Interview Bank

How to reason about it · think before answering

1. The question is about where trust comes from. 'Citations are more convenient' is surface; the real difference is who guarantees the quote is real.
2. With prompting, both the quote and the page number are free text the model generates — it may paraphrase, it may misremember the page, and you cannot tell a real quote from an imagined one. With citations, the model emits citation intent in a standard format, the API parses and verifies it server-side, cited_text is guaranteed to exist in the document, and page_location comes from the API. Fidelity is enforced by the API rather than promised by the model.
3. Two side benefits: cited_text does not count toward output tokens, so it is cheaper than asking the model to copy; and the result is structured content blocks your UI can highlight and jump to without regex guessing.
4. When you can't: citations are incompatible with structured outputs (JSON Schema) — enabling both returns a 400. Either drop API-level citations and add a page field to the schema (one notch less reliable), or split into two calls: citations for facts, structured output for shaping.
5. Follow-ups: page semantics — start_page_number is 1-indexed and end_page_number is exclusive; document_index distinguishes sources. Can you audit citation quality? Yes — string-match cited_text against the source, or sample manually.

分析过程 · 先想清楚再作答

1. 这题考的是「可信度从哪来」。答成「citations 更方便」是表面；本质区别是谁来保证引用的真实性。
2. 拆法：提示词方案里，引用和页码都是模型生成的自由文本——它可能顺手改写原文、可能记错页码，你无法区分「真引用」和「自以为引用」。citations 方案里，模型内部以标准格式输出引用意图，API 在服务端解析并核对，返回的 cited_text 一定是文档里真实存在的段落，page_location 的页码由 API 给出。真实性由 API 保证而不是由模型自觉保证。
3. 附带的两点好处：cited_text 不计入输出 token，比让模型抄原文便宜；返回是结构化的内容块，程序可以直接高亮、跳转，不用正则去猜「第 3 页」出现在哪。
4. 不能用的场景：与结构化输出（JSON Schema）不兼容，二者同开会报 400；此时要么放弃 API 级引用、在 schema 里留 page 字段让模型自己填（可靠性差一档），要么分两步：先 citations 拿事实，再用结构化输出整理。
5. 可预期的追问：页码字段的语义？start_page_number 从 1 开始，end_page_number 不包含；多文档时 document_index 区分来源。再追问「能否验证引用质量」——能，用 cited_text 与原文做字符串比对，或抽样人工核对。

How to reason about it · think before answering

1. The discriminator is not how many checks you list but whether you can justify the three. Ten items with no ranking suggests you have never had to prioritise.
2. Derive them by consequence: the failures that are invisible to users and most damaging go first.
3. First, citations must be verifiable: every cited id resolves to a real chunk, and that chunk genuinely overlaps the sentence citing it. This ranks first because a wrong citation is undetectable by the user, and citations are the only source of trust this system has.
4. Second, refusal must actually fire: ask a question the corpus cannot answer and confirm the system says so instead of inventing. Also invisible, and one discovered fabrication zeroes out trust in the whole product.
5. Third, ingestion-to-retrieval consistency: freshly ingested documents are retrievable immediately, and the keyword and vector paths cover the same set. This guards against the 'one route finds it, the other does not' failure, which is the hardest to diagnose.
6. Expected follow-up: why not latency and cost? Because those failures are visible. Users complain about slowness and the bill reports overspending; nobody will ever report the three above.

分析过程 · 先想清楚再作答

1. 这题的区分度不在你能列几项，而在你能不能说清「为什么是这三项」。列十项而每项都不给理由，反而说明你没有排过优先级。
2. 推导方式是按后果排序：哪种故障用户看不出来、又损失最大，哪一项就该排在前面。
3. 第一项是引用可查证：每条引用的编号都能回查到真实存在的块，且那一块确实与该句有实质重合。这一项排第一是因为引用错了用户根本发现不了，而它恰恰是这类系统唯一的信任来源。
4. 第二项是该拒答时真的拒答：构造一个语料里没有答案的问题，看它是回那句拒答话术还是开始编。这一项也属于用户看不出来的故障，且一旦编造被发现，整个系统的可信度归零。
5. 第三项是摄取到检索的一致性：摄取完之后新文档立刻能被检索到，且关键词与向量两路的覆盖数量对得上。这一项防的是「一路能查一路查不到」这种最难排查的故障。
6. 可预期的追问：为什么延迟和成本不在前三？因为它们是**看得见**的故障——慢了用户会抱怨，贵了账单会告诉你；而上面三项不检查就永远不会有人告诉你。