Natural Language Processing and Information Systems : 29th International Conference on Applications of Natural Language to Information Systems, NLDB 2024, Turin, Italy, June 25–27, 2024, Proceedings, Part I / edited by Amon Rapp, Luigi Di Caro, Farid Meziane, Vijayan Sugumaran.

Format:

Book

Contributor:

Rapp, Amon, editor.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 14762

Language:

English

Subjects (All):

Computer engineering.

Computer networks.

Artificial intelligence.

Image processing--Digital techniques.

Image processing.

Computer vision.

Social sciences--Data processing.

Social sciences.

Computer Engineering and Networks.

Artificial Intelligence.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Computer Application in Social and Behavioral Sciences.

Local Subjects:

Computer Engineering and Networks.

Artificial Intelligence.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Computer Application in Social and Behavioral Sciences.

Physical Description:

1 online resource (552 pages)

Edition:

1st ed. 2024.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2024.

Summary:

The two-volume proceedings set LNCS 14762 and 14763 constitutes the refereed proceedings of the 29th International Conference on Applications of Natural Language to Information Systems, NLDB 2024, held in Turin, Italy, in June 25–27, 2024. The 35 full papers, 26 short papers, 3 demo papers and 8 industry track papers included in these books were carefully reviewed and selected from 141 submissions. They focus on advancements and support studies related to languages previously underrepresented, such as Arabic, Romanian, Italian and Japanese languages.

Contents:

Fine-Tuning BERT On Coarse-Grained Labels: Exploring Hidden States For Fine-Grained Classification

Studies on the Use of Large Language Models for the Automation of Business Processes in Enterprise Resource Planning Systems

Efficient Knowledge Distillation: Empowering Small Language Models with Teacher Model Insights

Text Role Classification in Scientific Charts Using Multimodal Transformers

LaFiCMIL: Rethinking Large File Classification from the Perspective of Correlated Multiple Instance Learning

Unveiling Depression on Social Media: Active Learning with Human-in-the-Loop Labeling for Mental Health Data Annotation and Analysis

All-words Pronunciation Estimation of Japanese Homographs Using Automatically Tagged Data

I’ve got the “Answer”! Interpretation of LLMs Hidden States in Question Answering

Improving DRS-to-Text Generation through Delexicalization and Data Augmentation

Large Language Models for Few-Shot Automatic Term Extraction

Data Augmentation Method Utilizing Template Sentences for Variable Definition Extraction

Semi-supervised Named Entity Recognition for Low-Resource Languages using Dual PLMs

Improved Models for Media Bias Detection and Subcategorization

Grounding Toxicity in Real-World Events across Languages.-Unveiling the Hate: Generating Faithful and Plausible Explanations for Implicit and Subtle Hate Speech Detection

The Influence of Iconicity in Transfer Learning for Sign Language Recognition

S3: A Simple Strong Sample-Effective Multimodal Dialog System

Body-Shaming Detection and Classification in Italian Social Media.-Adaptive Greedy Layer Pruning: Iterative Layer Pruning With Subsequent Model Repurposing

Toward Automatic Group Membership Annotation for Group Fairness Evaluation

REA: Refine-Estimate-Answer Prompting for Zero-Shot Relation Extraction

Enhancing Romanian Offensive Language Detection through Knowledge Distillation, Multi-Task Learning and Data Augmentation

Automating Gender-Inclusive Language Modification in Italian University Administrative Documents

An SoK of Relation Extraction Techniques in Cyber Threat Intelligence

Shact: Disentangling and Clustering Latent Syntactic Structures from Transformer Encoders

MaskPure: Improving Defense Against Text Adversaries with Stochastic Purification

SERIEMA: A Framework to Enhance Clustering Stability, Compactness, and Separation by Fusing Multimodal Data

Exploiting Graph Embeddings from Knowledge Bases for Neural Biomedical Relation Extraction

DAHRS: Divergence-Aware Hallucination-Remediated SRL Projection

EpidGPT: A Combined Strategy to Discriminate Between Redundant and New Information for Epidemiological Surveillance Systems

Towards Generating High-Quality Knowledge Graphs by Leveraging Large Language Models

DeepCodeGraph: A Language Model for Compile-Time Resource Optimization Using Masked Graph Autoencoders

Design and Implementation of a Natural Language Interface for Controlling the Web of Things Devices

IndEL: Indonesian Entity Linking Benchmark Dataset for General and Specific Domains

Semantic Multi-Concept Annotation for Tabular Data in Financial Documents.

ISBN:

3-031-70239-5