Huang / Li / Chen | Advanced Intelligent Computing Technology and Applications | Buch | 978-981-950013-0 | www.sack.de

Buch, Englisch, 537 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 838 g

Reihe: Lecture Notes in Artificial Intelligence

Huang / Li / Chen

Advanced Intelligent Computing Technology and Applications

21st International Conference, ICIC 2025, Ningbo, China, July 26-29, 2025, Proceedings, Part XXIII
Erscheinungsjahr 2025
ISBN: 978-981-950013-0
Verlag: Springer

21st International Conference, ICIC 2025, Ningbo, China, July 26-29, 2025, Proceedings, Part XXIII

Buch, Englisch, 537 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 838 g

Reihe: Lecture Notes in Artificial Intelligence

ISBN: 978-981-950013-0
Verlag: Springer


The 20-volume set LNCS 15842-15861, together with the 4-volume set LNAI 15862-15865 and the 4-volume set LNBI 15866-15869, constitutes the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025.

The 1206 papers presented in these proceedings books were carefully reviewed and selected from 4032 submissions. They deal with emerging and challenging topics in artificial intelligence, machine learning, pattern recognition, bioinformatics, and computational biology. 

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Research

Weitere Infos & Material


.- Natural Language Processing and Computational Linguistics.
.- Can LLM be a Good Path Planner based on Prompt Engineering? Mitigating  the Hallucination for Path Planning.
.- ModalLogicBench: Unveiling Modal Logic Reasoning Abilities of Large  Language Models.
.- A Source Template-based Data Augmentation Method for Low-Resource  Neural Machine Translation.
.- Exploring Behavior-Driven Development for Code Generation.
.- LLM- Based Data Synthesis and Distillation for High-Quality Text-to-SQL  Training.
.- External Knowledge-Enhanced Semi-supervised Multi-Label Short Text  Classification.
.- Bridging Knowledge Gaps: Fine-Tuned RAG Frameworks for Biomedical  Evidence-Based Question Answering.
.- MTAOS: Aspect-Level Opinion Summarization with Opinion Phrase  Masking.
.- COMLoRA: A chain-based LoRA architecture combined with MoE.
.- Sentence Trunk Fusion for Neural Machine Translation.
.- ProCFD: Towards Robust Multimodal Sentiment Analysis through Prototype  Fusion and Contrastive Feature Decomposition.
.- T3: A Novel Zero-shot Transfer Learning Framework Iteratively Training on  an Assistant Task for a Target Task.
.- ALMP: Automatic Layer-by-layer Mixed-Precision Quantization For Large  Language Models.
.- Can we employ LLM to meta-evaluate LLM-based evaluators? A  Preliminary Study.
.- EmbSpeech: A Unified Framework Towards Low-Resource Zero-Shot  Speech Synthesis.
.- SViQA: A Unified Speech-Vision Multimodal Model for Textless Visual  Question Answering.
.- Event Causality Extraction via Label-Aware Multi-Prompt Generation  Network.
.- Improving Low-Resource Neural Machine Translation with Dependency  Distance-based Self-Attention.
.- Automated Coding Utterances toward Chinese Course Core Competence  with Large Language Models.
.- Introspective Reward Modeling via Inverse Reinforcement Learning for  LLM Alignment.
.- BERTFAN: Multi-Layer Feature Fusion and Data Augmentation for  Sentiment Analysis.
.- Instruction Tuning with Data Augmentation for Event Argument Extraction.
.- EQAA-MAC: Enhancing Question Answering Accuracy via Multi-Agent  Cooperation in IT Operations.
.- Cross-domain Constituency Parsing with Multi-LLM Debate.
.- Unified Option Generation for Zero- and Few-shot Emotion and Cause  Analysis in Dialogues.
.- Open-World Knowledge Augmentation for Zero-Shot Information  Extraction in LLMs.
.- Prompting Large Models for Knowledge and Reasoning Augmentation in  KB-VQA.
.- IterSelectTune: An Iterative Data Selection Framework for Efficient  Instruction Tuning.
.- Utilize unbiased contrastive learning to enhance the key emotional features  in low-resource sentiment analysis.
.- Post-training Performance Boosting Method for Code Large Language  Models via Model Merging.
.- Automated Construction of High-quality Evaluation Datasets Based on  LLMs.
.- Enhancing Code Generation for Large Language Models Using Fine-Grained Distillation.
.- Morphological Recombination-Based Neural Machine Translation with Self Supervised Data Augmentation.
.- From Coarse to Fine: Chinese Spelling Correction Based on LoRA  Technology and Multi-Agent Collaboration.
.- Using External knowledge to Enhanced PLM for Semantic Matching.
.- UnCert-CoT: Uncertainty-Aware Chain-of-Thought for Code Generation  with Large Language Model.
.- Towards Reliable Large Language Models: A Survey on Hallucination  Detection.
.- KPEE: A Two-Stage Proposal-Based Reformulation of Event Extraction.
.- Morphology-Driven Meta-Adapter for Low-Resource Mongolian Sentiment  Analysis.
.- Knowledge Graph Completion Combining Dynamic Learnability and  Contrastive Learning.
.- FlexKG: A Flexible Framework for Enhanced Reasoning over Knowledge  Graph with Large Language Model.
.- Enhancing Code Search Fine-Tuning with Momentum Contrastive Learning  and Cross-Modal Matching.
.- RECODE: Leveraging Reliable Self-Generated Tests and Fine-Grained  Execution Feedback to Enhance LLM-Based Code Generation.
.- Evidence-Augmented Generative Explanation for Health Rumor Detection.



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