By skyforbes Hi everyone,
I’m analyzing a long conversation with an LLM and I’d like to understand how to detect whether the model is truly using earlier messages or just generating a generic answer.
I’m analyzing a long conversation with an LLM and I’d like to understand how to detect whether the model is truly using earlier messages or just generating a generic answer.
I’m specifically looking for guidance on:
- how to check if an LLM is attending to past turns
- signs that an answer is generic or hallucinated
- prompting techniques to force stronger grounding in previous messages
- tools or methods people use to analyze context usage in multi-turn dialogue
- how to reduce or test for “context drop” in long chats
The conversation is in French, spans many messages, and includes mixed topics — so I’d like to avoid misinterpreting whether the model actually used the prior context.
How do you personally evaluate whether a response is context-grounded?
Are there tools, prompt patterns, or techniques that you recommend?
Thanks a lot for any guidance!