Is there a proof of convergence for any transformer model? D | R
I'm interested in proofs of convergence surrounding NLP problems in general, and transformers in particular. Can anyone point me to a paper that proves an NLP machine learning model converges to anything at all?
I see some validation in the practice of NLP, but I'm struggling to intuit a target to converge to when trying to prove that a transformer converges to anything at all.
/r/MachineLearning
https://redd.it/1aol1tp
How to get out the loneliness of research career
Hi guys, I'm a ms student and I'm doing research under the guidance with a new AP in my university. H's a good person, has strong capability, and he always encourages us to follow our own thoughts. However, since he is a new AP, our lab only have 2 ms students including me and 0 phd student.
I feel like overwhelmed by the loneliness. When I come across problems, such as the derivation of formulas and some research stuff, I can't find a friend to ask. My only way of acquiring information from other people is my weekly meeting with my professor.
I tried to talk with other phds in my univ but they usually don't work on my field, i.e., unsupervised learning and world models stuff. One impressive moment is one day I deployed some docker apps to our lab server just for fun. I wanted to cheer for that but couldn't find anyone to talk with.
I'm determined to pursue a phd career but I can't stand for the loneliness and pressure (from both research and coursework since I'm a ms). The instructions given by professor is rather free because he doesn't want to be so rigorous and hopes to inspire our enthusiasm towards research, whereas I need to publish one paper before my phd application so that I can be competitive in the applicantion pool. However, even if I become a phd in those big schools, I'm afraid that I'll keep repeating this lonely life for 5 years, and I'll spend my life before my 30 as an upset person :(
Sorry for these cliche, I just can't hold myself.
/r/deeplearning
https://redd.it/1ak1hmn
D 3 years doing ML, no success yet. Is it common?
I'm working in ML research for 1.5 years now, more specifically medical imaging and previously as a DL Engineer for building a facial recognition pipeline. Despite a good understanding and all my focus I'm yet to make a good enough system or model for all many use cases I worked on.
From last 4 months I'm exploring 'learning from noisy label' I worked on 3 techniques, spent considerate time integrating target loaders but results were poor, even worse than baseline.
Previously, made a failed attempt to make a system identification using hybrid adaptive algorithm scheme but approach failed. Did write a technical report on that.
Also, on the otherhand, I do participate in online competition. Vanilla methods get me top 10-20% but when I try to improve on it, I always fail. None of my method work well, super frustrating despite all efforts.
I'm not trying to build a state-of-art model, but atleast expect myself to get over the previous baselines or work of any significance.
/r/MachineLearning
https://redd.it/1aeq9pz
Open Source Multicamera Calibration in a GUI: pyxy3d
/r/computervision
https://redd.it/18rcwy4
D Deep dive into the MMLU ("Are you smarter than an LLM?")
After all the hubbub around the MMLU (for example my article) I thought I would make an interface for seeing how humans do versus even middle of the pack LLM. It's called Are You Smarter Than An LLM?
It presents you random questions from the MMLU and compares your answers to the LLM. Click the "what is this" button at the bottom for more details on how it works.
Feedback appreciated!
/r/MachineLearning
https://redd.it/18ntia7
KL divergence
Why do we use KL divergence in VAEs, it seems to me that we could just minimize the cross entropy between our models distribution and the Gaussian (or whatever distribution we choose for latent space). Is it simply because KL divergence has a minimum of 0 and we already know the entropy of the Gaussian? I guess more what I am getting at is how do we choose between kl divergence and cross entropy as a loss function if minimizing one always minimizes the other?
/r/deeplearning
https://redd.it/18k82sv
3D Pose Estimation of Two Interacting Hands from a Monocular Event Camera
/r/computervision
https://redd.it/18fvkv5
D Thoughts on Mamba?
I ran the NanoGPT of Karparthy replacing Self-Attention with Mamba on his TinyShakespeare Dataset and within 5 minutes it started spitting out the following:
​
https://preview.redd.it/4r96tp6lxx4c1.png?width=836&format=png&auto=webp&s=10f2f61cd4cea96f4f903cb2070835fc5d1df951
​
https://preview.redd.it/32ler5vnxx4c1.png?width=622&format=png&auto=webp&s=dd00e53f43dd0afa058758a987901ee6789d2258
​
https://preview.redd.it/sc96i4xoxx4c1.png?width=678&format=png&auto=webp&s=94d2ed279054363d3ed2b6beed65be89468582b0
So much faster than self-attention, and so much smoother, running at 6 epochs per second. I'm honestly gobsmacked.
https://colab.research.google.com/drive/1g9qpeVcFa0ca0cnhmqusO4RZtQdh9umY?usp=sharing
​
Some loss graphs:
Multihead attention without truncation\(x is iterations in 10s, and y is loss\)
Multihead attention with truncation\(x is iterations in 10s, and y is loss\)
Mamba loss graph\(x is iterations in 10s, and y is loss\)
​
​
/r/MachineLearning
https://redd.it/18d65bz
After two years of self-study, my first independent paper: Cross-Axis Transformer with 2D Rotary Embeddings
https://arxiv.org/pdf/2311.07184v1.pdf
/r/computervision
https://redd.it/189bo8i
A good modern textbook to get me up to speed on NLP in Python?
