What Transfers Under Source Shift? Definitions, Examples, and Fine-Tuning for Climate Disclosure Classification

arXiv:2607.17952 · cs.CL, cs.CE · Submitted 2026-07-20 · Read on arXiv

cs.CL, cs.CE

Submitted: 2026-07-20

Updated: 2026-09-02

Comments: Accepted to Findings of EMNLP 2026. Camera-ready version

Code: https://github.com/Leoccino/TCFD-SourceShift

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Adaptation — 42× in this paper · explained in 1 episode
Fine-Tuning — 29× in this paper · explained in 5 episodes
Accuracy — 5× in this paper · explained in 1 episode
Robustness — 5× in this paper · explained in 5 episodes
Adam — 4× in this paper · explained in 2 episodes
Benchmark — 4× in this paper · explained in 2 episodes
In-Context Learning — 4× in this paper · explained in 4 episodes
LoRA Fine-Tuning — 4× in this paper · explained in 3 episodes
Embeddings — 3× in this paper · explained in 2 episodes
Generalization — 3× in this paper · explained in 13 episodes
Distribution Shift — 2× in this paper · explained in 5 episodes
Domain Shift — 2× in this paper · explained in 4 episodes
IEAs World Energy Outlook — 2× in this paper
Prompt Engineering — 2× in this paper · explained in 4 episodes
Benchmarking — 1× in this paper · explained in 3 episodes
Core — 1× in this paper · explained in 2 episodes
Domain Adaptation — 1× in this paper · explained in 5 episodes
LoRA Adapters — 1× in this paper · explained in 3 episodes
Parameter-Efficient Fine-Tuning — 1× in this paper · explained in 2 episodes
Quantization — 1× in this paper · explained in 12 episodes

Sources

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