circuithunter

5 ms·

1.
DataSmith: Automating Data Research to Beat Post-Train Bench(datologyai.com)
2 points by circuithunter 1mo ago|0 comments
2.
DatBench: Discriminative, faithful, and efficient VLM evaluations(arxiv.org)
18 points by circuithunter 9mo ago|0 comments
3.
BeyondWeb: Lessons from Scaling Synthetic Data for Trillion-Scale Pretraining(arxiv.org)
4 points by circuithunter 1y ago|0 comments
4.
Models are what they eat: automatic data curation for LLMs(datologyai.com)
2 points by circuithunter 2y ago|0 comments
5.
Are all negatives created equal in contrastive instance discrimination?(arxiv.org)
1 points by circuithunter 6y ago|0 comments
6.
Training BatchNorm and Only BatchNorm: On the Power of Random Features in CNNs(arxiv.org)
4 points by circuithunter 7y ago|0 comments
7.
The Early Phase of Neural Network Training(arxiv.org)
3 points by circuithunter 7y ago|0 comments
8.
by circuithunter 7y ago
This is a really nice paper which asks some critical questions for the future of NAS research. However, it's important to note that this paper doesn't show that NAS algorithms as originally designed, with completely independent tr
9.
Remove, Reduce, Inform: New Steps to Manage Problematic Content(newsroom.fb.com)
2 points by circuithunter 7y ago|0 comments
10.
Google Founders Have Skipped All of the Company's 2019 Town Hall Meetings(buzzfeednews.com)
6 points by circuithunter 7y ago|0 comments
11.
“Men Are Scum”: Inside Facebook's War on Hate Speech(vanityfair.com)
13 points by circuithunter 8y ago|2 comments
12.
Why Fears of Fake News Are Overhyped(medium.com)
1 points by circuithunter 8y ago|0 comments
13.
What Is Facebook Doing to Address the Challenges It Faces?(newsroom.fb.com)
1 points by circuithunter 8y ago|0 comments
14.
Facebook hires prominent privacy managers ahead of end-to-end encryption rollout(venturebeat.com)
2 points by circuithunter 8y ago|0 comments
15.
AI Has Started Cleaning Up Facebook, but Can It Finish?(wired.com)
1 points by circuithunter 8y ago|0 comments
16.
Facebook tries to explain why companies could erase your messages(nbcnews.com)
3 points by circuithunter 8y ago|0 comments
17.
Facebook “partner” arrangements: Are they as bad as they look?(arstechnica.com)
1 points by circuithunter 8y ago|0 comments
18.
Leaked Audio Reveals Google's Efforts to Woo Conservatives(wired.com)
3 points by circuithunter 8y ago|0 comments
19.
How Can DNN Similarity Help Us Understand Training and Generalization?(ai.googleblog.com)
2 points by circuithunter 8y ago|0 comments
20.
DeepMind – On the importance of single directions for generalization(arxiv.org)
8 points by circuithunter 9y ago|0 comments
21.
Understanding Deep Learning Through Neuron Deletion – DeepMind(deepmind.com)
14 points by circuithunter 9y ago|0 comments
22.
DeepMind expands to Canada with new research office in Edmonton, Alberta(deepmind.com)
7 points by circuithunter 9y ago|1 comments
23.
by circuithunter 10y ago
Machine translation is a big one. See the recent NY Times feature [1] and the arxiv paper [2]. Automated image captioning is another (used extensively by Facebook). [1] https://www.nytimes.com/2016/12/14/magaz
24.
by circuithunter 10y ago
There's actually quite a bit of evidence suggesting that brains, both behaviorally and mechanistically, are Bayesian [0]. As for your second point, assuming that humans are Bayesian, there are many reasons why people would have variabi
25.
Clustering subreddits by common word usage(arimorcos.com)
2 points by circuithunter 11y ago|0 comments
26.
Creating a Reddit dataset(arimorcos.com)
1 points by circuithunter 12y ago|0 comments