question answering

RAGthoven: A Configurable Toolkit for RAG-enabled LLM Experimentation COLING 2025 RAMQA: A Unified Framework for Retrieval-Augmented Multi-Modal Question Answering NAACL 2025 RA-MTR: A Retrieval Augmented Multi-Task Reader based Approach for Inspirational Quote Extraction from Long Documents COLING 2025 RAP: A Metric for Balancing Repetition and Performance in Open-Source Large Language Models NAACL 2025 RASPberry: Retrieval-Augmented Monte Carlo Tree Self-Play with Reasoning Consistency for Multi-Hop Question Answering ACL 2025 RASTeR: Robust, Agentic, and Structured Temporal Reasoning IJCNLP 2025 Read Your Own Mind: Reasoning Helps Surface Self-Confidence Signals in LLMs EMNLP 2025 Reasoning Enhanced Missing Knowledge Retrieval Augmented Generation Framework for Domain Specific Question Answering IJCNLP 2025 Reasoning of Large Language Models over Knowledge Graphs with Super-Relations ICLR 2025 Reasoning over Uncertain Text by Generative Large Language Models AAAI 2025 Reasoning with Trees: Faithful Question Answering over Knowledge Graph COLING 2025 ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning EMNLP 2025 Recon, Answer, Verify: Agents in Search of Truth EMNLP 2025 Recursive Question Understanding for Complex Question Answering over Heterogeneous Personal Data ACL 2025 Reference-Guided Verdict: LLMs-as-Judges in Automatic Evaluation of Free-Form QA EMNLP 2025 REFIND at SemEval-2025 Task 3: Retrieval-Augmented Factuality Hallucination Detection in Large Language Models SemEval 2025 Refining Attention for Explainable and Noise-Robust Fact-Checking with Transformers EMNLP 2025 Reflection on Knowledge Graph for Large Language Models Reasoning ACL 2025 REGULAR: A Framework for Relation-Guided Multi-Span Question Generation IJCNLP 2025 Regulatory Question-Answering using Generative AI COLING 2025 ReKG-MCTS: Reinforcing LLM Reasoning on Knowledge Graphs via Training-Free Monte Carlo Tree Search ACL 2025 ReproHum #0031-01: Reproducing the Human Evaluation of Readability from “It is AI’s Turn to Ask Humans a Question” ACL 2025 ReTAG: Retrieval-Enhanced, Topic-Augmented Graph-Based Global Sensemaking EMNLP 2025 Retrieval-Augmented Generation Meets Local Languages for Improved Drug Information Access and Comprehension. ACL 2025 Retrieving Support to Rank Answers in Open-Domain Question Answering EMNLP 2025