Cabrio / Monteiro Natural Language Processing and Information Systems

31st International Conference on Applications of Natural Language to Information Systems, NLDB 2026, Trondheim, Norway, June 17–19, 2026, Proceedings
Erscheinungsjahr 2026
ISBN: 978-3-032-29532-3
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 350 Seiten

Reihe: Lecture Notes in Computer Science

This volume LNCS constitutes the proceedings of the 31st International Conference on Applications of Natural Language to Information Systems, NLDB 2026, held in , , .

The 22 full papers presented in this volume were carefully reviewed and selected from 46 submissions. The proceedings contain Generative and Large Language Models; Social Media and Web Data; AI safety and ethics; Efficient/Low-resource methods in NLP; Information Retrieval and Text Mining; Explainable AI; Interpretability and Models Analysis in NLP.

Zielgruppe

Research

Autoren/Hrsg.

Cabrio, Elena

Monteiro, Eric

Inhaltsverzeichnis

.- Generative and Large Language Models.

.-  Summarising Regulations: an Empirical Study of Long-Document Summarisation Methods 
under Extreme Compression.

.-  ThinknCheck: Grounded Claim Verif ication with Compact, Reasoning-Driven, and 
Interpretable Models.

.-  Secure Coding Unleashed: Boosting Productivity With On-Premise LLM-Powered IDE Plugins.

.- What Do Claim Verification Datasets Actually Test? A Reasoning Trace Analysis.

.-  Using Text Simplification in Norwegian News Summarization.

.-  Temporal Reframing as a Historical Reasoning Task for Large Language Model.

.- Social Media and Web Data.

.-  Ontology-Augmented Prompt Engineering for Aspect-Based Sentiment Classification.

.-  Consp2VecD: A Dataset based on Emotional Dynamics expressed by Reddit Conspiracy 
Groups for Information Disorder Analysis.

.-  Adaptive Filtering for Large Language Model.

.- AI safety and ethics.

.-  Bias Evaluation Across Domains.

.-  Mitigating Gender Bias in English to Romanian Machine Translation.

.-  Zoom In Disparities in Healthcare LLM Q&A.

.- Efficient/Low-resource methods in NLP.

.-  Tokenizations for Austronesian Language Models: study on languages in Indonesia 
Archipelago.

.-  Efficient Error-Type Transfer for Grammatical Error Detection via Embedding Alignment.

.- Towards Robust Uzbek Neural Dependency Parsing: Cross-Treebank Training.

.- Information Retrieval and Text Mining.

.-  Adapting GPT for Egyptian Arabic–English Code-Switched Sentiment Analysis through 
Prompting, Retrieval, and Sentiment-Guided Fine-Tuning.

.-  Evaluating Noisy Optimization in Finetuning LMs for Neural Ranking.

.-  Evaluating LLM-Generated Wikipedia Content: Political Topics in a French Setting.

.- Explainable AI.

.-  When Words Move Markets: Interpretable Behavioural and Robustness Analysis of LLMs for 
Financial Sentiment Reasoning via Local Perturbation Explanations.

.-  Attention-Pruned SHAP: Accelerating SHAP-Based Explainability with Attention-Guided 
Feature Pruning.

.- Temporal Structure in LLM Reasoning:Analyzing Hidden States and Semantic Embeddings.

.- Interpretability and Models Analysis in NLP.

.- Expansion Is Not Enough: Revisiting Dynamically Expandable Networks for NLP Tasks.

.-  Automated ICD-10 Coding Approaches with UMLS Integration and Model Interpretability 
Support.