6 citations · 10 across the 6 of their papers we have counts for
6 papers
Analyzing LLM Instruction Optimization for Tabular Fact Verification
Xiaotang Du, Giwon Hong, Wai-Chung Kwan +4
Instruction optimization provides a lightweight, model-agnostic approach to enhancing the reasoning performance of large language models (LLMs). This paper presents the first syste…
Enhancing Long Document Long Form Summarisation with Self-Planning
Xiaotang Du, Rohit Saxena, Laura Perez-Beltrachini +2
We introduce a novel approach for long context summarisation, highlight-guided generation, that leverages sentence-level information as a content plan to improve the traceability a…
Analysing the Residual Stream of Language Models Under Knowledge Conflicts
Yu Zhao, Xiaotang Du, Giwon Hong +6
Large language models (LLMs) can store a significant amount of factual knowledge in their parameters. However, their parametric knowledge may conflict with the information provided…
Steering Knowledge Selection Behaviours in LLMs via SAE-Based Representation Engineering
Yu Zhao, Alessio Devoto, Giwon Hong +6
Large language models (LLMs) can store a significant amount of factual knowledge in their parameters. However, their parametric knowledge may conflict with the information provided…
Are We Done with MMLU?
Aryo Pradipta Gema, Joshua Ong Jun Leang, Giwon Hong +13
Maybe not. We identify and analyse errors in the popular Massive Multitask Language Understanding (MMLU) benchmark. Even though MMLU is widely adopted, our analysis demonstrates nu…
The Hallucinations Leaderboard -- An Open Effort to Measure Hallucinations in Large Language Models
Giwon Hong, Aryo Pradipta Gema, Rohit Saxena +8
Large Language Models (LLMs) have transformed the Natural Language Processing (NLP) landscape with their remarkable ability to understand and generate human-like text. However, the…