6 citations · 16 across the 16 of their papers we have counts for
18 papers · 1 filter
TACLer: Tailored Curriculum Reinforcement Learning for Efficient Reasoning
Huiyuan Lai, Malvina Nissim
Large Language Models (LLMs) have shown remarkable performance on complex reasoning tasks, especially when equipped with long chain-of-thought (CoT) reasoning. However, eliciting l…
OntoURL: A Benchmark for Evaluating Large Language Models on Symbolic Ontological Understanding, Reasoning and Learning
Xiao Zhang, Huiyuan Lai, Qianru Meng +1
Large language models have demonstrated remarkable capabilities across a wide range of tasks, yet their ability to process structured symbolic knowledge remains underexplored. To a…
Multidimensional Consistency Improves Reasoning in Language Models
Huiyuan Lai, Xiao Zhang, Malvina Nissim
While Large language models (LLMs) have proved able to address some complex reasoning tasks, we also know that they are highly sensitive to input variation, which can lead to diffe…
Multi-perspective Alignment for Increasing Naturalness in Neural Machine Translation
Huiyuan Lai, Esther Ploeger, Rik van Noord +1
Neural machine translation (NMT) systems amplify lexical biases present in their training data, leading to artificially impoverished language in output translations. These language…
Towards Tailored Recovery of Lexical Diversity in Literary Machine Translation
Esther Ploeger, Huiyuan Lai, Rik van Noord +1
Machine translations are found to be lexically poorer than human translations. The loss of lexical diversity through MT poses an issue in the automatic translation of literature, w…
mCoT: Multilingual Instruction Tuning for Reasoning Consistency in Language Models
Huiyuan Lai, Malvina Nissim
Large language models (LLMs) with Chain-of-thought (CoT) have recently emerged as a powerful technique for eliciting reasoning to improve various downstream tasks. As most research…