Natural Language Processing

QuRating: Selecting High-Quality Data for Training Language Models ICML 2024 R2AG: Incorporating Retrieval Information into Retrieval Augmented Generation EMNLP 2024 R3-NL2GQL: A Model Coordination and Knowledge Graph Alignment Approach for NL2GQL EMNLP 2024 RA2FD: Distilling Faithfulness into Efficient Dialogue Systems EMNLP 2024 RAAMove: A Corpus for Analyzing Moves in Research Article Abstracts COLING 2024 RACAI at ClimateActivism 2024: Improving Detection of Hate Speech by Extending LLM Predictions with Handcrafted Features EACL 2024 RACER: An LLM-powered Methodology for Scalable Analysis of Semi-structured Mental Health Interviews EMNLP 2024 RAC: Retrieval-augmented Conversation Dataset for Open-domain Question Answering in Conversational Settings EMNLP 2024 RaDA: Retrieval-augmented Web Agent Planning with LLMs ACL 2024 RADCoT: Retrieval-Augmented Distillation to Specialization Models for Generating Chain-of-Thoughts in Query Expansion COLING 2024 RadGraph-XL: A Large-Scale Expert-Annotated Dataset for Entity and Relation Extraction from Radiology Reports ACL 2024 RA-DIT: Retrieval-Augmented Dual Instruction Tuning ICLR 2024 RaFe: Ranking Feedback Improves Query Rewriting for RAG EMNLP 2024 RAG4ITOps: A Supervised Fine-Tunable and Comprehensive RAG Framework for IT Operations and Maintenance EMNLP 2024 RAGAR, Your Falsehood Radar: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models EMNLP 2024 RAGAs: Automated Evaluation of Retrieval Augmented Generation EACL 2024 RAG-Driver: Generalisable Driving Explanations with Retrieval-Augmented In-Context Multi-Modal Large Language Model Learning RSS 2024 RAG-Fusion Based Information Retrieval for Fact-Checking EMNLP 2024 RAG-HAT: A Hallucination-Aware Tuning Pipeline for LLM in Retrieval-Augmented Generation EMNLP 2024 RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation EMNLP 2024 RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering EMNLP 2024 RAGs to Style: Personalizing LLMs with Style Embeddings EACL 2024 RAG-Studio: Towards In-Domain Adaptation of Retrieval Augmented Generation Through Self-Alignment EMNLP 2024 RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models ACL 2024 RAGViz: Diagnose and Visualize Retrieval-Augmented Generation EMNLP 2024