Understand first
New to this knowledge point
Complete the prerequisite concepts, read the principles and counterexamples, and then explain why in your own words.
Start with core principles →Knowledge catalogChoose core direction and segmented content
Understand → Implement → Debug → Design
Evidence support, partial answers, and calibrated abstention
Examine the sufficiency of evidence, item-by-item citation, conflict resolution and rejection calibration.
Knowledge content check2026-10-03 · Check the source of the original question2026-10-02
It is recommended to understand first:
Prompts, structured output, and iterative acceptance checks →Context and generation budgets →Tool calls: structure, authorization, and business contracts →Which step do you want to learn from this knowledge point?
Select the starting point based on the current basis, or you can go deeper one by one. When you encounter an unfamiliar concept, go back to the core principles first; use the knowledge exercises to check your understanding when you are finished.
Implement next
Prepare to write the principles into code
Understand implementation steps and boundaries, complete small tasks, and check results against acceptance requirements.
Reading implementation and trade-offs →Debug failures
Need to handle failures and changes in conditions
Follow the continuous questioning to locate the failure premise, and then compare the migration cases to explain how the plan should be adjusted.
Continue to delve deeper into the problem →Compare designs
Need to design or review plans
Combine engineering deductions and senior self-evaluation standards to explain the applicable conditions, costs and alternatives of the plan.
Analyze engineering scenarios →Knowledge unit directory
LEARN · PRACTICE · REFLECT
Knowledge learning and personal records
First read along the principles, Q&A and migration cases. When you need to check your understanding, switch to reinforcement exercises or start personal recording.
Answers and personal notes
Can be practiced directly. After logging in, answers, favorites, and notes will be saved to your account.
Log in and saveEach modified commit will be kept as an independent history. Your level of mastery is up to you to evaluate yourself against the standards.
Core concept · Evidence support, partial answers, and calibrated abstention
Understand the core principles first
Preparatory concepts:Relevance and logical support, Advocate decomposition, Answers and No Answers Review
A citation proves a source, not a source that supports the current conclusion. The scope of the answer should be determined by the relationship between the verifiable claim and the evidence. When the evidence is insufficient, the conclusion should be narrowed or the information should be supplemented. Similarity cannot be used to fill in the answer.
Relevance does not establish a claim
A highly ranked task-management document about an old version’s pause feature may not answer whether this version supports cancellation. Locate each claim’s object, version, conditions, and value in evidence. Whole-document citations can hide missing support.
Choose among answering, qualifying, and clarifying
Answer with complete evidence; return supported portions with explicit gaps when evidence is partial. Clarify missing conditions and investigate outdated or conflicting sources. A justified inability to answer is valid. Unrelated citations plus model common knowledge cannot become verified knowledge-base evidence.
Evaluate support at the claim level
List required claims and mark supported, conflicting, outdated, or missing. Cross-document derivations need steps and shared conditions. Similarity locates reading material; model confidence is not a calibrated correctness probability. Verify important values and reporting definitions with deterministic calculations or human review.
Measure wrong answers and excessive refusal
Refusing everything lowers apparent hallucination without providing useful answers. Measure correct coverage on answerable questions, unsupported answers on unanswerable ones, partial-answer support, and clarification quality. Fix data versions and repeat evaluations for variability. Calibrate thresholds to samples and risk; no universal score guarantees correct refusal.
Check understanding with a question
RAG quoted the document but is still talking nonsense. How to judge whether to answer or refuse to answer?
A relevant document does not necessarily support a claim. Require specific evidence for key numbers and conclusions, distinguishing missing, stale, and conflicting support. Answer established portions with explicit gaps, clarifying or retrieving more when needed. Calibrate abstention with answerable and unanswerable examples rather than model-reported confidence.
Implementation and trade-offs
There are two levels of correct citations
First, the reference must actually exist, be accessible to users, and point to the correct version; second, the quoted fragment must support the specific claim. Linking to the entire document does not certify the numbers within it. By dividing "product supports SSO" and "current package includes SSO" into two claims, we can find that the model mistakenly expands general capabilities into specific benefits.
