Eliciting Complex Spatial Reasoning in MLLMs through Wide-Baseline Matching

https://aim-uofa.github.io/reasonmatch/

Outperforms all other open- and closed-source spatial reasoning models, but still inferior to human accuracy. Uses #LMDB

ReasonMatch — Eliciting Complex Spatial Reasoning in MLLMs through Wide-Baseline Matching

CVPR 2026 · ReasonMatch-Bench (2,810 image pairs) and DCRL reach 70.5 F1, outperforming evaluated open- and closed-source MLLM baselines.

Dydra

A cloud-hosted RDF triplestore written in Common Lisp with a revisioned graph store that maintains versioned snapshots of previous states, queryable via a REVISION clause in SPARQL. Uses #LMDB for storage and RonDB for scaled deployments. Supports MQTT streaming for incremental changes.

https://gdb-engines.com/db/dydra/

Dydra — Graph Database | GDB-Engines

A cloud-hosted RDF triplestore written in Common Lisp with a revisioned graph store that maintains versioned snapshots of previous states, queryable via a REVISION clause in SPARQL. Uses LMDB for storage and RonDB for scaled deployments. Supports MQTT streaming for incremental changes.

GDB-Engines
@dplattsf this guy used Nvidia's Locate Anything tool to identify dogs & cats in images https://medium.com/@hitorunajp/i-tried-nvidia-locateanything-3b-7a2b86b511a0 (uses #LMDB )
I tried NVIDIA LocateAnything-3B

How to use the newest model and build an object detector on Colab

Medium

A high-performance jpeg decode library for AMD’s GPUs

https://packages.cachyos.org/package/cachyos-extra-v3/x86_64_v3/rocal

I don't know why a jpeg decoder depends on #LMDB but ok...

rocal - cachyos-extra-v3 (x86_64_v3)

A high-performance jpeg decode library for AMD’s GPUs

- Storage implemented atop #LMDB
- CLI, API and App servers written in #Rust
- Guest code execution sandboxed using #WebAssembly
- Queryable structured event logs
- Automatic TLS via Let's Encrypt

SpMAP: Transparent Sparsity for LLMs

Large Language Models (LLMs) present significant challenges when deployed on client devices, primarily due to their large weight sizes and computational demands.

SpMAP is a lightweight method that supports sparse weight tensors using existing virtual memory (VM) features. The key idea is to instantiate a sparse tensor by stacking many file-backed memory mappings atop one anonymous mapping,

https://dl.acm.org/doi/10.1145/3745756.3809197

References #LMDB . mmap ftw!

If you remember place.live, this site is similar but purely text based. Built on #LMDB, runs on a €5/month vps https://news.ycombinator.com/item?id=48328843
A Trillion Characters | Hacker News

I'm surprised the https://social.cologne/@bareos folks aren't making hay from this rsync uproar, since they're devoted to backup/restore. They use #LMDB by the way.
Bareos (@[email protected])

212 Posts, 99 Following, 109 Followers · Backup Recovery Open Source Software www.bareos.com

Mastodon

What if someone looked at Linux/POSIX mmap (and the OS's VMM subsystem) and challenged themselves with, "Hey what if we added the bare minimum additional C code on top of that to turn it into a true ACID KV database?"

and a kinda spiritual successor to and upgrade from classic BerkeleyDB of old

thats LMDB in a nutshell

one of the most brilliant designs I've learned about in a long time. very happy to add to my toolbox!

#LMDB

http://www.lmdb.tech/

Hallo-Live: Real-Time Streaming Joint Audio-Video Avatar Generation

The method adopts a causal dual-stream DiT model to generate synchronized avatar video and speech in a streaming manner. Hallo-Live reaches 20.38 FPS with 0.94 s latency on two NVIDIA H200 GPUs, while preserving strong lip-sync accuracy, visual fidelity, and speech quality.
Built on #LMDB

https://github.com/fudan-generative-vision/Hallo-Live

GitHub - fudan-generative-vision/Hallo-Live: Hallo-Live: Real-Time Streaming Joint Audio-Video Avatar Generation

Hallo-Live: Real-Time Streaming Joint Audio-Video Avatar Generation - fudan-generative-vision/Hallo-Live

GitHub