TimeROME-DLM enables training-free knowledge editing in masked diffusion language models via temporal causal tracing and low-rank residual edit memory applied at inference time.
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ORE decouples semantic entanglement in LLM hidden states via orthogonal edit vectors and a gated non-linear head, improving batch knowledge editing performance including cross-lingual cases.
Reproducibility study confirms AlphaEdit on original setups but finds performance degrades at high edit counts, fails to generalize to newer models, and harms downstream tasks.
citing papers explorer
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TimeROME-DLM: Temporal Causal Tracing and Low-Rank Inference-Time Knowledge Editing for Masked Diffusion Language Models
TimeROME-DLM enables training-free knowledge editing in masked diffusion language models via temporal causal tracing and low-rank residual edit memory applied at inference time.
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Orthogonal Representation Editing: Decoupling Semantic Entanglement in Batch Knowledge Editing of LLMs
ORE decouples semantic entanglement in LLM hidden states via orthogonal edit vectors and a gated non-linear head, improving batch knowledge editing performance including cross-lingual cases.
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Reproducibility Study of "AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models"
Reproducibility study confirms AlphaEdit on original setups but finds performance degrades at high edit counts, fails to generalize to newer models, and harms downstream tasks.