The status of the evidence determines the next step
If necessary fields are missing, a budgeted re-inspection can be carried out; if the question has entity ambiguity, clarify it first; if there is a source conflict, the source, time and scope of application will be explained side by side. Provisions from different years and different regions cannot be combined into a new rule. For evidence that the user does not currently have access to, the content cannot be disclosed by citing the abstract, nor can the hidden document title be exposed using "rejection reason".
More refusals do not automatically mean greater safety
Create four types of sets of answerable, unanswerable, partially answerable and conflicting questions. Measure the accuracy on answerable questions, unsupported-answer rate, false-refusal rate and citation support rate. Determine the business loss first, and then select the threshold; the similarity of a single vector is not naturally comparable between different queries and corpora, and the self-reported confidence of the model also requires external calibration.
Review and online verification
Use field checks or independent calculations for important facts, and use manually calibrated grader assistance for open conclusions, but retain manual spot checks. Record missing evidence categories to provide input for completing the knowledge base. User corrections can be entered into the feedback set to be reviewed and cannot be directly written back to the retrieval database as ground-truth answers, otherwise an incorrect feedback will become persistent contamination.
Engineering deduction
- scene
- Interview hypothesis: The answer quoted the general introduction of the product, but mistakenly stated that the basic package includes enterprise SSO.
- design decisions
- Split the package rights into claims and retrieve the corresponding version of package evidence.
- Verify target
- When the evidence does not support it, explain the gap and refuse to infer non-existent rights and interests.
- applicable boundary
- Thresholds should be calibrated according to business scenarios, and there is no guarantee that all generation will be completely error-free.
Continuous questions and answers
Continue reading along with the premises and constraints of the problem. Understand the reference answers first, then try to put away the answers and explain the cause and effect and trade-offs in your own words.
Level 1Does high similarity mean answerable?
Extend from the ranking signal to the evidentiary relationships required for the answer to be true.
Reference answer
Doesn't mean. The degree of similarity indicates the degree of correlation judged by the vector or retriever, and does not detect versions, negations, applicable conditions, and factual support. Break the question into claims and locate the evidence item by item; when you only find relevant introductions, you can explain the known background, but you cannot answer the missing key conclusions. A high score and a citation present may still be a no-answer sample.
Follow this answer further
Level 2Two of the three claims have evidence, but one is missing. Do I have to reject the entire paragraph?
After the parent question confirms that the score cannot make decisions, he further uses the claim dependence to determine part of the answer range.
Reference answer
There is no need to mechanically refuse to answer the whole paragraph. Answer two items and make the unconfirmed item clear when the two answered items do not depend on the third and would not mislead. If the third item is a prerequisite for executing an action, such as "no cancellation fees", it cannot be executed based on the other two suggestions. First draw the claim dependencies and decide whether the missing evidence blocks the entire conclusion.
Follow this answer further
Level 3The missing item is whether the payment is revocable. Can the model inference "should be possible" be used as a supplement?
When partial answers encounter key action premises, the boundaries of inference are stricter than general background explanations.
Reference answer
No executable conclusion can be drawn based on this. Refund availability, duration and fees depend on specific rules and general experience does not complement authorization or commercial conditions. Can explain which terms need to be checked, provide known status; pause the recommendation until applicable sources are obtained. The risk comes from the position of the missing item in the decision chain, not from whether the answer is written tactfully.
Level 1What should I do if two official documents conflict with each other?
Evidence may still conflict, requiring conditions and uncertainties to be preserved.
Reference answer
First check whether the product, version, region and effective time are the same, and then check for updates, corrections and formality. Many conflicts are just different scopes of application; when they cannot be resolved, the differences and sources are explained side by side, without averaging or picking the one you like best. Critical conflicts affecting operations should suspend conclusions, clarify scope, or seek authoritative updates.
Level 1How to prevent the increase in refusal rate from concealing the degradation of ability?
Refusal optimization itself will change the indicator denominator and requires complete acceptance.
