3 citations · 4 across the 5 of their papers we have counts for
8 papers · 1 filter
Liaozhai through the Looking-Glass: On Paratextual Explicitation of Culture-Bound Terms in Machine Translation
Sherrie Shen, Weixuan Wang, Alexandra Birch
The faithful transfer of contextually-embedded meaning continues to challenge contemporary machine translation (MT), particularly in the rendering of culture-bound terms--expressio…
Learning to Summarize by Learning to Quiz: Adversarial Agentic Collaboration for Long Document Summarization
Weixuan Wang, Minghao Wu, Barry Haddow +1
Long document summarization remains a significant challenge for current large language models (LLMs), as existing approaches commonly struggle with information loss, factual incons…
ExpertSteer: Intervening in LLMs through Expert Knowledge
Weixuan Wang, Minghao Wu, Barry Haddow +1
Large Language Models (LLMs) exhibit remarkable capabilities across various tasks, yet guiding them to follow desired behaviours during inference remains a significant challenge. A…
HBO: Hierarchical Balancing Optimization for Fine-Tuning Large Language Models
Weixuan Wang, Minghao Wu, Barry Haddow +1
Fine-tuning large language models (LLMs) on a mixture of diverse datasets poses challenges due to data imbalance and heterogeneity. Existing methods often address these issues acro…
The Bitter Lesson Learned from 2,000+ Multilingual Benchmarks
Minghao Wu, Weixuan Wang, Sinuo Liu +7
As large language models (LLMs) continue to advance in linguistic capabilities, robust multilingual evaluation has become essential for promoting equitable technological progress.…
Demystifying Multilingual Chain-of-Thought in Process Reward Modeling
Weixuan Wang, Minghao Wu, Barry Haddow +1
Large language models (LLMs) are designed to perform a wide range of tasks. To improve their ability to solve complex problems requiring multi-step reasoning, recent research lever…