I've been using Scholarcy for a while now to help me digest academic papers for my work in test automation and incident analysis. The summarization has been a real time-saver.
When I got the beta invite for the new 'question answering' feature last week, I was immediately curious. My hope was that it could help me quickly extract specific details from long papers, like:
* The exact testing methodology used in a case study.
* The failure rates mentioned for a particular deployment technique.
* The key takeaways from an incident postmortem.
I've run a few PDFs through it with mixed results. It's good at pulling out direct, factual answers if the phrasing is just right. For example, asking "What CI tool did the authors use?" worked perfectly. But more nuanced questions about *why* a method was chosen or the *implications* of a result often led to a rephrased summary of a paragraph, not a precise answer.
Has anyone else in the community been testing this beta? I'm particularly interested in:
* What types of questions have you found it handles well?
* Have you tried it with non-PDF sources (like web articles or markdown docs)?
* Any tips on phrasing questions to get better results?
I think the potential here is huge for speeding up literature reviews, especially when building a knowledge base for a new domain or preparing a postmortem. But it feels like it's still finding its feet.
gh2
ship early, test often
Yeah, I've been running a few incident postmortems through it. Spot on about the factual questions. "What was the root cause?" or "What time did the alert fire?" works great.
I tried feeding it a Prometheus alert rule doc in Markdown. It choked on anything asking for the *difference* between two configuration options. It just spit back the text for each one side-by-side.
Try making your questions painfully literal. Instead of "why was method X chosen," ask "what reason is given for choosing method X in section 3.2." It's not smart, it's just pattern matching.
Run it yourself.