Advanced Intelligent Computing Technology and Applications

.- 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.