vision-language modelautoregressive next-token predictionSource HF Daily Papers
PhysBrain 1.5: From Vision-Language Models to Physical Foundation Models172 upvotes3 comments
vision-language model54 authorsno limits stated
What we saw
“PhysBrain 1.5 unifies physical environment understanding, action generation, and future state prediction via joint autoregressi…”
They claim — Across 28 embodied understanding benchmarks, our 8B model achieves an average score of 72.5, setting a new open-source state of the art and performing on par with leading proprietary mode…
Published 2026-09-13
Fetched 2026-09-15 23:01 UTC · 70061e1a1aeb68ea
Torn from — the abstract
Thread ↗ recursive self-improvementexploration strategiesSource HF Daily Papers
Dream-RSI: Recursive Self-Improvement through Evolving Worlds278 upvotes3 comments
recursive self-improvement17 authorsstates limits
What we saw
“Dream-RSI enables scalable recursive self-improvement by using historical discovery replay to evaluate exploration policies off…”
Published 2026-09-13
Fetched 2026-09-15 23:01 UTC · 263aacf523ded915
Torn from — the abstract
Thread ↗ foundation agentic language modelVerifiable Experience PipelineSource HF Daily Papers
Atria Dawn: The Dawn of Agentic Superintelligence424 upvotes3 comments
foundation agentic language model143 authorsno limits stated
What we saw
“Atria Dawn Preview is a foundation agentic language model trained through verified tool interactions that achieves strong bench…”
They claim — Across 16 benchmarks spanning real-world research, engineering, and digital work, Atria Dawn Preview is competitive with frontier agents and achieves the highest reported score on five of…
Published 2026-09-13
Fetched 2026-09-15 23:01 UTC · 21c391716120f827
Torn from — the abstract
Thread ↗ Source Hacker News
HTMLSource GitHub
yifanzhang-pro/recurrent-looped-tranformer858 stars84 forks
Apache-2.0HTMLpushed 2d ago
Location, estimated · Not stated
What we saw
“Official Project Page for Recurrent Looped Transformer (RLT)”
They claim — Training length is 32 operations; evaluation extends to 128 operations (4× the training length), with 2,048 test programs per task and length.
Published 2026-09-12
Fetched 2026-09-15 23:01 UTC · 675776a9a37fe26a
What the account wrote — The account left it blank
Torn from — the README
Source HF Daily Papers
StepAudio 3 Realtime Technical Report91 upvotes1 comments
90 authorsno limits stated
What we saw
“Realtime spoken interaction demands deep reasoning, prompt responses, and fluid turn-taking. We present StepAudio 3 Realtime, a…”
They claim — StepAudio 3 Realtime achieves top-tier performance across key dimensions: an exceptional 90.6 on the MMSU benchmark, 98.9 Overall on the Artificial Analysis Full-Duplex Bench, and a 56.0%…
Published 2026-09-11
Fetched 2026-09-16 23:01 UTC · c13c53fb82422478
Torn from — the abstract
Thread ↗ PythonaiSource GitHub
kruzovic7/ai-data-extractor825 stars132 forks
MITPythonpushed 4d ago
Location, estimated · Not stated
What we saw
“Free open-source extractor for AI coding assistant chat histories. Supports Claude Code, Cursor, Windsurf, Aider, Cline/Roo Cod…”
Published 2026-09-11
Fetched 2026-09-15 23:01 UTC · 32cd43375b85b5e6
What the account wrote — The account left it blank
Torn from — the README
image-text-to-textggufSource Hugging Face
ukisai/Swift-Qwen3.8-27B-GGUF179 likes55k downloads
otherbuilt on Swift-Qwen3.8-27b
What we saw
This source gives a title and a link, nothing to quote.
They claim — (<1% loss) and as a result getting a x1.95 speed-up on several tasks.
Published 2026-09-11
Fetched 2026-09-15 23:01 UTC · fae0d09608b75058
Torn from — the model card
comfyuiSource Hugging Face
Comfy-Org/YuE2150 likes59k downloads
cc-by-nc-4.0built on SheetSage2
What we saw
This source gives a title and a link, nothing to quote.
Published 2026-09-11
Fetched 2026-09-15 23:01 UTC · 65418212282ccac7
Torn from — the model card
image-text-to-texttransformersSource Hugging Face
dealignai/DeepSeek-V4.1-Flash-UNCENSORED-FP8229 likes6.8k downloads
mitbuilt on DeepSeek-V4.1-Flash
What we saw
This source gives a title and a link, nothing to quote.
