Here's what I recommend: Claude 3.5 Sonnet is way better than GPT for long PDFs, though it still misses some nuances. I've wasted sooo much cash on tools that hallucinate math, but for my thesis, I used Elicit AI Research Assistant. It's basically the pro choice for parsing findings into tables. Unfortunately, the 'Plus' plan is kinda pricey for a student budget, but ngl, it's SO worth it!

In my experience, academic PDFs use complex layouts that trip up basic AI. This matters because it leads to those hallucinations ur trying to avoid. Over the years, I've found SciSpace handles technical charts way better than GPT. Also, NotebookLM is honestly better for strict accuracy.

TL;DR: SciSpace for math/charts; NotebookLM for accuracy. gl!

Oh man, I feel u. Last year I was buried under 50-page engineering papers and the hallucinations were LITERALLY driving me crazy. I needed stuff that actually cited its sources so I wouldn't fail my peer review lol. It's so stressful when you're worried an AI is just hallucinating some math formula that doesn't exist.

After testing way too many tools for my own work, here are the ones I’m actually happy with:

1. Scholarcy Premium: This one is a beast for accuracy and safety.
- Pros: It breaks papers into structured "flashcards" and is GREAT at extracting tables and references. It feels much safer because it sticks strictly to the text provided and doesn't wander off.
- Cons: The monthly sub cost is something to consider on a student budget, but it saves hours of manual data entry.

2. Humata AI Pro: My go-to for the really long, dense files.
- Pros: It handles massive PDFs without any lag. The Q&A feature is super reliable for technical jargon since it points you directly to the exact page it's quoting so you can verify the findings.
- Cons: You kinda have to get the paid plan to get the best out of the advanced layout analysis.

Lesson learned: don't rely on basic LLMs for math or charts, but these specific tools make parsing SO much easier and more reliable. Good luck with the thesis! 👍

Exactly what I was thinking

Curious about one thing: are you dealing with heavy LaTeX symbols or just standard stats? Tbh, I've had issues with OCR layout analysis failing on complex math.

1. Consensus AI Search: Good for broad summaries, but unfortunately, free credits run out fast.
2. Perplexity AI Pro: Not as good as expected for technical precision in dense PDFs.

Knowing your specific budget would help before I recommend anything else!!

^ This. Also, managing the sheer volume of these files is half the battle. I spent months building my own local indexing system because I was paranoid about privacy and wanted total control over the metadata layers.

• my old server setup used to run 24/7
• custom scripts for cleaning up the OCR errors
• a massive SQL database for cross-referencing authors I actually remember one weekend where I almost fried my motherboard because I was trying to run a heavy analysis on a few thousand PDFs at once. The room got so hot I had to open all the windows in the middle of winter. I ended up learning more about hardware thermal limits than actual research that month. Anyway, just make sure you keep an eye on your system resources if you go the local processing route. But yeah.

> I specifically need something that can handle long PDFs and maybe even explain the charts or math sections. Has anyone found a reliable tool that doesn't hallucinate too much? I am happy you raised this topic because I have been dealing with the exact same issue for about five months now. Honestly, I am in the same boat and it is quite frustrating that I still havent found a reliable way to process these dense technical papers without the AI hallucinating the math sections. I have been systematically testing different setups for my research, but the precision just isnt there yet for the complex charts and formulas I encounter.