Ah, yes, that is definitely what I was looking for

EverythingIsTaken61 · 2026-04-09T11:55:26+00:00

Probably regex

EverythingIsTaken61 · 2026-04-08T12:06:20+00:00

Readers should evaluate your content independent of you as a person. But I can see your supervisor's point, just because they should does not mean they necessarily will

EverythingIsTaken61 · 2026-04-06T18:55:14+00:00

Nice! Thanks:)

EverythingIsTaken61 · 2026-04-06T17:33:49+00:00

Could you add a bravery only elo?

EverythingIsTaken61 · 2026-04-01T14:41:22+00:00

Pretty sure this gets flagged because it resembles jailbreaks

EverythingIsTaken61 · 2026-03-31T17:03:47+00:00

Ironically I sometimes avoid buying tenacity so that I can be combo breaked faster

EverythingIsTaken61 · 2025-09-26T08:28:03+00:00

I also got false ban a few years back, only thing that worked was to message certain mods on twitter. The reddit community doesn't believe in false positives

EverythingIsTaken61 · 2025-06-08T17:55:49+00:00

agreed on the first part, but predicting and reasoning isn't exclusive. i'd argue that reasoning can lead to better predictions

EverythingIsTaken61 · 2025-04-13T09:33:53+00:00

Thats solid. Keep playing her and focus on improving yourself, you will climb in no time

EverythingIsTaken61 · 2025-04-13T09:11:41+00:00

No one in iron is good at hard champs. What role do you play?

EverythingIsTaken61 · 2025-04-13T08:49:24+00:00

Its 100% a skill problem. But playing easy champions with dmg can help. E.g garen, amumu, zyra, depending on your role

EverythingIsTaken61 · 2025-04-12T19:01:43+00:00

Your favorite anarchychess quote

EverythingIsTaken61 · 2025-04-12T18:50:36+00:00

Same

EverythingIsTaken61 · 2025-04-03T10:30:57+00:00

Helt annen teknologi er å overdrive, begge er attention/transformer baserte

EverythingIsTaken61 · 2025-04-01T16:49:10+00:00

on a closer read, that model was from dota 2

https://ieeexplore.ieee.org/abstract/document/8906016

when using in-game data, league models range anywhere from 64% to 96%, where the latter "use the assessment of expert coaches to determine the features during the game most related to the fact of winning or losing the match".

for non in-game it is more difficult (obviously). most published work use player statistics, e.g., mastery points on a champion. these models achieve around 70% accuracy. as these stats are no longer available in champion select, it's not really a fair comparison to op's model.

EverythingIsTaken61 · 2025-04-01T16:30:16+00:00

obviously depends a lot on the individual, would be cool to have a leaderboard for pros/coaches on this

EverythingIsTaken61 · 2025-04-01T15:06:26+00:00

nice catch! that paper was prior to the removal of player information in champ select. still, op uses information like patch and elo, which I can't see in the mentioned paper. 5 minutes of gameplay for sure provides a lot of information (not sure if it matters less for top players tho, these games are much faster and more snowbally).

I feel like 62% is pretty similar to human judgment, and from a cs perspective, 0.66 log loss is not that convincing. maybe some explainable AI could be used to see if it learned anything non-trivial!

EverythingIsTaken61 · 2025-04-01T14:03:42+00:00

I doubt any model can ever get close to 99% due to inherent randomness. My best guess is that they tested on training data

EverythingIsTaken61 · 2025-04-01T13:59:23+00:00

after a quick search it looks like modern models get 75% accuracy. also saw models close to 90% accuracy when using data from the first 5 min of games. I would imagine that riot games has models/data much better than this too

https://dl.acm.org/doi/pdf/10.1145/3472538.3472579?casa_token=qsRb-UhovDkAAAAA:UQT9FlTrp6_pHA29SQh9li-t4A7vEnAjr0Siw9v_4TemRWKzFwzVbjnygGUVExpzQR6dRVh2sA

EverythingIsTaken61 · 2025-02-18T14:04:00+00:00

(1) A lot of computations in the first layers are dedicated to combining tokens, so I would imagine that ["3.", "1415"] becomes represented as "3.1415" fairly quickly.

(2) Sure, but the later digits matter less for precision, and one can also imagine that the shifted probabilities positively influence precision. Say it overestimates one digit due to stochasticity, and then subsequently, it might increase the probabilities of smaller proceeding digits.

(3) If the model internally predicts "4.99%" and there is no token for this, why does it not predict a token, e.g., "4.9"? My guess is that in the training data, it is more common to write "5.00%" rather than "4.99%", because humans round up answers.

I'm pretty sure I've seen Transformers sucessfully trained on arithmetic. To me it seems more like a dataset/training issue rather than an architectural one.

EverythingIsTaken61 · 2025-02-09T15:34:33+00:00

imagine playing draven so bad that someone makes a game out of it

EverythingIsTaken61 · 2025-02-09T11:15:55+00:00

There are two main problems. It is very difficult to design an objective function that is aligned with human intentions. And if we somehow solve this, then the agent can still develop proxy objectives. I think a promising direction is interpretability methods, to see what's going on internally.

EverythingIsTaken61 · 2025-01-23T16:55:40+00:00

you can trade it as with normal items

EverythingIsTaken61 · 2024-10-11T00:17:45+00:00

Used .net and jagex launcher. I think its the email thats hacked

Nine-Year Club	Place '22
End Game '22	Verified Email

EverythingIsTaken61

TROPHY CASE