knowledge boundary

Fine-Tuned LLMs Know They Don’t Know: A Parameter-Efficient Approach to Recovering Honesty AAAI 2026 KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality ACL 2026 Alignment for Efficient Tool Calling of Large Language Models EMNLP 2025 Analyzing LLMs’ Knowledge Boundary Cognition Across Languages Through the Lens of Internal Representations ACL 2025 Detecting Knowledge Boundary of Vision Large Language Models by Sampling-Based Inference EMNLP 2025 Divide-Then-Align: Honest Alignment based on the Knowledge Boundary of RAG ACL 2025 Do LVLMs Know What They Know? A Systematic Study of Knowledge Boundary Perception in LVLMs EMNLP 2025 Explore What LLM Does Not Know in Complex Question Answering AAAI 2025 Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation COLING 2025 KBM: Delineating Knowledge Boundary for Adaptive Retrieval in Large Language Models EMNLP 2025 Knowledge Boundary of Large Language Models: A Survey ACL 2025 Know the Unknown: An Uncertainty-Sensitive Method for LLM Instruction Tuning ACL 2025 MAC-Tuning: LLM Multi-Compositional Problem Reasoning with Enhanced Knowledge Boundary Awareness EMNLP 2025 MMBoundary: Advancing MLLM Knowledge Boundary Awareness through Reasoning Step Confidence Calibration ACL 2025 TailorRPA: A Retrieval-Based Framework for Eliciting Personalized and Coherent Role-Playing Agents in General Domain EMNLP 2025 Teaching Large Language Models to Express Knowledge Boundary from Their Own Signals ACL 2025 Thinking Out Loud: Do Reasoning Models Know When They’re Right? EMNLP 2025 Token Knowledge: A New Perspective For Knowledge in Large Language Models EMNLP 2025 Towards Fully Exploiting LLM Internal States to Enhance Knowledge Boundary Perception ACL 2025 Towards Reliable Large Audio Language Model ACL 2025 UAlign: Leveraging Uncertainty Estimations for Factuality Alignment on Large Language Models ACL 2025 Alignment for Honesty NeurIPS 2024 Benchmarking Knowledge Boundary for Large Language Models: A Different Perspective on Model Evaluation ACL 2024 Do Large Language Models Know How Much They Know? EMNLP 2024 Knowing What LLMs DO NOT Know: A Simple Yet Effective Self-Detection Method NAACL 2024