abhgh

8 ms·

1.
by abhgh 5d ago
Was looking for a video on this specific work, but only found this [1] where the English translation seems AI-generated. It reminded me of thermoacoustic refrigeration which I found cool (heh) when I had encountered it many years ago - wher
2.
by abhgh 14d ago
The searchable term is "Self-preference Bias" :) My first encounter with any kind of study was the G-Eval paper [1]. They study whether their LLM judge prefers human or LLM-generated summaries (answer: it's the latter). [1] S
3.
by abhgh 18d ago
What you call "Weathering" has been a constant gripe of mine. We have LLM-driven softwares toward that almost seem to start from scratch every time a request comes in - there are mechanisms to learn or generalize, like writing out
4.
by abhgh 2mo ago
Cool project! I tried something similar a while ago [1] - I wanted to load up an embedding model and semantically order texts, all in the browser. So I pull ONNX weights from HuggingFace (MPNet, MiniLM), use Transformers.js to embed, and us
5.
by abhgh 3mo ago
Oh wow, they are still around! I used to keep a Knoppix disk around for times when my desktop would run out of space and wouldn't boot (if I remember right). Boot it with Knoppix, delete some files, and then boot it normally!
6.
by abhgh 3mo ago
You usually see this kind of analyses in conference papers, esp. if they have a datasets track. The NeurIPS Datasets & Benchmarks (D&B) track is a good example. But you will have to monitor the proceedings yourself closely - there i
7.
by abhgh 3mo ago
These "You're right to push back" scenarios are scary for me. I mostly code ML implementations, and some of the errors Claude Code (CC - have only used Opus 4.7) makes are very sneaky, and if you don't have sufficient ex
8.
by abhgh 3mo ago
Reg PRs - for the ones with complex requirements what I am seeing is that time to initial PR is very short, and a ping-pong between the reviewer and developer begins, because in my cases (not all) the developer vibe-coded parts, and they di
9.
by abhgh 4mo ago
I should go back to this (like some of the other comments suggest) - I think there is potential in suggesting multiple lines, and I would have really loved it to work, but it is clear that their ux testing was poor.
10.
by abhgh 4mo ago
I am not particularly bothered by the speed but the AI suggestion clutter is quickly becoming an issue for me :( I type fragments of a line and it will suggest the next 5-6 lines. They may not be outright wrong, but they might not represent
11.
by abhgh 7mo ago
They are great for specialized use-cases: (a) where the problem is not hard enough (you don't need reasoning), or (b) diverse enough (you don't need a world model), (c) you want cheap inference (and you can make it happen hardware
12.
by abhgh 7mo ago
I notice you mentioned dspy - do you also support prompt optimization?
13.
by abhgh 8mo ago
This is an amazing quote - thank you. This is also my argument for why I can't use LLMs for writing (proofreading is OK) - what I write is not produced as a side-effect of thinking through a problem, writing is how I think through a
14.
The Gumbel-Max Trick(blog.quipu-strands.com)
2 points by abhgh 8mo ago|0 comments
15.
by abhgh 8mo ago
I once modeled user journeys on a website using fancy ML models that honored sequence information, i.e., order of page visits, only to be beaten by bag-of-words (i.e., page url becomes a vector dimension, but order is lost) decision tree mo
16.
by abhgh 9mo ago
I use Claude Code within Pycharm and I see the git diff format for changes there. EDIT: It shows the side-by-side view by default, but it is easy to toggle to a unified view. There's probably a way to permanently set this somewhere.
17.
by abhgh 9mo ago
Thank you. Your comment about LLMs to semantically parse diverse data, as a first step, makes sense. In fact come to think of it, in the area of prompt optimization too - such as MIPROv2 [1] - the LLM is used to create initial prompt guesse
18.
by abhgh 9mo ago
I was not aware this existed and it looks cool! I am definitely going to take out some time to explore it further. I have a couple of questions for now: (1) I am confused by your last sentence. It seems you're saying embeddings are a s
19.
by abhgh 10mo ago
Thanks for the example. Yes, true, this is for expensive functions - to be precise functions that depend on data that is hard to gather, so you interleave the process of computing the value of the function with gathering strategically just
20.
by abhgh 10mo ago
Timefold looks very interesting. This might be irrelevant but have you looked at stuff like InfoBax [1]? [1] https://willieneis.github.io/bax-website/
21.
by abhgh 10mo ago
You don't - the way I use LLMs for explanations is that I keep going back and forth between the LLM explanation and Google search /Wikipedia. And of course asking the LLM to cite sources helps. This might sound cumbersome but with
22.
by abhgh 10mo ago
Love awk. In the early days of my career, I used to write ETL pipelines and awk helped me condense a lot of stuff into a small number of LOC. I particularly prided myself in writing terse one-liners (some probably undecipherable, ha!); but
23.
UMAP Projections of Animals to 2D(duhaime.s3.amazonaws.com)
1 points by abhgh 10mo ago|0 comments
24.
by abhgh 11mo ago
I'm curious to know if Anthropic mentions anywhere that they use speculative decoding. For OpenAI they do seem to use it based on this tweet [1]. [1] https://x.com/stevendcoffey/status/1853582548225683814
25.
by abhgh 11mo ago
Wouldn't this be an optimization problem, that's to say, something like z3 should be able to do - [1], [2]? I was about to suggest probabilistic programming, e.g., PyMC [3], as well, but it looks like you want the optimization to
26.
by abhgh 1y ago
Hadn't seen this before, very nice read, thank you!
27.
by abhgh 1y ago
Thank you for your kind comment!
28.
by abhgh 1y ago
Aside from secondmind [1] I don't know of any companies (only because I haven't looked)... But if I had to look for places with strong research culture on GPs (I don't know if you're) I would find relevant papers on arxi
29.
by abhgh 1y ago
This is the definitive reference on the topic! I have some notes on the topic as well, if you want something concise, but that doesn't ignore the math [1]. [1] https://blog.quipu-strands.com/bayesopt_1_key_ideas_GPs#gau
30.
by abhgh 1y ago
Active Learning is a very tricky area to get right ... over the years I have had mixed luck with text classification, to the point that my colleague and I decided to perform a thorough empirical study [1], that normalized various experiment

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