Junyan Xu

https://www.arxiv-vanity.com/papers/2305.17743/ too See also https://github.com/arxiv-vanity/arxiv-vanity/issues/761

We already used ELF (v0 and v1) to generate selfplay games before, and v0 seems to have accelerated the progress, but the effect of v1 was unclear. Also a network...

I think you can just use my komi+next branch (or the release of the same name) and append --nonslack to your command. It will automatically adjust winrate to the range...

Setting --target-komi -7.5 has absolutely the same effect as switching black and white. I get other komi by interpolating or extrapolating from these two scenarios.

+ The G series networks are regularly updated at https://drive.google.com/drive/folders/1XrdAxjDQ7Dnz49QRdv9Dfm1P__-rwR3L + For the latest engine, compile the komi+next branch or use the release https://github.com/alreadydone/lz/releases/tag/komi%2Bv0.42 + For instructions see https://github.com/gcp/leela-zero/pull/1772. Best...

From what I heard it's at least decent for handicap games if not the best. By the way, the initial number 5 means training used 50% human games. I think...

I think this is a part of a bigger program of autoformalization (with internal Google code-name [N2Formal](https://leanprover-community.github.io/archive/stream/219941-Machine-Learning-for-Theorem-Proving/topic/Papers.20on.20Neural.20Conjecturing.html#200585253), which I think stands for 'natural to formal'). These threads on Zulip mention...

I think there is potential that human mathematicians could teach a lot of math to machines through a powerful language model like the one behind OpenAI API [2], but the...

**[after I pointed out Szegedy's document *A Promising Path Towards Autoformalization and General Artificial Intelligence* to /u/starspawn0, he reposted it as a topic on the same subreddit, and the following...

Additional relevant papers (continually updated): *Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity*, Berkeley (Pathak et al.), https://arxiv.org/abs/1902.05546, [tweet](https://twitter.com/pathak2206/status/1098376206880108546) *What Can Neural Networks Reason About?*, https://arxiv.org/abs/1905.13211, [tweet](https://twitter.com/KeyuluXu/status/1208242799948156928)...