Source HF Daily Papers
Training Object Permanence in World Models206 upvotes2 comments
31 authorsno limits stated
What we saw
“Object permanence and solidity are hallmarks of human cognitive priors. Recent studies show that video generation models, a par…”
Published 2026-09-22
Fetched 2026-09-25 23:01 UTC · 9ddf4b0029a949c3
Torn from — the abstract
Thread ↗ text-rankingcontrastive-lmSource Hugging Face
Contrastive-LM/CLM-v0.1-8B416 likes766 downloads
apache-2.0built on Qwen3-8B
What we saw
This source gives a title and a link, nothing to quote.
They claim — Terminal-Bench 2.1 (87.6%), 4–6× faster than Jev.
Published 2026-09-21
Fetched 2026-09-25 23:01 UTC · 96c8aa6a5329130e
Torn from — the model card
image-text-to-texttransformersSource Hugging Face
apple/LensVLM-9B246 likes1.7k downloads
apple-amlrbuilt on Qwen3.5-9B
What we saw
This source gives a title and a link, nothing to quote.
Published 2026-09-21
Fetched 2026-09-25 23:01 UTC · 436cd7dd55e01e86
Torn from — the model card
text-to-imagetransformersSource Hugging Face
SupraLabs/Supra2-IMG150 likes515 downloads
apache-2.0
What we saw
This source gives a title and a link, nothing to quote.
They claim — Supra2-IMG is a tiny 100M parameters text-to-image (T2I) model that has been trained from scratch on high-quality synthetic data and delivers state-of-the-art image quality for its size.
Published 2026-09-21
Fetched 2026-09-27 23:01 UTC · e006b2ea9024da28
Torn from — the model card
Source HF Daily Papers
OmniEcho: Spatial Audio Understanding for Embodied Agents23 upvotes2 comments
13 authorsno limits stated
What we saw
“Humans can effortlessly localize the direction of a sound source and integrate it with visual cues for reasoning, yet this rema…”
Published 2026-09-19
Fetched 2026-09-25 23:01 UTC · ebf4594fa0d2f86a
Torn from — the abstract
Thread ↗ MarkdownaiSource GitHub
pallavi-shekhar/ai-engineering-interview-questions-company-wise1.5k stars144 forks
Apache-2.0Markdownpushed 6d ago
Location, estimated · India
What we saw
“Your Cheat Sheet For AI Engineering Interviews at Top AI Companies - Questions and Answers.”
They claim — How would you cut LLM serving cost by 10x?
Published 2026-09-19
Fetched 2026-09-25 23:01 UTC · 6d945172946e0f37
What the account wrote — Bangalore, India
Torn from — the README
C++apple-siliconSource GitHub
incoai/splash915 stars92 forks
Apache-2.0C++pushed today
Location, estimated · Not stated
What we saw
“A local inference engine for Apple silicon, built around the model.”
They claim — 24 GB Macs can use smaller GGUF variants.
Published 2026-09-18
Fetched 2026-09-26 23:01 UTC · 92d2f0a31d978b91
What the account wrote — The account left it blank
Torn from — the README
PythonSource GitHub
kerpopule/hermes-jev-skills875 stars83 forks
MITPythonpushed today
Location, estimated · Not stated
What we saw
“Jev-powered model routing, memory, compaction, skill selection, computer and browser use for Hermes agents (also Claude Code an…”
They claim — Mailbox sorting (jev mail): the subject and up to 2,500 characters of the body, redacted; the sender's domain (never the mailbox); a local class read off the address alone (automated for …
Published 2026-09-18
Fetched 2026-09-26 23:01 UTC · 1d5e91c79063d0be
What the account wrote — The account left it blank
Torn from — the README
automatic-speech-recognitionsafetensorsSource Hugging Face
moondream/parakeet-redux165 likes2.1k downloads
cc-by-4.0
What we saw
This source gives a title and a link, nothing to quote.
They claim — MacBook Air with the Apple M2 (4 performance and 4 efficiency CPU cores, 10-core GPU), 16 GB unified memory, macOS 15.
Published 2026-09-18
Fetched 2026-09-26 23:01 UTC · 6144a78a085e7fc8
Torn from — the model card
image-text-to-texttransformersSource Hugging Face
XingChen-AGI/TeleOCR617 likes28k downloads
apache-2.0
What we saw
This source gives a title and a link, nothing to quote.
They claim — We evaluated NaviDC-OCR with its native weights, achieving better results than MinerU 2.5 Pro and PaddleOCR-VL 1.6.
