Yixiong Hao

Projects

Writing

Resources

Ideas

Resume

I try to write ideas AND questions down when they pop up and this is a running collection (most recent on top). If any of them sounds interesting to you/if you can answer of my questions , please reach out :D

Last updated June 2025.

Product/use case

• LLM for peer reviewing because it’s so broken…
  • Turns out my professor dropped a paper on this! Check it out: https://arxiv.org/abs/2504.09737
• Finetune a vision model to describe in real time the items most relevant for situational awareness (some inference optimization) and attach a camera to glasses/some other eyewear. Sort of allow blind people to ‘see’
• TAs don’t get paid enough to grade manually written homework. What is we use OCR+LLM to make an autograder and then leave the regrade requests for TAs?
• An AI/ML journal/conference/workshop that publishes negative results
  • In addition to current flaws of the incentive structure of academia. it inherently encourages capabilities research that will get many references because they’re immediately applicable. Incentive for documenting negative results can help alignment because we also need to know what DOESN’T WORK
• An browser extension over LLM interfaces to collect hallucinations/bad responses in general. Companies need bad examples to RLHF their LLM continuously and improve then, not sure how they collect it at the moment
• Ok this one is goofy but what if we made a place where people can rant about their jobs and problems in their life (in detail) and people looking to solve these problems (us) can go contact them to get more info and feedback
• An agency to do deep tech diligence for investors for VCs
  • wtf happened with Rabbit R1
• Research the correlation between capability at like $1k worth of training and capability when training is complete, could use neuroevolution to discover better architectures for LLMs.
• Community notes + reddit native on every site, all over the internet
  • Already done, but hard to grow socially hahaha
• RAG + Anki automation for books & papers
• Gamify and socialize productivity - points app to see visible progress, “we make your efforts seen”
  • Ok I know how cringe this sounds but lemme cook
• Robot powered kitchen on campuses selling weekly meal prep
• Help yt and podcasters reach international audiences with AI voice and language translation
• LLMs as stream/chat/server moderators
• Alignment Hackathons
• Power up LLM content detectors and put them ALL over the internet, pitch to chrome/edge, this is a BIG issue rn and will only get worse
• Webapp for career fair and networking events - attendees can share their resume to a database accessible by search by employers, employers can star resumes etc, should be transparent to students too
  • Feature: contact sharing for networking: attendees fill out all forms of contact/profiles they’re comfortable with sharing, ability to star people etc
• Train/API a classification cv model and put them inside low cost cameras on frequently used bins, government contract
• Producing AI tools review and under the hood info content, too many useless wrappers
• Reinvent search engine, complete LLM engine with multiple interfaces (Screen, voice, or even neural in the future) companies pay to rank higher
• Use AI to detect deepfakes
  • Tbh all firms developing production models should be required to produce a tool that can reliably identify content their models created
• Mitigate social misalignment on the integration of AI systems into society
• Start a autopilot clout optimizer twitter acc
• LLM system for assessing the rationality of argument and award bayes points, twitter acc
• Birthday reminder app with ads for gifts

Alignment research

• Study scaling laws of activation engineering techniques
  • If mechanistic interpretability works out in the long term, alignment/steering techniques would likely involve modifying activations at inference time. This would be valuable knowledge
• Watermarking to detect LLM generated content - as a service.
• Improving in-the-open reasoning in natural language
  • Systems like language model agents that reason in the open are more interpretable and therefore controllable. If we want this to be used, we need to make it good enough to beat black box reasoning methods
• Pre training scoping: we do the HF part of RLHF to decide which parts to include in the data. Cheaper than AIF as the reward model should be way smaller!
• Start a org focusing on black-box psychology style research on LLMs/agents. Focus on reproducing the important studies in human psychology on this new form of intelligence. Based on this.