yongliang-wu/DFT

• highreadme#1

  Clarify the 'DFT' acronym in the README's introduction

  原因：

  当前

  # *On the Generalization of SFT*: <br>A Reinforcement Learning Perspective with <br>Reward Rectification

  复制粘贴的修复

  复制

  This repository presents **DFT** (*On the Generalization of SFT: A Reinforcement Learning Perspective with Reward Rectification*), an implementation for our ICLR 2026 paper. It explores a reinforcement learning perspective with reward rectification to improve the generalization of supervised fine-tuning (SFT).

  待办完成忽略
• highlicense#2

  Add a LICENSE file to the repository

  原因：

  复制粘贴的修复

  复制

  Create a `LICENSE` file in the repository root with the text of a standard open-source license, such as the MIT License.

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  How to improve supervised fine-tuning generalization for large language models using reinforcement learning?

  你：未被推荐
  AI 推荐顺序：

  1. 🤗 Transformers (huggingface/transformers)
  2. TRL (huggingface/trl)
  3. DeepMind's Acme (deepmind/acme)
  4. OpenAI's Spinning Up (openai/spinningup)
  5. 🤗 Datasets (huggingface/datasets)
  6. NumPy (numpy/numpy)
  7. PyTorch (pytorch/pytorch)

  AI 推荐了 7 个替代方案，却始终没点名 yongliang-wu/DFT。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  Seeking methods to enhance LLM training through novel reward rectification or shaping techniques.

  你：未被推荐
  AI 推荐顺序：

  1. Hugging Face Transformers (huggingface/transformers)
  2. TRL (Transformer Reinforcement Learning) library (huggingface/trl)
  3. PyTorch (pytorch/pytorch)
  4. JAX (google/jax)
  5. Anthropic
  6. TensorFlow (tensorflow/tensorflow)
  7. Hugging Face Accelerate (huggingface/accelerate)
  8. Stable Baselines3 (DLR-RM/stable-baselines3)
  9. Ray RLlib (ray-project/ray)

  AI 推荐了 9 个替代方案，却始终没点名 yongliang-wu/DFT。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  warn

  建议：

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of yongliang-wu/DFT?

  pass
  ✓AI 明确点名了 yongliang-wu/DFT

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts yongliang-wu/DFT in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 yongliang-wu/DFT

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo yongliang-wu/DFT solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 yongliang-wu/DFT

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？