Reference answer
Keep the question set and answerable labels unchanged, report answer coverage, incorrect answers, and false refusals separately; check the evidence flow for questions that could have been answered but were rejected. Taking "correctness only at the time of answer" encourages deletion of difficult questions. Relate new refusals to recalls and version changes to determine whether boundaries are reasonably maintained or capabilities are degraded.
Draw inferences from one example: If the conditions change, how to deduce it?
First find out the conditions for change, and then determine which premises in the original plan still hold true. The following cases are teaching deductions to facilitate the transfer of principles to new problems.
Allow general knowledge to aid explanation
Changing conditions:From closed knowledge base to source plus common sense
Extended question:The information only explains the retry mechanism. Can you add general engineering suggestions?
Derivation and reference solutions
When the business allows, you can clearly separate "clear explanation of data" and "suggestions based on engineering principles". It is recommended to state the premise and give an independent basis. Undocumented functions or configurations of this product cannot be supplemented. For models that only allow internal sources to be cited, the range of answers will be limited if there is insufficient evidence.
The principles that remain unchanged:Each specific claim generated must have a demonstrable basis, and inferences cannot be disguised as the source's exact words.
Information changes over time
Changing conditions:The answer used to be well-founded, but now the knowledge version is lagging behind
Extended question:Does the old quote actually exist and still answer "is it supported now"?
Derivation and reference solutions
Indicate the version and date of the material, and check the current release record; if there is no current evidence, you can only say how the old material describes it, and explain that the current situation cannot be confirmed. The old answer cache will be invalidated according to the knowledge version. Giving "used to be supported" cannot logically deduce "now supported", especially when there are deprecations or regional differences.
The principles that remain unchanged:The evidence must not only be relevant and exist, but also be applicable to the time the question was asked.
Easy to make mistakes
- If there is a citation, it is considered to be valid.
- Treat model confidence as probability
- Only optimize the accuracy rate without counting errors and rejections
References
It is designed based on public technical information; the reference materials support the technical mechanism, and the scenarios and scoring standards are designed by this website and do not represent the original interview questions of a certain company. New Q&A and migration cases are added for principle explanation, and source verification and case operation verification are recorded separately.
Check how far you understand
After reading, you can explain the principles, boundaries, and trade-offs against these standards. It is up to you to evaluate your mastery; if further verification is needed, complete the small tasks below.
- Basic standards met
- Ability to check, item by item, whether a quoted fragment actually supports an adjacent conclusion.
- Intermediate and advanced signals
- Four types of evidence samples are proposed, and wrong forced answers and wrong rejected answers are counted at the same time.
- Senior criteria
- String together evidence timeliness, authority, grader calibration and feedback review.
Continue to do advanced research experiments
Why can’t the old context continue to be used after the policy changes?
Transferring pre-retrieval filtered ideas to memory versions and recovery. Observe how existing drafts become invalid after cancellation.
Read full text and fault analysis → · Download Reliability Experiment v3 ↓
python3 cli.py memory-put --db memory.sqlite
python3 cli.py submit --db memory.sqlite
python3 cli.py run --db memory.sqlite --lease-seconds 2 --fault after_draft
python3 cli.py memory-forget --db memory.sqlite
# 等待至少 2 秒后分别执行
python3 cli.py run --db memory.sqlite
python3 cli.py inspect --db memory.sqliteKeep evidence and check item by item
- The draft checkpoint already exists after the first exit.
- Recovery after memory-forget gets failed with memory_changed_or_expired.
- No publish checkpoint; explain the difference between fail blocking and complete deletion.
Verify local scope, version, and undo blocking; old checkpoints remain, no complete deletion of logs, backups, or checkpoints is provided.
Hands-on verificationComplete on demand · Suggestions15 minutes
Provide two paragraphs of evidence for the three claims, mark support, contradictions and deficiencies, and write a final reply.
Expand acceptance requirements and checkpoints
- Claims that are not supported will not be forced to answer
- Conflict has origin and time
- Known parts can still be clearly delivered
Key inspections
- Distinguish between relevance and support
- Evaluate the two types of losses: forced answer and refused answer
- Handle conflicts, timeliness, and citation permissions