Skip to main content

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 BDHCQ

model = BDHCQ()

ids = torch.randn(2, 1024)

logits = model(ids)

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}
}

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-0.0.2.tar.gz (7.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

bdh_cq-0.0.2-py3-none-any.whl (7.2 kB view details)

Uploaded Python 3

File details

Details for the file bdh_cq-0.0.2.tar.gz.

File metadata

  • Download URL: bdh_cq-0.0.2.tar.gz
  • Upload date:
  • Size: 7.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.17

File hashes

Hashes for bdh_cq-0.0.2.tar.gz
Algorithm Hash digest
SHA256 78a91b5e6ec5165c94b3e2875f83e8d3bb905388a33f2af6505f64565955235e
MD5 0e83303f8c72942d31c8125958f34cd1
BLAKE2b-256 48b669360403d8f7a0f6b1005f32925f369a5d17d52175ac23f0959f9c97c108

See more details on using hashes here.

File details

Details for the file bdh_cq-0.0.2-py3-none-any.whl.

File metadata

  • Download URL: bdh_cq-0.0.2-py3-none-any.whl
  • Upload date:
  • Size: 7.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.17

File hashes

Hashes for bdh_cq-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 3c86b00d418dc744b2ba1adbfddf9e23f7d7f047cd259f2314e2463629383c55
MD5 8822bdfc48e31973061b105ed5ef6ff2
BLAKE2b-256 0a94f15e5992c8777adacd0883b427e135d9597f29eb2885100dc919f11f166d

See more details on using hashes here.

Release history Release notifications | RSS feed

0.0.20

2 files

0.0.19

2 files

0.0.17

2 files

0.0.16

2 files

0.0.15

2 files

0.0.14

2 files

0.0.12

2 files

0.0.11

2 files

0.0.10

2 files

0.0.9

2 files

0.0.7

2 files

0.0.6

2 files

0.0.5

2 files

0.0.4

2 files

0.0.3

2 files

This release

0.0.2 This release

2 files

0.0.1

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page