarking generative-AI systems, such as LLMs, has gained considerable interest, driven by their enhanced capabilities across a wide range of tasks. Although current approaches…
Teacher-Student Training for Debiasing: General Permutation Debiasing for Large Language Models
Adian Liusie, Yassir Fathullah, Mark J. F. Gales
Large Language Models (LLMs) have demonstrated impressive zero-shot capabilities and versatility in NLP tasks, however they sometimes fail to maintain crucial invariances for speci…