LoRA+CoT

Fine-tuning with chain-of-thought rationales aiming to reduce dr via procedural alignment.

Neighborhood — ranked by edge-count

concept

Fine-tuning
implements
Parameter updates that reduce mismatch dr; another anchoring variant in UCCT.
Prior-Target Mismatch (dr)
associated_with
Measures how far the target PT is from the prior P_prior; increases anchoring difficulty

method

E2: Numeral-Base Arithmetic Controlled Study
uses
Quantitative study varying representational familiarity via numeral bases B10/B8/B9 at fixed computational complexity

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

Short rationales (LoRA+CoT) sometimes improve in-distribution performance but do not reliably reduce cross-base harmfinding0.752
E2 finding showing CoT's limited benefit for OOD transfer, consistent with larger dr out of scope
LoRA (Low-Rank Adaptation)method0.738
Parameter-efficient fine-tuning method used for both SDF and expert iteration stages.
LoRA Fine-Tuning with Axolotlmethod0.717
Specific fine-tuning implementation using LoRA rank 32, learning rate 2e-4, AdamW 8-bit optimizer
Low-Rank Adaptation (LoRA)method0.711
Parameter-efficient fine-tuning method used to implement SOO fine-tuning on LLMs
LoRA SFTmethod0.704
Light fine-tuning method used in E2 to reduce mismatch dr.
Chain-of-Thought (CoT)framework0.703
A prompting technique that elicits intermediate reasoning steps before final answer inference in language models.
Multimodal-CoTframework0.683
A two-stage framework that separates rationale generation and answer inference by incorporating vision and language modalities.
CoT Monitormethod0.676
Named method for monitoring chain-of-thought text to detect when the model signals its answer, compared against activation probes