They claim — The refusal circuitry is surgically removed while every capability-critical component (routed experts, Engram memory, CSA2 sparse attention, DSpark draft head, vision tower, router gates,…
Published 2026-09-10
Fetched 2026-09-13 23:03 UTC · aba564a993aae2f3
Torn from — the model card
vision-action shortcutslatent interface trainingSource HF Daily Papers
Breaking the Vision-Action Shortcut: Latent Interface Training for Generalizable Robotics Foundation Models71 upvotes2 comments
vision-action shortcuts4 authorsno limits stated
What we saw
“LIT improves robot action generalization by first training pose-conditioned action priors without images, then constraining vis…”
They claim — Across four vision-language-action and world-action architectures (Pi0.5, MolmoAct2, FAST-WAM, and ImageWAM), LIT improves overall LIBERO-Plus success by 3.87-10.70 percentage points whil…
Published 2026-09-10
Fetched 2026-09-14 23:01 UTC · 3e83d75847ca11ec
Torn from — the abstract
Thread ↗ gated sliding-window attentionfull attentionSource HF Daily Papers
ZGCM-1: A Fully Open and Extremely Efficient Foundation Model for Math and Agentic Search302 upvotes7 comments
gated sliding-window attention22 authorsstates limits
What we saw
“ZGCM-1 is a 7B open foundation model that combines internal reasoning with external tool use, trained via efficient architectur…”
They claim — On several challenging mathematical reasoning and agentic search suites, it remains competitive with frontier models orders of magnitude larger, such as Qwen3-235B-A22B and GLM-5.1.
Published 2026-09-10
Fetched 2026-09-15 23:01 UTC · fcb1e94d9a32e870
Torn from — the abstract
Thread ↗ image-text-to-textggufSource Hugging Face
DavidAU/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-NM-DAU-NEO-MTP-GGUF143 likes114k downloads
apache-2.0built on Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored
What we saw
This source gives a title and a link, nothing to quote.
They claim — TWIN TURBO: Closed source level of intelligence with an arc-c at 709 (this is instruct "medium", reasoning is even higher), while using smaller quants too.
Published 2026-09-10
Fetched 2026-09-14 23:01 UTC · 68058414275bc9a3
Torn from — the model card
large language models (LLMs)AI benchmarksSource HF Daily Papers
real-time video generationspatial video generationSource HF Daily Papers
Vidu S2: Real-Time Interactive, Editable, and Spatial Video Generation695 upvotes2 comments
real-time video generation35 authorsno limits stated
What we saw
“Vidu S2 introduces real-time interactive avatar and video editing models that support high-resolution spatial video generation …”
They claim — Experiments show that Vidu S2 outperforms all baselines.
Published 2026-09-09
Fetched 2026-09-15 23:01 UTC · 5e45abe94152d970
Torn from — the abstract
Thread ↗ image-text-to-texttransformersSource Hugging Face
ukisai/Swift-Qwen3.8-27b323 likes2.8k downloads
otherbuilt on Qwen3.8-27B
What we saw
This source gives a title and a link, nothing to quote.
They claim — (<1% loss) and as a result getting a x1.95 speed-up on several tasks.
Published 2026-09-08
Fetched 2026-09-14 23:01 UTC · b4d8039f21680101
Torn from — the model card
post-trainingsupervised fine-tuningSource HF Daily Papers
Feyospace-v1: How the Cyber Mercury Seven Trained Frontier Cyber Models130 upvotes3 comments
post-training7 authorsno limits stated
What we saw
“A data-centric framework with specialized systems for reasoning analysis, cost reduction, and execution verification enables sm…”
They claim — The three checkpoints improve over their starting models by an average of 23.76% on the full CyberGym suite and 10.49% across the pooled CTF suites.
Published 2026-09-07
Fetched 2026-09-14 23:01 UTC · 4d29dafb2e864139
Torn from — the abstract
Thread ↗ PythonaiSource GitHub
crwdla/tokentab1.1k stars215 forks
MITPythonpushed 6d ago
Location, estimated · Unrecognised
What we saw
“A CLI that reads Claude Code, Codex, and Gemini CLI session logs and works out how much they cost, by model, project, and day.”
They claim — Cache hit under ~80%, consistently - your context probably isn't stable between calls, or caching isn't switched on.