Hey everyone,
I have an MS in Statistics, but the focus was not on NLP - more classical models with a little machine learning. I'm not sure what's hip in the NLP circles, but I don't want to go down a bunch of rabbit holes trying to find out. Any suggestions?
/r/LanguageTechnology
https://redd.it/17xa49p
I built an open source motion capture system that costs $20 and runs at 150fps! Details in comments
/r/computervision
https://redd.it/17xi20j
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Is overfitting always a bad thing?
As I understand, overfitting occurs when a model learns noise in the training data, so that it performs on training data higher than validation data. Overfitting is bad because overfit models do not generalize well on unseen data. So we use early stopping to prevent overfitting.
Now, I am training a CNN for image classification. At first, till the training accuracy reaches 95%, I see the same trend in validation accuracy. So till this point, there is no overfitting. But as I train the model from 95% to 99%, validation accuracy moves from 95% to 96%. By definition, this is overfitting, but the validation performance of the model is still improving. Is this kind of overfitting also considered bad?
/r/deeplearning
https://redd.it/1alyiic
D Why do current LLMs work well in discrete space but not in continuous space?
One interesting observation is that LMs are trained to predict tokens over a categorical distribution and then a sampling algorithm is used to discretize the distribution to produce an output. If we try this in a continuous domain, e.g., predict pixels directly with L2 loss, it doesn't work, the output gets very blurry. It seems that the descretization via sampling is crucial to make things work during inference. Recent papers like GIVT can model the output as a gaussian mixture instead of a categorical distribution, but sampling is still necessary to make it work.
I'm sure this isn't some new observation, are there any resources out there that can help explain why this is the case?
/r/MachineLearning
https://redd.it/18vfj7k
D Do we really know how token probability leads to reasoning? For example, when we give GPT4 a riddle and it selves it using non-intuitive logic, how is that happening?
GPT4 can solve the below very basic riddle/question with ease.
Example riddle: You have a cup and a ball. You place the ball on the table and place the cup over the ball. You then place the cup on the kitchen counter. Where is the ball?
Answer: It's still on the original table of course.
How does a probability engine know that reasoning?
/r/MachineLearning
https://redd.it/18q9ucf
D What are 2023's top innovations in ML/AI outside of LLM stuff?
What really caught your eye so far this year? Both high profile applications but also research innovations which may shape the field for decades to come.
/r/MachineLearning
https://redd.it/18hnh8p
PubMedBERT Embeddings - Semantic search and retrieval augmented generation for medical literature
https://huggingface.co/NeuML/pubmedbert-base-embeddings
/r/LanguageTechnology
https://redd.it/17y4a5s
How do you keep up with the advancements with/in LLMs?
I would like to know how everyone can stay (almost) up-to-date with the advancements in LLMs? Do you follow survey papers/any blogs/newsletters/channels etc?
/r/LanguageTechnology
https://redd.it/18akb71
Converting multiview images to 3d model
Hi, I'm looking for a solution to convert multi-view images that look like this:
https://preview.redd.it/wbquazk95i4c1.png?width=1762&format=png&auto=webp&s=5a9ded99bc0eb8891e73f7519317a7aeae572044
into 3D models (obj, glb, etc.)
I'm pretty sure I can do this with NeRF but I'm fairly new to the field (coming from a classic software engineer background) so I'm looking for suggestions and some advice on this topic.
I've also been suggested to use COLMAP for this purpose but from what I understand COLMAP seems to be a different kind of tool that is meant to reconstruct 3d from multiple poses / camera pictures.
I'd also welcome any existing projects that could help me save some time doing so. Thanks!
/r/computervision
https://redd.it/18bftod
We've programmed our DIY smartwatch to take the wheel and steer the Space Rover around 🚀🌌
/r/computervision
https://redd.it/186q043
[R]eading List for Andrej Karpathy’s “Busy person’s intro to Large Language Models” Video
I loved Andrej’s talk about in his “Busy person’s intro to Large Language Models” video, so I decided to create a reading list to dive in deeper to a lot of the topics. I feel like he did a great job of describing the state of the art for anyone from an ML Researcher to any engineer who is interested in learning more.
The full talk can be found here:
https://youtu.be/zjkBMFhNj_g?si=fPvPyOVmV-FCTFEx
Here’s the reading list:
https://blog.oxen.ai/reading-list-for-andrej-karpathys-intro-to-large-language-models-video/
Let me know if you have any other papers you would add!