Published 2026-08-14
Fetched 2026-09-28 05:05 UTC · e9a2dd67be526bb6
Torn from — the model card
Source TWIML AI
From Voice Agents to AI Avatars with Alexander Smola - #777Sep 16
no limits stated134 words
What we saw
“Voice AI has gotten remarkably good, but natural conversation remains a high bar. Small delays, awkward interruptions, or the w…”
Published 2026-09-16
Fetched 2026-09-16 23:01 UTC · 23f6faf1dc0a63ec
Torn from — the listing only (the original would not open)
Source TechCrunch AI
Source r/LocalLLaMA
Qwen 3.8 27B Running for 63 hours on a RTX 3090 to solve the Riemann hypothesisSep 16
no limits stated216 words
What we saw
“I let Qwen 3.8 27B 4bit quantized with 100K context window run autonomously for 63 hours (50 million+ tokens) to try to solve t…”
They claim — I am really hopeful that one of the unsolved millenium prize problems will be solved by an agent or a swarm of agents powered by an open source model in the next 12 months.
Published 2026-09-16
Fetched 2026-09-16 23:01 UTC · e56d70fcc4431c46
Torn from — the listing only (the original would not open)
Thread ↗ Source r/LocalLLaMA
Xiaomi MiMo 2.6 Live Training DashboardSep 16
What we saw
“Cool to see this as it happens!   submitted by   /u/skeole [link]   [comments]”
Published 2026-09-16
Fetched 2026-09-16 23:01 UTC · 447c6318c53d1050
Torn from — the listing only (the original would not open)
Thread ↗ Source TechCrunch AI
Source AWS ML Blog
Improving HCLS AI reasoning with open-source agent skillsSep 16
states limits3.7k words
What we saw
“AI agents on foundation models often misapply healthcare and life sciences decision frameworks, citing the right guideline but …”
They claim — The collection covers 38 skills across 11 HCLS domains including genomics, drug discovery, claims operations, and medical imaging.
Published 2026-09-16
Fetched 2026-09-16 23:01 UTC · f38341d7421950db
Torn from — the listing only (the original would not open)
Source AWS ML Blog
Fault tolerant distributed training on Amazon EKS using NVRxSep 16
states limits3.1k words
What we saw
“Integrate NVIDIA Resiliency Extension (NVRx) into PyTorch FSDP training on Amazon EKS to overlap checkpoint I/O with training a…”
They claim — Synchronous checkpointing adds a second source of idle time: every save blocks all ranks on I/O, which on the cluster sizes in this post consumed up to 40% of total wall time.
Published 2026-09-16
Fetched 2026-09-16 23:01 UTC · 8f850829b2016926
Torn from — the listing only (the original would not open)
Source Latent Space
Underwriting Superintelligence: Backing Agents you can Sue — Rune Kvist, AIUCSep 16
states limits19k words
What we saw
“AIUC first got our attention with the NFDG backing, and have just announced a $40M series A today, with the most impressive ind…”
They claim — In this episode, the AIUC cofounder joins swyx and Vibhu to announce a new $40M round and explain why companies like Cursor, Harvey, Lovable, and ElevenLabs are increasingly confronting a…
Published 2026-09-16
Fetched 2026-09-16 23:01 UTC · 62deec15f163701c
Torn from — the listing only (the original would not open)
Source OpenAI
Our framework for reporting model misalignmentSep 16
What we saw
“OpenAI shares a framework for tracking, investigating, and disclosing model misalignment, alongside six reports of unexpected o…”
Published 2026-09-16
Fetched 2026-09-16 23:01 UTC · 827a0c403a3c663f
Torn from — the listing only (the original would not open)
Source OpenAI
Helping older adults use AI in everyday lifeSep 16
What we saw
“OpenAI and AARP are bringing free, hands-on ChatGPT workshops to 1,000 older adults across 10 U.S. cities to build practical AI…”
Published 2026-09-16
Fetched 2026-09-16 23:01 UTC · a8a40dafc20d6b2f
Torn from — the listing only (the original would not open)
Source AWS ML Blog
Optimizing agent system prompts with Amazon Bedrock AgentCoreSep 16
no limits stated2.0k words
What we saw
“AgentCore optimization turns production traces into proposed configuration changes, then validates them before promotion. This …”
They claim — A single reflector pass can focus on patterns in the first 5–10 traces it examines and miss failure modes that appear only in a smaller portion of the corpus.
Published 2026-09-16
Fetched 2026-09-16 23:01 UTC · 93c67c600c06037d
Torn from — the listing only (the original would not open)
Source AWS ML Blog
Build a serverless PII redaction pipeline with Amazon Bedrock Data AutomationSep 16
states limits2.9k words
What we saw
“Learn how to automate end-to-end PII detection and redaction from scanned documents at scale using Amazon Bedrock Data Automati…”
They claim — We tested document samples spanning six document quality levels in our use case, from clean typed forms through low-resolution 100 dots per inch (DPI) scans (Table 2).
