Papers by Dimitris Gkoumas

6 papers
Common European Language Data Space (2024.lrec-main)

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Challenge: the Common European Language Data Space (LDS) is an integral part of the EU data strategy, which aims at developing a single market for data.
Approach: the Common European Language Data Space (LDS) is an integral part of the EU data strategy . its decentralised technical infrastructure and governance scheme are currently being developed by the LDS project .
Outcome: the Common European Language Data Space (LDS) is an integral part of the EU data strategy, which aims at developing a single market for data.
Less for More: Enhanced Feedback-aligned Mixed LLMs for Molecule Caption Generation and Fine-Grained NLI Evaluation (2025.acl-long)

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Challenge: Recent trends have led to the use of multimodal models to learn molecular and linguistic representations, either in separate but coordinated spaces or in a common space.
Approach: They propose a novel atomic-level evaluation method leveraging off-the-shelf Natural Language Inference (NLI) models for use in the unseen chemical domain.
Outcome: The proposed method surpasses state-of-the-art models in the unseen chemical domain while relying on a granularity-based evaluation method.
Evaluation and Facilitation of Online Discussions in the LLM Era: A Survey (2025.emnlp-main)

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Challenge: Recent advances in LLMs enable artificial facilitation agents to not only moderate content, but also actively improve the quality of interactions.
Approach: They propose a taxonomy on discussion quality evaluation and a new taxonomies for intervention and facilitation strategies.
Outcome: The proposed methods synthesize ideas from Natural Language Processing (NLP) and Social Sciences to provide a taxonomy on discussion quality evaluation, and a roadmap of good practices and future research directions.
A Digital Language Coherence Marker for Monitoring Dementia (2023.emnlp-main)

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Challenge: Existing studies have shown that dementia is associated with thought disorders relating to inability to produce coherent communication.
Approach: They propose to capture language coherence as a human-interpretable digital marker for monitoring cognitive changes in people with dementia.
Outcome: The proposed model shows a significant difference between people with mild cognitive impairment, those with Alzheimer’s Disease and healthy controls and high association with clinical bio-markers.
Reformulating NLP tasks to Capture Longitudinal Manifestation of Language Disorders in People with Dementia. (2023.emnlp-main)

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Challenge: Dementia is associated with language disorders which impede communication.
Approach: They propose to use a pre-trained language model to automatically learn linguistic disorder patterns by forcing it to focus on reformulated natural language processing (NLP) tasks and associated linguistic patterns.
Outcome: The proposed communication marker outperforms existing linguistic approaches and shows external validity via significant correlation with clinical markers of behaviour.

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