/r/MachineLearning
https://redd.it/184qeuo
Who wants to take on Duolingo?
Hello /r/LanguageTechnology \-
I've recently built my prototype for an NLP based language learning application which was received very positively. I've decided to go full time on it and make it a reality, and am looking for another technical co-founder to join me on this journey as CTO.
I'm a technical founder, but as I'm currently doing all the development, design, admin, sales, support, funding, etc, I'm looking for someone to just focus on the tech. The tech includes:
\- python backend
\- clojurescript frontend
\- NLP (currently via stanza, although partial support for spacy as well)
\- lots of LLM integrations
\- lots of TTS integrations
\- lots of vector embeddings
​
If any polyglots out there are passionate about NLP/LLMs/AI, genuinely believe they can change the world, dream in docker files and model weights, and just want to work on really cool tech, please send me a DM 🙏 let's change the world together.
Site can be found at https://phrasing.app. The app is currently in private beta, if you're interested in the application but not the job, fill out the beta application and send me a DM and I'll prioritize your access 😁
PS: I messaged mods first for permission, but heard no response. I hope this post is well received.
​
/r/LanguageTechnology
https://redd.it/180h4s9
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470. @r_Avicii
471. @rddit
472. @VaporwaveAesthetics
473. @r_overwatch
474. @rtf2memes
475. @r_battlecats
476. @Chainsaw_Man_Topic
477. @r_usenet
478. @r_egg_irl
479. @r_kcv
480. @dailyfoodporn
481. @r_sdarksouls
482. @r_googleplaydeals
483. @r_notinteresting
484. @r_dota2
485. @okbuddyretardd
486. @r_cricket
487. @attack_on_titan_topic
488. @PraiseTheCameraMan
489. @memanon
490. @r_rimesegate
491. @r_travis_scott
492. @r_kemonomimi
493. @whitepeopletweets
494. @r_latestagecapitalism
495. @rExmuslim
496. @r_okbuddyfresca
497. @RedditHistory
498. @r_apphookup
499. @ThereWasAnAttempt
500. @rdataisbeautiful
201. @reddit_brasil
202. @reddit_pride
203. @r_nootropics
204. @mikuichika_nakano
205. @r_ShitpostTC
206. @r_arma
207. @r_youshouldknow
208. @r_psychology1
209. @r_HistoryAnimemes
210. @r_gharkekalesh
211. @r_diy
212. @rStableDiffusion
213. @BrandNewSentence
214. @r_tensei
215. @stablediffusion_r
216. @r_TrashTaste
217. @r_technicallythetruth
218. @r_furrypasta
219. @holdmycosmo
220. @r_embedded
221. @worldnews_reddit
222. @fakealbumcovers
223. @r_tylerthecreator
224. @r_mlp
225. @r_youtubehaiku
226. @r_crappydesign
227. @r_coys
228. @wutttttttt
229. @rAnarchism
230. @trans_memes
231. @fate_hot
232. @r_wheredidthesodago
233. @GnarMains
234. @Mapporncirclejerk
235. @redditpiracy
236. @r_fantheories
237. @CricketShitpost
238. @r_TechSupportGore
239. @r_ToolBand
240. @r_dotnet
241. @r_privacy
242. @r_Tipovi
243. @r_redpillmalayalam
244. @r_digimon
245. @r_technology
246. @r_Bloodborne
247. @r_stonks
248. @imaginarylands
249. @r_outrun
250. @r_opm
251. @r_SlimeRancher
252. @r_Ferrets
253. @r_SuperSentai
254. @reddit_animalsbeingderps
255. @r_trackers
256. @r_mwiii
257. @rdogelore
258. @AllTwitter
259. @r_breadtube
260. @r_badcode
261. @r_suicidewatch
262. @r_animearmpits
263. @Windows11Group
264. @chainsawfolk
265. @r_oneshot
266. @r_wallpapers
267. @r_Windows_Redesign
268. @r_tupac
269. @r_IKEAhacks
270. @r_vinyl
271. @r_trashpandas
272. @footballmanagergames
273. @r_simpsonshitpost
274. @r_chodi
275. @CanalLixo
276. @r_araragi
277. @r_MinecraftMemes
278. @r_programmerhumor
279. @jenkinsci
280. @reddit_androiddev
281. @dailygratitudee
282. @r_chemistry
283. @r_abandoned
284. @animals_telegram
285. @loliconsunite
286. @wallstreetnewsitalia
287. @minimalwallz
288. @r_workreform
289. @R_Punny
290. @r_zargoryangalaksisi
291. @r_imaginarylandscapes
292. @r_indiangaming
293. @MoviePosterTG
294. @r_Julia
295. @r_rainbow6
296. @r_radiocontrol
297. @r_imgoingtohellforthis
298. @reddit_gif
299. @lyricalquotes
300. @r_PoliticalMemes