  How to eliminate pronominal reference in group chats? In this work, we have
preprocessed 58k authentic chat data and manually annotated 2.3k questions. The
reliability of this annotation was confirmed by the scaling law. After this, we
conducted fine-tuning on Qwen models, ranging from 0.5B to 32B parameters. The
optimal version improved 29.07 in F1 score. This confirms the viability of
fine-tuning Large Language Model (LLM) for downstream Natural Language
Processing (NLP) tasks. Our contributions are: 1) Created Supervised
Fine-Tuning (SFT) training data in alpaca format, along with a set of Low-Rank
Adaptation (LoRA) weights, and 2) Developed a method for acquiring high-quality
data leveraging scaling law principle. The script, raw data with alpaca format
and experiments track are open-sourced on Github
https://github.com/InternLM/HuixiangDou/tree/main/web/tools, HuggingFace
https://huggingface.co/tpoisonooo and WandB
https://wandb.ai/tpoisonooo/huixiangdou-cr/table?nw=nwusertpoisonooo . The
privacy of the data involved has been authorized by users.
