SHIFT proposes gates for knowledge conflicts in RAG
Published on June 29, 2026, the paper presents an intervention in FFN activations to balance retrieved evidence and a model’s internal knowledge.
Source: SHIFT direciona ativações para mitigar conflitos de conhecimento em RAG (arxiv.org). Text prepared with AI from this source.
What happened and what to do
Published on June 29, 2026, the paper describes SHIFT, which adds learnable gates to FFN activations. The proposal aims to help language models balance retrieved context in RAG systems with parametric knowledge, especially when the two sources conflict.
A company can respond with tests that identify discrepancies between retrieved documents and model answers, alongside monitoring of source quality and output. Where appropriate, it can assess model interventions and compare their effects with improvements to retrieval, evidence prioritization, and response rules.
How the consultancy can help
Wendelmaques can diagnose how source conflicts affect your RAG system and scope an implementation for evaluation, monitoring, and adjustments to retrieval or the model, including ongoing operation.
Next step
Send a short description of your RAG case to receive a scoped proposal for diagnosis and implementation.
Let's assess your project
I reply with scope and a proposal.