ReFT is different: (1) ReFT selects timesteps to intervene on; and (2) ReFT targets representations instead of weights. To help you understand these differences, let's consider these cases: Learning LoRA weights on o_proj. Learning ReFT interventons that apply to …

Apr 4, 2024 · ReFT methods operate on a frozen base model and learn task-specific interventions on hidden representations. We define a strong instance of the ReFT family, Low-rank Linear Subspace ReFT (LoReFT), and we identify an ablation of this method that trades some performance for increased efficiency.

ReFT represents a novel approach to parameter-efficient, powerful, and interpretable fine-tuning of language models.

Dec 20, 2024 · LoReFT, is a technique that adjusts the hidden representations within a linear subspace formed by a low-rank projection matrix. It builds upon the distributed alignment search (DAS) method introduced by Geiger et al. and Wu et al.

Feb 4, 2025 · ReFT is different: (1) ReFT selects timesteps to intervene on; and (2) ReFT targets representations instead of weights. To help you understand these differences, let's consider these cases: Learning LoRA weights on o_proj. Learning ReFT interventons that apply to …

ReFT methods operate on a frozen base model and learn task-specific interventions on hidden representations. We define a strong instance of the ReFT family, Low-rank Linear Subspace ReFT (LoReFT), and we identify an ablation of this method that trades some performance for increased eficiency.

Apr 6, 2024 · In the paper [3], researchers propose Representation Finetuning (ReFT) approach, which operates on a frozen base model and learn task-specific interventions on hidden representations. This...

Oct 7, 2024 · ReFT techniques learn task-specific interventions on hidden representations using a frozen base model. We define Low-rank Linear Subspace ReFT (LoReFT), a strong instance of the ReFT...

ReFT methods operate on a frozen base model and learn task-specific interventions on hidden representations. We define a strong instance of the ReFT family, Low-rank Linear Subspace ReFT (LoReFT), and we identify an ablation of this method that trades some performance for increased eficiency.

Aug 14, 2024 · ReFT methods train interventions that manipulate a small fraction of model representations in order to adapt model behaviors to solve downstream tasks at inference time, also being replacements...