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knowledge editing

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Showing 126–150 of 175 papers

TitleStatusHype
BMIKE-53: Investigating Cross-Lingual Knowledge Editing with In-Context Learning—0
Understanding Language Model Circuits through Knowledge Editing—0
How Well Can Knowledge Edit Methods Edit Perplexing Knowledge?—0
Multilingual Knowledge Editing with Language-Agnostic Factual NeuronsCode0
MC-MKE: A Fine-Grained Multimodal Knowledge Editing Benchmark Emphasizing Modality Consistency—0
Retrieval Meets Reasoning: Dynamic In-Context Editing for Long-Text Understanding—0
Adaptive Token Biaser: Knowledge Editing via Biasing Key Entities—0
MEMLA: Enhancing Multilingual Knowledge Editing with Neuron-Masked Low-Rank Adaptation—0
Breaking Boundaries: Investigating the Effects of Model Editing on Cross-linguistic Performance—0
RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuningCode0
Identifying Query-Relevant Neurons in Large Language Models for Long-Form TextsCode0
DIEKAE: Difference Injection for Efficient Knowledge Augmentation and Editing of Large Language ModelsCode0
Knowledge Editing in Language Models via Adapted Direct Preference Optimization—0
Time Sensitive Knowledge Editing through Efficient FinetuningCode0
Outdated Issue Aware Decoding for Reasoning Questions on Edited KnowledgeCode0
Editing the Mind of Giants: An In-Depth Exploration of Pitfalls of Knowledge Editing in Large Language ModelsCode0
Leveraging Logical Rules in Knowledge Editing: A Cherry on the Top—0
Large Language Model Bias Mitigation from the Perspective of Knowledge Editing—0
Detecting Edited Knowledge in Language Models—0
TAXI: Evaluating Categorical Knowledge Editing for Language ModelsCode0
DyKnow: Dynamically Verifying Time-Sensitive Factual Knowledge in LLMsCode0
MLaKE: Multilingual Knowledge Editing Benchmark for Large Language ModelsCode0
Multi-hop Question Answering under Temporal Knowledge Editing—0
Dialectical Alignment: Resolving the Tension of 3H and Security Threats of LLMs—0
Is Factuality Enhancement a Free Lunch For LLMs? Better Factuality Can Lead to Worse Context-Faithfulness—0
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