Ziyi Zhang, Shengqi Li (on PhD app market!) for multi agent D&D sim creation + RL openreview.net/pdf?id=3Op7k...

Me mostly if you want boba and beach recs (or NVIDIA full time RS roles I guess, I'm hiring a few ppl there but not UCSD)

Jenny Shen for pluralistic alignment + human feedback arxiv.org/abs/2510.01167

Chris Cui for text sims + RL + scalable oversight of reasoning models arxiv.org/abs/2504.14128

Lucas (on industry market) for how reasoning emerges from mid training/SFT to RL lucasdino.github.io/assets/files...

Bosung Kim for all things VLA, embodied AI, and long context memory arxiv.org/abs/2505.16928

Ruiyi Wang for multi turn agentic RL and all the RL infra in and outs arxiv.org/abs/2510.01132

Yay congrats, Mark! Well deserved! It's def a required reading for all things comp storytelling (and creativity!)

My students will be presenting IRPO arxiv.org/abs/2504.15477 and a paper on Personalized RLHF arxiv.org/abs/2504.07070 on Wed onwards

My students will be presenting papers next Wed/Thursday so be sure to check those out too

Yes AI for edu is a thing but almost all vanilla LLMs just railroad students into answers. Complete cognitive offload is not useful for improving learning outcomes

That's fair, I guess I should rephrase to "regardless of a possible common prior, it's nearly impossible for different providers to have the same representations pop out of their post trained LLM"

The moral of the story here is basically that who is making your LLM really matters. Internal use cases critical to their businesses will always influence data distributions and everything downstream of that. This is in contrast to things like Platonic Representation Hypothesis

The top two scores are 332 not 322 but other than the typo the rest of this list seems legit and consistent across multiple sources
www.indiatvnews.com/education/hi...

x.com/RejaullahmdM...