BDH-CQ (wip)
Implementation of BDH-CQ: In-Context Learning with Recurrent Latent Reasoning, proposed by Pathway Research
Install
$ pip install bdh-cq
Usage
import torch
from bdh_cq import BDH
model = BDH(
dim = 512,
num_tokens = 20_000
)
ids = torch.randint(0, 20_000, (2, 1024))
logits = model(ids) # (2, 1024, 20_000)
Citations
@misc{engdahl2026bdhcq,
title = {BDH-CQ: In-Context Learning with Recurrent Latent Reasoning},
author = {Björn Engdahl and Adrian Kosowski and Jan Chorowski and Zuzanna Stamirowska and Przemysław Uznański and Junlin Jiang and Rohan Phadke and Remigiusz Kinas and Richard Zhong},
year = {2026},
eprint = {2608.09888},
archivePrefix = {arXiv},
primaryClass = {cs.NE},
url = {https://arxiv.org/abs/2608.09888}
}
1 maintainer
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
bdh_cq-0.0.12.tar.gz
(12.3 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
bdh_cq-0.0.12-py3-none-any.whl
(12.3 kB
view details)
File details
Details for the file bdh_cq-0.0.12.tar.gz.
File metadata
- Download URL: bdh_cq-0.0.12.tar.gz
- Upload date:
- Size: 12.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via:
uv/0.8.17
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2e2f8ddf8f7a2527760c87b19a8d51cfa054be7f904372eb6c6748b0fc82b2cd
|
|
| MD5 |
68b285c43bcfeed510fdb4930c2b5964
|
|
| BLAKE2b-256 |
39e1846b28bf7325f5ffbd65e4bb597eacbdb71e8ba0eddbfc3b4835a7ec6be0
|
File details
Details for the file bdh_cq-0.0.12-py3-none-any.whl.
File metadata
- Download URL: bdh_cq-0.0.12-py3-none-any.whl
- Upload date:
- Size: 12.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
uv/0.8.17
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d62d1ae8fec8ffde7018f9584743c3009b10cd38cab742965761c99df0fc458e
|
|
| MD5 |
ae04da19c47b11fe18197a260aeda712
|
|
| BLAKE2b-256 |
fd47b7fbf63cd5788154323f6495bc12bfa8edd4617e924cc4552c99bbf0b266
|
