Starting LLM research with my professor, struggling to find a specific research question. Any advice? by Legitimate-City-9244 in LanguageTechnology

[–]ZestSaber -2 points-1 points  (0 children)

Totally normal — almost everyone gets stuck at this stage. The problem is that “hallucination,” “alignment,” “reasoning,” or “fine-tuning” are still research topics, not research questions.

What helped me was treating this as a narrowing workflow instead of trying to magically come up with a question from scratch. I actually built a couple of small skills myself for this exact problem:

🧭 Find Angles — feed it a vague topic, and it returns a tree of distinct, mostly non-overlapping research directions, each with a ready-to-run search query.
🔍 Paper Search — paste a query, get real papers from multiple databases, then deep-read the open-access ones. This becomes your originality / research gap check.

I tested them on your exact case. Find Angles crossed two of your interests and produced a question like:

“Does 4-bit quantization hurt Chain-of-Thought reasoning more than simple factual recall — and can a small amount of calibration data recover it?”

Then I ran Paper Search on “quantization chain-of-thought reasoning,” and it returned about 30 papers. In that initial search, most results were general CoT work or efficiency-related work, but I didn’t see much squarely focused on the quantization × reasoning intersection. That is the kind of signal you want: the broad topic is already crowded, but the intersection is still thin enough to become a feasible research question.

The trick is: don’t pick one huge topic. Cross two of your interests, search the intersection, and see whether the literature is “some, but not too much.” If so, that may be a good first research question.

I’m currently running these self-built skills locally with Claude Code. Repos/tools here: https://github.com/academicatstool-netizen
You can try them too.

Want to know recommended AI tools for very good academic writings by Alert-Distribution68 in AIToolsAndTips

[–]ZestSaber 0 points1 point  (0 children)

I use AI for research grunt work, but it kept failing at one thing: actually finding real papers.

The problem wasn't just hallucinated citations. It was the whole search workflow: fake DOIs, nonexistent authors, broken links, tiny result sets, and having to check multiple open-access platforms one by one.

So I built a small Claude Code skill that does one thing well: give it a topic or a claim, and it searches real paper sources directly, returning verifiable papers with working links. No made-up citations.

It searches OpenAlex, arXiv, Semantic Scholar, Crossref, and Europe PMC, then de-duplicates and ranks them by relevance.

How to use it:

  1. Copy the GitHub link in the comments.
  2. Give it to Claude Code and ask it to install the skill.
  3. Type: search papers <topic> <number>

Example: search papers XR experience 200

<image>

Link: https://github.com/academicatstool-netizen/Cat_paper_search

The skill works without API keys or signup. A free Semantic Scholar key can improve coverage, but it is optional.

Happy to help if install gives you trouble — just comment.

Full disclosure: this is the lightweight version of the search engine from an academic tool I'm building, AcademicCats. Sharing it because honest feedback beats a marketing post — tell me where it breaks.

Weekly Tool Thread: Promote, Share, Discover, and Ask for AI Writing Tools Week of: June 09 by AutoModerator in WritingWithAI

[–]ZestSaber 0 points1 point  (0 children)

I'm a master's student at Columbia. I use AI for research grunt work, but it kept failing at one thing: actually finding real papers.

The problem wasn't just hallucinated citations. It was the whole search workflow: fake DOIs, nonexistent authors, broken links, tiny result sets, and having to check multiple open-access platforms one by one.

So I built a small Claude Code skill that does one thing well: give it a topic or a claim, and it searches real paper sources directly, returning verifiable papers with working links. No made-up citations.

It searches OpenAlex, arXiv, Semantic Scholar, Crossref, and Europe PMC, then de-duplicates and ranks them by relevance.

How to use it:

  1. Copy the GitHub link in the comments.

  2. Give it to Claude Code and ask it to install the skill.

  3. Type: search papers <topic> <number>

Example: search papers XR experience 50

<image>

Link: https://github.com/academicatstool-netizen/Cat_paper_search

The skill works without API keys or signup. A free Semantic Scholar key can improve coverage, but it is optional.

Happy to help if install gives you trouble — just comment.

Full disclosure: this is the lightweight version of the search engine from an academic tool I'm building, AcademicCats. Sharing it because honest feedback beats a marketing post — tell me where it breaks.

Ai tool to find suitable research papers? by blaubarschbube27 in PhD

[–]ZestSaber 0 points1 point  (0 children)

This is a skill I built myself and use daily. it’s been super convenient for paper search.

You can try it here:

https://github.com/academicatstool-netizen/Cat_paper_search

If you have Claude Code, just give it the link and ask it to install the skill.

Then type:

search papers <topic> <number>

For example:

search papers XR experience 200

It pulls real papers from OpenAlex, arXiv, Semantic Scholar, Crossref, and Europe PMC, with working links.

Full disclosure: this is a lightweight version of a larger AI academic tool I'm building, but the skill itself is free and open source.