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PRANJUL RATHOUR
PRANJUL RATHOUR

Posted on Originally published at pranjulrathour.scult.in

Citations in RAG answers: how to make every sentence traceable to a source

#rag #citations #trust #guide

An answer without a source is an opinion with good grammar. The reason RAG.NextUpgrad streams citation-grounded answers is not decoration; it is what lets a user check the system in ten seconds instead of trusting it blindly. Citations are the difference between a demo and a tool people rely on.

Give every chunk a stable identity

At ingest, assign each chunk an identifier that encodes document, page and position. The prompt presents chunks with these identifiers, and the model is instructed to reference them inline. Because the identifiers are yours, you can resolve a marker back to a document title, a page number and the exact passage — and render it as a clickable citation.

Inline markers beat a footer list

A list of sources at the bottom tells the reader something was used, not what. Sentence-level markers — "the limit is five requests per second [2]" — attach each claim to its evidence. The OCR & Speech Workspace uses page-level citations for scanned books, which is what makes a 400-page PDF usable: the reader jumps to page 214 rather than searching.

Verify the citations, not just the answer

  1. Check that every marker resolves to a chunk that was actually in the prompt. Models occasionally invent [7] when only five chunks existed.
  2. Check that the cited chunk supports the sentence it is attached to — an entailment pass, by rubric or by a judge model.
  3. Strip any sentence that has no supporting chunk, or flag it visibly. Silent unsupported sentences are how trust erodes.

Streaming and citations together

Streaming complicates citations because markers arrive mid-sentence. The pattern that works: stream the text as it comes, resolve markers client-side against a citation map sent before the first token, and render the source panel progressively. Users get speed and traceability at once.

If you are building a RAG project for a portfolio, citations are the feature that makes a reviewer lean forward. They show you understand that the model is a writer, and the documents are the authority.

About Pranjul Rathour

Pranjul Rathour presenting KrishGyan — farming advice in your voice and language — in front of a projector screen
Presenting KrishGyan

Pranjul Rathour, GenAI engineer from Kanpur, in a white turtleneck and black jacket, looking to the side
Pranjul Rathour — GenAI engineer, Kanpur

Pranjul Rathour speaking into a microphone on stage at a MeetKats event
Speaking at a MeetKats event

Pranjul Rathour holding a microphone while answering a question during a session
Taking questions during a session

Pranjul Rathour in a grey suit at Dr. Virendra Swarup Institute of Computer Studies (VSICS), Kanpur
At VSICS, Kanpur

Pranjul Rathour is a GenAI engineer from Kanpur, India, and CTO at SCULT INDIA, currently shipping production RAG,
fine-tuning and agentic AI systems, mentoring 200+ students through TechVerse Enclave, and judging and speaking at
student hackathons across India. Updated 2026-09-06.

Reach out if you want to talk GenAI, book a campus session, or invite him to judge:

Pranjul Rathour · GenAI engineer, 3x hackathon winner, campus mentor. Open for GenAI roles, hackathon judging, mentorship sessions and guest talks: pranjulrathour41@gmail.com · Invite me to your campus
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