arXiv Machine Learning
4d ago

KV-Cache Patching: Tracing How and Where Fine-Tuned Behaviors Arise

The paper investigates where fine‑tuned behaviors in language models are instantiated by patching the key‑value (KV) cache between a LoRA‑fine‑tuned model and its base version. Results show that certain behaviors, such as German responses or emergent misalignment, can be transferred or removed by swapping KV cache segments, and that the impact grows with the amount patched and is concentrated at a few pivotal positions like system‑prompt and chat‑template tokens.

By Jonas Loos, Oliver Eberle
arXiv Computer Vision
4d ago

Hidden Commitment: When Language Models Silently Pick a Side and How Steering Can Surface It

The paper investigates whether language models truly reveal their internal decision process when faced with conflicting evidence. In a conflicting‑context question‑answering task, the authors find that models can silently commit to one source, a hidden source commitment that can be detected via a residual source‑choice direction. They show that steering this direction can change the chosen source, while conflict disclosure behaves differently and is only partially steerable.

By Samuel Dawit Assefa, Jae Won Cho
arXiv Computation and Language
2d ago

Cross-Prompt Reuse of Entity-Replacement Responses

The paper investigates how entity‑replacement responses can be reused across different English factual questions when model weights are fixed. By injecting hidden‑state changes from two source questions into a target question about the same entity, the authors compare predicted log‑probability shifts with actual measurements, finding that hidden reuse can reduce no‑change error by up to 49% on certain models and that a later protocol can achieve 58‑68% success on three cohorts. The study also notes that larger checkpoints, chat formats, and new entities affect replication, and that relation‑neutral changes at entity tokens lower relation‑selective error more effectively than random changes.

By Jinkun Chen, Xuemin Yu, Sijia Han, Vlado Keselj