adlumal

3 ms·

1.
Triplet-extract is a GPU-accelerated Python implementation of Stanford OpenIE(github.com)
2 points by adlumal 11mo ago|1 comments
2.
by adlumal 11mo ago
I built a pure-Python port of Stanford OpenIE that GPU-accelerates the natural-logic forward-entailment search itself (via batched reparsing) rather than replacing it with a neural model. This often yields more triplets than standard OpenIE
3.
Building Fast Vector Search for Legal Documents(huggingface.co)
3 points by adlumal 1y ago|1 comments
4.
by adlumal 1y ago
I benchmarked embedding APIs for speed, compared local vs hosted models, and tuned USearch for sub-millisecond retrieval on 143k chunks using only CPU. The post walks through the results, trade-offs, and what I learned about embedding API t
5.
by adlumal 1y ago
This may be due to changes in the sources used for remotes over time perhaps. > There was a slight loss of -0.6 dB per decade in the cumulative threshold, but regression analysis showed the lack of a significant correlation between age
6.
by adlumal 1y ago
Could this be a symptom of the free tier of ChatGPT, but not all LLMs? I’ve recently been a heavy user of Anthropic’s Claude and I don’t believe I’ve seen too many of these in my chats. Though this may be because I haven’t asked Claude to w
7.
by adlumal 1y ago
Having done some work in the legal AI field, I wonder how this classifier deals with issues of transparency, explainability and ultimately trust? It’s valuable to have some idea of how a proceedings might unfold but from my experience most
8.
by adlumal 2y ago
This paper is looking to be pretty significant. Was hoping to find some discussion here as well!
9.
Show HN: I made a state machine framework for guided conversations with LLMs(github.com)
19 points by adlumal 2y ago|3 comments