6 citations · 22 across the 17 of their papers we have counts for
19 papers
SarcasmMiner: A Dual-Track Post-Training Framework for Robust Audio-Visual Sarcasm Reasoning
Zhu Li, Yongjian Chen, Huiyuan Lai +3
Multimodal sarcasm detection requires resolving pragmatic incongruity across textual, acoustic, and visual cues through cross-modal reasoning. To enable robust sarcasm reasoning wi…
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…
Fine-tuning with HED-IT: The impact of human post-editing for dialogical language models
Daniela Occhipinti, Michele Marchi, Irene Mondella +4
Automatic methods for generating and gathering linguistic data have proven effective for fine-tuning Language Models (LMs) in languages less resourced than English. Still, while th…
Responsibility Perspective Transfer for Italian Femicide News
Gosse Minnema, Huiyuan Lai, Benedetta Muscato +1
Different ways of linguistically expressing the same real-world event can lead to different perceptions of what happened. Previous work has shown that different descriptions of gen…
Pre-Trained Language-Meaning Models for Multilingual Parsing and Generation
Chunliu Wang, Huiyuan Lai, Malvina Nissim +1
Pre-trained language models (PLMs) have achieved great success in NLP and have recently been used for tasks in computational semantics. However, these tasks do not fully benefit fr…
Multilingual Multi-Figurative Language Detection
Huiyuan Lai, Antonio Toral, Malvina Nissim
Figures of speech help people express abstract concepts and evoke stronger emotions than literal expressions, thereby making texts more creative and engaging. Due to its pervasive…
Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP
Anya Belz, Craig Thomson, Ehud Reiter +39
We report our efforts in identifying a set of previous human evaluations in NLP that would be suitable for a coordinated study examining what makes human evaluations in NLP more/le…
Multidimensional Evaluation for Text Style Transfer Using ChatGPT
Huiyuan Lai, Antonio Toral, Malvina Nissim
We investigate the potential of ChatGPT as a multidimensional evaluator for the task of \emph{Text Style Transfer}, alongside, and in comparison to, existing automatic metrics as w…
Multi-Figurative Language Generation
Huiyuan Lai, Malvina Nissim
Figurative language generation is the task of reformulating a given text in the desired figure of speech while still being faithful to the original context. We take the first step…
Human Judgement as a Compass to Navigate Automatic Metrics for Formality Transfer
Huiyuan Lai, Jiali Mao, Antonio Toral +1
Although text style transfer has witnessed rapid development in recent years, there is as yet no established standard for evaluation, which is performed using several automatic met…
Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer
Huiyuan Lai, Antonio Toral, Malvina Nissim
We exploit the pre-trained seq2seq model mBART for multilingual text style transfer. Using machine translated data as well as gold aligned English sentences yields state-of-the-art…
Generic resources are what you need: Style transfer tasks without task-specific parallel training data
Huiyuan Lai, Antonio Toral, Malvina Nissim
Style transfer aims to rewrite a source text in a different target style while preserving its content. We propose a novel approach to this task that leverages generic resources, an…
Thank you BART! Rewarding Pre-Trained Models Improves Formality Style Transfer
Huiyuan Lai, Antonio Toral, Malvina Nissim
Scarcity of parallel data causes formality style transfer models to have scarce success in preserving content. We show that fine-tuning pre-trained language (GPT-2) and sequence-to…
On the interaction of automatic evaluation and task framing in headline style transfer
Lorenzo De Mattei, Michele Cafagna, Huiyuan Lai +3
An ongoing debate in the NLG community concerns the best way to evaluate systems, with human evaluation often being considered the most reliable method, compared to corpus-based me…