Published 2026-09-16
Fetched 2026-09-16 23:01 UTC · 6fc8596fd9d93039
Torn from — the listing only (the original would not open)
Source OpenAI
Reimagining advertising with AISep 16
What we saw
“Explore new AI-powered advertising experiences from OpenAI, including Sponsored Agents, tools for marketers, and integrations w…”
Published 2026-09-16
Fetched 2026-09-16 23:01 UTC · 8c2a426559207a9d
Torn from — the listing only (the original would not open)
Source OpenAI
How to connect AI usage to business valueSep 16
What we saw
“Learn how ChatGPT Work and Codex analytics help teams understand AI usage and spend, identify training needs, and connect adopt…”
Published 2026-09-16
Fetched 2026-09-16 23:01 UTC · ec2f604ddc5e799a
Torn from — the listing only (the original would not open)
Source Hacker News
Introducing System One Models and Jev1.8k points472 comments
no limits stated2.2k words
What we saw
This source gives a title and a link, nothing to quote.
They claim — Output tokens: ~5x more expensive than input tokens.
Published 2026-09-15
Fetched 2026-09-15 23:01 UTC · a56dc0fbbb070541
Torn from — the page itself
Thread ↗ Source HF Daily Papers
AI for Games in the Foundation Model Era106 upvotes1 comments
10 authorsno limits stated
What we saw
“Foundation models, alongside advances in learned game-world models, are reshaping AI across the game lifecycle. Beyond playing …”
Published 2026-09-14
Fetched 2026-09-16 23:01 UTC · bcd23ad210dcebdc
Torn from — the abstract
Thread ↗ Source Latent Space
Humanity’s Last Invention — Richard Socher of RecursiveSep 14
states limits19k words
What we saw
“At 1:09:00 we talk about the rise of AI x Finance, and AIE NYC is one month away - our hotel block is 97% sold out, get tix & t…”
They claim — At 1:09:00 we talk about the rise of AI x Finance, and AIE NYC is one month away - our hotel block is 97% sold out, get tix & travel ASAP - we will announce speakers from Bridgewater, Ram…
Published 2026-09-14
Fetched 2026-09-14 23:01 UTC · c05b8ea278666dc2
Torn from — the listing only (the original would not open)
PythonSource GitHub
ai-sucks-butt/ai-sucks-butt1.7k stars0 forks
no licensePythonpushed today
Location, estimated · Not stated
What we saw
“If you think AI sucks, star the repo.”
Published 2026-09-14
Fetched 2026-09-16 23:01 UTC · 293a5d397115ca6c
What the account wrote — The account left it blank
Torn from — the README
audiomusicSource Hugging Face
Mothersuperior/yue2-mothersuperior-realaudio-tokenizer-v4125 likes0 downloads
cc-by-nc-4.0built on MERT-v2-FullSong
What we saw
This source gives a title and a link, nothing to quote.
They claim — bf16 variants are half the size; head top-1 agreement with fp32 is 98.6%).
Published 2026-09-13
Fetched 2026-09-15 23:01 UTC · 1bd7034ce20966aa
Torn from — the model card
Source Hacker News
Fable 5.1 Solves the Cyphral Distich, a 370-year-old cipher1.2k points541 comments
states limits1.5k words
What we saw
This source gives a title and a link, nothing to quote.
They claim — Urquhart left a second, much larger cryptogram in the same style — the Cyphral Octastich in The Jewel (1652), 285 numbers instead of 64, and just as unsolved.
Published 2026-09-13
Fetched 2026-09-13 23:03 UTC · fa1356e849525169
Torn from — the page itself
Thread ↗ Nothing on this page matches what you picked.
Papers, repos, models, blogs, Reddit and podcasts — once a day, by machine. Everything collected gets taken apart once — the README, the abstract, the model card — and what that turns up is kept for good, whether or not it becomes a card. Titles and links go to the original; nothing is reproduced here.
The grey line on each card is what the teardown found, not what the source advertises: the licence, the last commit, the model it was built on, whether the paper states its own limits. Open “What we saw” to check what was read to get it. Where it says listing only, the original could not be read — some sites refuse us, and we do not pretend otherwise.
A line in quotation marks is a sentence lifted from the source itself — their number, not a measurement of ours. We copy it and leave it unchecked; that is the point of quoting it.
Topics are assigned by matching words in the original title, quote and tags against a fixed list — no model reads the card. Some cards match nothing and carry no topic at all; pick a topic and those drop out. Source and topic narrow together.
Each card keeps the sentence we actually read at the moment we read it, plus a fingerprint of the response we received. That sentence — not the whole page — is what we can still stand behind if the original later changes or disappears.
Guessed from one free-text field the account filled in itself, and half of them leave it empty. Shown as its own value rather than hidden.