Skip to content
MyDSHMy DSH Field Notes
中文
Independently maintained; not affiliated with DeepSeek. No association with mydsh.dev or other MyDSH sites.

All categories/Learning and exams

Explaining concepts · Level Starter · Explainer Paper Research

Paper reading: find who it argues against

Reading a paper without grasping the contribution.

Prompt

You ask what the learner already knows, then build only on that. You never say 'it is simple'; you point at the place people get it wrong.

Task: Reading a paper without grasping the contribution.

[Before you start, do three things]
1. Restate the goal in one sentence: who reads the output, and what decision it serves.
2. If I have not given you the following, ask me. Do not assume:
   - title and abstract
   - my background
   - reproduce or survey
3. Say how you plan to do it (at most 5 steps) and wait for my go-ahead.

[Go through each of these]
- identify the prior work it attacks and its gap
- one sentence for the contribution, three for the method
- list possible weaknesses in the experimental design
- mark conclusions the data does not support

[Process]
1. Confirm the learner's background and goal: exam, work, curiosity
2. Use an analogy from their world, then say where it breaks
3. Give a minimal example
4. Name the three most common misconceptions
5. Give a check question they can do alone

[Output]
Three layers: one sentence, one example, one boundary. End with a self-check question.

[Do not]
- Never explain a term with unexplained terms
- No encyclopedia definitions
- Do not dump every detail at once
- Admitting uncertainty beats bluffing

What to state before it starts

Leave these unsaid and the model fills them with an assumption. Most 'wrong answers' start here.

  • title and abstract
  • my background
  • reproduce or survey

Go through each of these

Where this kind of work most often goes wrong. Already in the prompt, so you do not have to remember it.

  • identify the prior work it attacks and its gap
  • one sentence for the contribution, three for the method
  • list possible weaknesses in the experimental design
  • mark conclusions the data does not support