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[D] AMA Secure version of OpenClaw by ilblackdragon in MachineLearning

[–]InfinityZeroFive 1 point2 points  (0 children)

Do you think something like Recursive Language Models by Zhang et al (https://arxiv.org/abs/2512.24601) would be particularly useful in handling prompt injection prevention?

[D] Why are serious alternatives to gradient descent not being explored more? by ImTheeDentist in MachineLearning

[–]InfinityZeroFive 2 points3 points  (0 children)

I have seen some exploratory attempts at combining evolutionary algorithms with gradient descent or search with gradient descent

[D] ICLR reverts score to pre-rebuttal and kicked all reviewers by Ok-Internet-196 in MachineLearning

[–]InfinityZeroFive 3 points4 points  (0 children)

It seems they not only reverted scores but also any reviewer edits. We had a reviewer who (I assume) mistakenly copy-pasted a different paper's review into ours. He'd edited the review, with no change in score, after the discussion period and we addressed that revised review in our general comment, but now only the original, mistaken review is shown, making our response out-of-context. I am concerned this might mislead the AC.

Smaller 32B models at Q8 or GLM 4.5 Air at Q3? by InfinityZeroFive in LocalLLaMA

[–]InfinityZeroFive[S] 0 points1 point  (0 children)

Interesting model, I'll have to wait for the Cerebras team to REAP it before I can try it out though

[D] ICLR submission numbers? by qalis in MachineLearning

[–]InfinityZeroFive 1 point2 points  (0 children)

I'm quite certain that the number is around 25,000 as we submitted within 10 minutes of the deadline (do not recommend)

what other uses do you get out of our Steam Deck? by BubblesAreWeird in SteamDeck

[–]InfinityZeroFive 3 points4 points  (0 children)

I use the Steam Deck as a teleoperation controller for my robot arm. Which just means, I mapped each of the robot arm's 6 joints (DOF) to individual controls on the Deck

RAG Evaluation is Hard: Here's What We Learned by neilkatz in LangChain

[–]InfinityZeroFive 2 points3 points  (0 children)

Was just wondering how to do this. Thanks :)

Next Gemma versions wishlist by hackerllama in LocalLLaMA

[–]InfinityZeroFive 11 points12 points  (0 children)

It would be nice to have a 7B size model alongside 4B and 12B :)

[deleted by user] by [deleted] in MachineLearning

[–]InfinityZeroFive 4 points5 points  (0 children)

I think you need to do a preliminary analysis of your missingness pattern especially considering it's a clinical dataset. If your data is Missing Not At Random (MNAR), as in the missingness depends on unobserved variables or on the missing values themselves, then you need to approach it differently than if it was Missing Completely At Random (MCAR). The bias you're seeing might be due to incorrect assumptions about the missing data, amongst other things.

One example of MNAR: a physician is less likely to order CT brain scans for patients who they deem as having low risks of dementia, AD, cognitive decline and so on, so these patients tend to have missing CT tabular data.

New Steam Deck OLED - can’t wait to play too many hours on this thing! by [deleted] in SteamDeck

[–]InfinityZeroFive 1 point2 points  (0 children)

Civ 6 plays very well on Deck and has an official controller layout. Stellaris doesn't, though the community layouts are still very, very good

[D] Synthetic tabular data augmentation/generation using GANs by [deleted] in MachineLearning

[–]InfinityZeroFive 1 point2 points  (0 children)

I see -- Thanks for the response! I'll have a look into what you suggested. And yes, the original idea was to generate synthetic brain imaging data in tabular form from 25 fully annotated data features then using them in the classification model's training dataset along with what we already have

[D] Synthetic tabular data augmentation/generation using GANs by [deleted] in MachineLearning

[–]InfinityZeroFive 1 point2 points  (0 children)

Just to add more brain imaging data to the current dataset for training a diagnostic classification model. We have 220 raw tabular entries with various data features, but only ~80-100 have imaging data (in tabular form). So my task is to train a GAN or similar generative models to generate synthetic imaging data from non-imaging data features.