Description

Book Synopsis

.- 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.

Advanced Intelligent Computing Technology and Applications

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    A Paperback by De-Shuang Huang

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      View other formats and editions of Advanced Intelligent Computing Technology and Applications by De-Shuang Huang

      Publisher: Springer
      Publication Date: 20/08/2025
      ISBN13: 9789819500130, 978-9819500130
      ISBN10:
      Also in:
      Artificial intelligence (AI)

      Description

      Book Synopsis

      .- 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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