ΒΆPaper Feed

Issue 37 Β· Sep 7–13, 2026

Week 2026-W37

0 papers scanned 0 shortlisted 0 picked $2.22 spent

Projects

A strong week for open releases: DeepSeek's million-context multimodal flagship, a genuinely new edge-inference approach, and an unusual cluster of fly-connectome-as-computer experiments. Audio/video also delivered with an editable open song generator and a training-free camera-control world model.

  1. HF model AI / ML trending #26 β™₯ 4,424 ↓ 1,294,550 βœ“ read

    deepseek-ai/DeepSeek-V4.1-Flash

    image-text-to-text Β· transformers

    This is the week's most consequential release: a 552B multimodal MoE with million-token context whose real story is the systems architecture β€” causal encoder-decoder, FP4 KV caching, and sparse-index reuse compressing persistent KV state to ~890 bytes/token. That combination could reset expectations for long-context, input-heavy multimodal inference.

    Look for Verify the KV-compression and long-context quality claims against independent evals, and check whether the custom serving stack is practical outside DeepSeek's own infrastructure.

    3 min read Β·Hugging Face β†— Β·mit

  2. GitHub Neuroscience β˜… 16 βœ“ read

    suanmiao/fly-self-driving

    A fruit fly connectome (165k neurons, 25.6M synapses) trained to drive a simulated street from pixels. Code, patches, renderer, results.

    A recurrent network hard-constrained to the measured 165k-neuron Drosophila connectome, with only synaptic gains learned, drives a simulated car from pixels with 58/60 collision-free held-out runs β€” a concrete test of whether real biological wiring supports closed-loop visual control. Shuffled-wiring baselines and released code make it far more than a stunt.

    Look for Single-seed simulation results and how much heavy lifting the learned gains and DAgger do versus the connectome topology itself β€” check the shuffled-control gap carefully.

    3 min read Β·GitHub β†— Β·PythonΒ·MIT

  3. HF model Speech / Video trending #11 β™₯ 957 ↓ 18,759 βœ“ read

    m-a-p/YuE2-3B

    text-to-audio

    An open 3B text-to-song model generating 48 kHz stereo vocals+accompaniment, with a genuinely new interface: inspectable, editable ABC symbolic plans and an agentic revision loop before acoustic synthesis. Local inference on a 24GB GPU makes it the most usable open music generator to date, squarely in the reader's audio interests.

    Look for Compare vocal/mix quality against Suno-class proprietary systems (see WildSongBench P53) and check the license terms for generated audio.

    3 min read Β·Hugging Face β†— Β·cc-by-nc-4.0

  4. GitHub Robotics β˜… 354 βœ“ read

    showlab/Show-Harness

    Just a VLM Agent Can Play Robots

    A clean framing for embodied agents: the VLM emits incremental semantic actions and deterministic embodiment-specific interpreters execute them, shared across Franka, Piper, ManiSkill, and Isaac Lab. The release is unusually complete β€” zero-shot frontier-VLM control, small-VLM fine-tuning, adapters, data, and browser-based demonstration collection without hardware.

    Look for How far the semantic-action vocabulary stretches beyond pick-and-place style tasks, and real-robot success rates versus simulation-heavy demos.

    3 min read Β·GitHub β†— Β·PythonΒ·Apache-2.0

  5. HF model AI / ML trending #2 β™₯ 2,214 ↓ 8,109 βœ“ read

    Edge0/Edge0-35B-A3B-preview

    text-generation Β· mlx

    Streaming 4-bit MoE experts from SSD with a learned one-step-ahead prerouter and Recover-LoRA adapters puts a 35B sparse model in under 3 GiB active memory at ~15 tok/s on Apple Silicon β€” a real jump for edge inference, not another quantized checkpoint. The 79.2 vs 83.2 benchmark gap against the FP16 base is a plausible trade.

    Look for Preview-stage, self-reported numbers tied to the MLX framework; check SSD wear/latency behavior and whether the approach ports beyond Apple Silicon (the 8B sibling P26 runs in ~1 GiB).

    3 min read Β·Hugging Face β†— Β·apache-2.0

  6. GitHub Speech / Video β˜… 83 βœ“ read

    Westlake-AGI-Lab/WorldinWorld

    Official implementation of WorldinWorld

    Re-filming ordinary videos from arbitrary camera paths using a frozen 14B video world model plus depth warping β€” no training or fine-tuning β€” is a genuinely new capability with runnable code, not just a paper. Bullet-time and free-camera re-cinematography from real footage is a meaningful demonstration of world models as controllable renderers.

    Look for Requires ~86 GB of weights and an 80 GB GPU; check geometric consistency on large camera excursions where depth-warping priors break down.

    3 min read Β·GitHub β†— Β·Python

Also notable

The shortlist: top candidates that survived triage Β· Archive