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yeesian

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Goodbye Python-Mip?

oberdieck.dk
1 points·by yeesian·2 tahun yang lalu·0 comments

Esmeralda

esmeralda.org
20 points·by yeesian·2 tahun yang lalu·18 comments

Coding Patterns – The CP-SAT Primer

d-krupke.github.io
2 points·by yeesian·2 tahun yang lalu·0 comments

A Strengthened Implementation of CuPDLP for Linear Programming by C Language

arxiv.org
1 points·by yeesian·2 tahun yang lalu·0 comments

Understanding the Decline of Impact Factors in Informs Journals

pubsonline.informs.org
1 points·by yeesian·2 tahun yang lalu·0 comments

Towards Large Language Models as Copilots for Theorem Proving in Lean

arxiv.org
3 points·by yeesian·2 tahun yang lalu·0 comments

Exploring the Limits of Transfer Learning with a Unified Transformer (2019)

arxiv.org
12 points·by yeesian·2 tahun yang lalu·1 comments

How do I get started with Jax on TPU VMs

github.com
23 points·by yeesian·2 tahun yang lalu·17 comments

Linearity of Relation Decoding in Transformer Language Models

lre.baulab.info
1 points·by yeesian·2 tahun yang lalu·0 comments

LLM Evaluation: Everything You Need to Run, Benchmark Evals

arize.com
2 points·by yeesian·2 tahun yang lalu·0 comments

Speech and Language Processing (3rd ed. draft)

web.stanford.edu
214 points·by yeesian·2 tahun yang lalu·32 comments

The Greatest Meme Template

readtrung.com
31 points·by yeesian·2 tahun yang lalu·9 comments

Coalescence: Making LLM inference 5x faster

blog.dottxt.co
5 points·by yeesian·2 tahun yang lalu·0 comments

Fast JSON Decoding for Local LLMs with Compressed Finite State Machine

lmsys.org
1 points·by yeesian·2 tahun yang lalu·0 comments

Generative Uncertainty

vaughntan.org
7 points·by yeesian·3 tahun yang lalu·0 comments

[untitled]

1 points·by yeesian·3 tahun yang lalu·0 comments

My Life as a Con Man (2020)

swyx.io
4 points·by yeesian·3 tahun yang lalu·0 comments

Using llama-cpp-Python grammars to generate JSON

til.simonwillison.net
2 points·by yeesian·3 tahun yang lalu·0 comments

Finite-State Transducers in Language and Speech Processing (1997)

aclanthology.org
3 points·by yeesian·3 tahun yang lalu·1 comments

Finite-State Transducer

en.wikipedia.org
6 points·by yeesian·3 tahun yang lalu·1 comments

comments

yeesian
·3 tahun yang lalu·discuss
FST implementation in Rust: https://news.ycombinator.com/item?id=38096511
yeesian
·3 tahun yang lalu·discuss
Relatedly (from a data structures perspective): https://news.ycombinator.com/item?id=10551280
yeesian
·3 tahun yang lalu·discuss
This was posted in the past (https://news.ycombinator.com/item?id=20502032); just re-posting now in light of their potential application to LLM grammars (https://news.ycombinator.com/item?id=38082219 for context)
yeesian
·3 tahun yang lalu·discuss
Relatedly:

Llama: Add grammar-based sampling - https://news.ycombinator.com/item?id=36819906 (105 comments)

ReLLM: Exact Structure for Large Language Model Completions - https://news.ycombinator.com/item?id=35829399 (13 comments)

Show HN: Structured output from LLMs without reprompting - https://news.ycombinator.com/item?id=36750083 (54 comments)

Show HN: LLMs can generate valid JSON 100% of the time - https://news.ycombinator.com/item?id=37125118 (303 comments)

A guidance language for controlling LLMs - https://news.ycombinator.com/item?id=35963936 (190 comments)

LMQL: A query language for programming (large) language models - https://news.ycombinator.com/item?id=35956484 (12 comments)
yeesian
·3 tahun yang lalu·discuss
https://archive.ph/hlh06
yeesian
·3 tahun yang lalu·discuss
https://cloud.google.com/vertex-ai/docs/start/explore-models...
yeesian
·3 tahun yang lalu·discuss
https://cloud.google.com/vertex-ai/docs/start/explore-models...
yeesian
·3 tahun yang lalu·discuss
(This is more of a link-dump than a paper discussion --)

For the line of inquiry w.r.t tensor compilers and MLIR/LLVM (linalg, polyhedral, [sparse_]tensor, etc), I personally found the following really helpful: https://news.ycombinator.com/item?id=25545373 (links to a survey), https://github.com/merrymercy/awesome-tensor-compilers

I also have an interest in the community more widely associated with pandas/dataframes-like languages (e.g. modin/dask/ray/polars/ibis) with substrait/calcite/arrow their choice of IR. Some links: https://github.com/modin-project/modin, https://github.com/dask/dask/issues/8980, https://news.ycombinator.com/item?id=16510610, https://news.ycombinator.com/item?id=35521785

I broadly classify them as such since the former has a stronger disposition towards linear/tensor-algebra, while the latter towards relational algebra, and it isn't yet clear (to me) how well innovations in one carry over to the other (if they do), and hence I'm also curious to hear more about proposals for a unified language across linalg and relational alg (e.g. https://news.ycombinator.com/item?id=36349015).

I'm particularly interested in pandas precisely because it seems to be right at the intersection of both forms of algebra (and draws a strong reaction from people who are familiar/comfortable with one community and not the other). See e.g. https://datapythonista.me/blog/pandas-20-and-the-arrow-revol... and https://wesmckinney.com/blog/apache-arrow-pandas-internals/
yeesian
·3 tahun yang lalu·discuss
Previous discussion: https://news.ycombinator.com/item?id=12399580
yeesian
·3 tahun yang lalu·discuss
That's cool, thanks for sharing! Do you know how close they are to their example use cases [1]? So far I've only been able to find a tool for calcite SQL parsing [2] but not the portion connecting to Arrow C++ compute kernel yet.

[1]: https://substrait.io/#example-use-cases [2]: https://substrait.io/tools/producer_tools/