This question is for folks who have done some kind of computing research.
Did you ever get formal training in how to do a literature review? What about informal training?
Some options, in case that lowers the barrier to entering the conversation:
This question is for folks who have done some kind of computing research.
Did you ever get formal training in how to do a literature review? What about informal training?
Some options, in case that lowers the barrier to entering the conversation:
@cxli For context: the #acmdl frictions make systematic reviews painful. It feels borderline unusable as a research tool and is incomplete.
#googlescholar is more complete, but the accuracy of the metadata drops off. I've found that historic searches (e.g., <1950) are mostly incorrectly dated.
I was curious whether this is corroborated by research and came across: https://pmc.ncbi.nlm.nih.gov/articles/PMC7079055/
...
@cxli Interestingly, this study (conducted in 2019) reports that the #ACMDL allows bulk download. I don't know if this feature is just hard to find or if it's been removed since then.
(Maybe @JonathanAldrich would know?)
@JonathanAldrich @cxli re:LLMs. I guess I might consider using an LLM to verify aspects of the review, but not for the primary research.
Here's an example task I recently tried to do: I wanted to catalogue the benchmarks used in ASPLOS 2026 papers. My query was very simple: just the papers from the proceedings that use the word "benchmark" somewhere. I wanted a table of the names of the suites, domain, units (or "entity types"), size, dates of introduction, and a few other things.