5 papers · 1 filter
Generalizing From Short to Long: Effective Data Synthesis for Long-Context Instruction Tuning
Wenhao Zhu, Pinzhen Chen, Hanxu Hu +4
Long-context modelling for large language models (LLMs) has been a key area of recent research because many real world use cases require reasoning over longer inputs such as docume…
Context and System Fusion in Post-ASR Emotion Recognition with Large Language Models
Pavel Stepachev, Pinzhen Chen, Barry Haddow
Large language models (LLMs) have started to play a vital role in modelling speech and text. To explore the best use of context and multiple systems' outputs for post-ASR speech em…
Pitfalls and Outlooks in Using COMET
Vilém Zouhar, Pinzhen Chen, Tsz Kin Lam +2
The COMET metric has blazed a trail in the machine translation community, given its strong correlation with human judgements of translation quality. Its success stems from being a…
The University of Edinburgh's Submission to the WMT22 Code-Mixing Shared Task (MixMT)
Faheem Kirefu, Vivek Iyer, Pinzhen Chen +1
The University of Edinburgh participated in the WMT22 shared task on code-mixed translation. This consists of two subtasks: i) generating code-mixed Hindi/English (Hinglish) text g…
The Highs and Lows of Simple Lexical Domain Adaptation Approaches for Neural Machine Translation
Nikolay Bogoychev, Pinzhen Chen
Machine translation systems are vulnerable to domain mismatch, especially in a low-resource scenario. Out-of-domain translations are often of poor quality and prone to hallucinatio…