Open-sourced jev architecture last year with model,paper and dataset
Everyone now talks about the architecture that's not auto regressive and does lightning fast probability prediction with a json schema. I worked on this literally one year back in March 2025, published an arxiv paper, pushed the model to huggingface along with the pypi package and training dataset. And then one year later, a frontier lab came, proposing the same idea like literal breakthrough without technical papers, open weights and no open dataset. For anyones information the main guiding model is RL not embedding model or LLM
Paper: https://arxiv.org/abs/2503.23303
Model: https://huggingface.co/DeepMostInnovations/sales-conversion-model-reinf-learning
Dataset: https://huggingface.co/datasets/DeepMostInnovations/saas-sales-conversations
Also the second work published in September 2025 was exactly the same one jev proposed now
Paper: https://arxiv.org/abs/2510.01237
My model uses PPO over sequence embeddings to output turn-by-turn conversion trajectories (probabilities from 0.0 to 1.0).
Jev uses parallel sampling (trained via RLCD) to output confidence distributions and schema choices.
It's incredibly frustrating that the thing that you made with months of hard work, sweat and sleepless night is architecturally similar with the vertical use case and don't get the support you deserve because frontier lab build something horizontal. The open-source story in general
> It's incredibly frustrating that the thing that you made with months of hard work, sweat and sleepless night is architecturally similar with the vertical use case and don't get the support you deserve because frontier lab build something horizontal.
Totally get the frustration.
Don't get too bent up about it -- take it as the market validating your hypothesis in a way you didn't expect. You should feel proud! That skillset - finding niches that could be humongous given the right cultivation, luck, funding, and marketing - is amazing.
I feel strongly that, if JEV and/or your model prove valuable as many of us are already thinking and hypothesizing, people will come knocking.
While LLMs are a neat space, this is a desperately missing component, and as someone who has built conditional choice probability models for almost two decades, I'm wildly interested to dig in this weekend and review the usefulness, the applicability as a homo economicus level of automation in a noisy prompt space (e.g. ensuring transitivity and IIA), and looking at this as a strong evolution.
I've added your model to my eval list!
From what I can tell these are classifiers trained for a single task. What excites people about Jev is that it can do zero-shot structured responses for arbitrary prompts. Now, this isn't new either; models like GLiNER have been around for a while. But Jev appears significantly more flexible and polished while still being cheap and fast.
The world's heavily about marketing, resources, connections, and signaling, unfortunately. You probably needed to market it in a bigger forum with shinier claims to attract attention (I don't think a paper on Arxiv is enough).
Feeling that open-source community do not get the recognition they deserve
https://github.com/vllm-project/vllm/pull/57250
Pity because without the frustration it would’ve been a good post. Catch is you’ve got intuition, but looking around instead of forward. Do it again, open-source it, either you’d quietly bring down few companies, or, when you’re close, you’d get offers from them. The who’s done what is a dying paradigm.
We are human , frustration is something we feel when same kinda architecture is closed sourced and we celebrate it
> We are human , frustration is something we feel
Absolutely. Besides, when we see injustice we shouldn't be silent about it because that would encourage more of it.
> when same kinda architecture is closed sourced and we celebrate it
I saw the post about Jev and the lack of basic information felt wrong and bizarre, I now see the most likely reason for it.
The best thing to do now, is to develop your open source project further and beat the Jev-ers, that story is very motivational and I'm interested.
Can you (or someone) provide some context for this post? What's Jev? What's the innovation here that was duplicated by the frontier lab?
Put it on your CV
"I can come up with revolutionary ideas one year earlier than entire billion dollar organizations"
"I inventet Jev a year earlier"
terrible, antisocial and wrong take
Lol no one cares, make a good product of it