Published 2026-09-07
Fetched 2026-09-13 23:03 UTC · 285e008f28d1dc05
What the account wrote — Newcastle
Torn from — the README
catastrophic forgettingcontinual supervised fine-tuningSource HF Daily Papers
Continual Learning Mechanisms Compose for Long-Horizon Memorization287 upvotes3 comments
catastrophic forgetting4 authorsno limits stated
What we saw
“Composing complementary continual learning mechanisms substantially improves long-horizon memorization in language models by co…”
They claim — Our best method combines all three anchors with merged LoRA, ranks among the top 3 methods in all datasets, and raises average final retention from 1.2% under naive sequential fine-tuning…
Published 2026-09-06
Fetched 2026-09-16 23:01 UTC · 299fad04b14317fa
Torn from — the abstract
Thread ↗ Pythonai-upscalingSource GitHub
perseval-BLR/NeuralScreen823 stars45 forks
no licensePythonpushed today
Location, estimated · Not stated
What we saw
“DLSS 5 NR on your whole Windows desktop, in real time with Boost, FG, etc. RTX 30/40/50, 12 languages, user presets, recording …”
They claim — Windows 10 and multi-GPU systems are experimental — v1.12 fixes adapter/output selection from user logs, not local hardware.
Published 2026-09-06
Fetched 2026-09-15 23:01 UTC · b6fda159d2186867
What the account wrote — The account left it blank
Torn from — the README
PythonaiSource GitHub
jtydhr88/screenwriting-skills1.2k stars134 forks
MITPythonpushed today
Location, estimated · Canada
What we saw
“Professional agent skills for screenwriting, television writing and dramaturgy”
Published 2026-09-06
Fetched 2026-09-15 23:01 UTC · 23ae32d1655cbeed
What the account wrote — Toronto, Canada
Torn from — the README
RLVRGRPOSource HF Daily Papers
DataFlex-RL: An Evaluation Platform for RLVR Data Policies110 upvotes2 comments
RLVR5 authorsstates limits
What we saw
“DataFlex-RL evaluates reinforcement learning data policies and finds that uniform sampling matches or exceeds adaptive rollout …”
They claim — Uniform GRPO improves the domain-balanced average accuracy by 7.76 percentage points over the untrained checkpoint.
Published 2026-09-04
Fetched 2026-09-14 23:01 UTC · 8b008970febe99b9
Torn from — the abstract
Thread ↗ image-text-to-textsafetensorsSource Hugging Face
TaichuAI/ZDTaichu5.0-9B151 likes213 downloads
no license
What we saw
This source gives a title and a link, nothing to quote.
They claim — Within the 10B-scale general-purpose VLMs compared in this release blog, ZDTaichu5.0-9B retains first-tier general visual understanding while supporting spatial reasoning, high-level embo…
Published 2026-09-04
Fetched 2026-09-15 23:01 UTC · 5179574dcefd9e42
Torn from — the model card
TypeScriptagentsSource GitHub
shadcn-ui/lint1.7k stars25 forks
MITTypeScriptpushed yesterday
Location, estimated · Not stated
What we saw
“An agent-first linter for Tailwind design systems. Write design system rules that agents can verify.”
They claim — 10% to 48% less than with rules alone.
Published 2026-09-02
Fetched 2026-09-15 23:01 UTC · 2bae6979048769f9
What the account wrote — The account left it blank
Torn from — the README
RustSource GitHub
faisalkindi/DLSS5oneclick769 stars55 forks
MITRustpushed today
Location, estimated · Not stated
What we saw
“One-click setup of the leaked DLSS 5 neural-rendering build for any DX11/DX12 game on RTX 20–50, with or without DLSS. ReShad…”
They claim — exe) - the game exe is detected automatically (the folder and two levels below it are searched, so bin\x64dx12\ and Unreal Binaries\Win64\ layouts work; Unity crash handlers, Unreal helpe…
Published 2026-08-31
Fetched 2026-09-13 23:03 UTC · 38bc58445c3c8fae
What the account wrote — The account left it blank
Torn from — the README
text-generationtransformersSource Hugging Face
meta-llama/Llama-3.1-8B-Instruct7.7k likes5.9M downloads
llama3.1built on Llama-3.1-8B
What we saw
This source gives a title and a link, nothing to quote.
Published 2024-07-18
Fetched 2026-09-14 23:01 UTC · bad7065e70b23d0e
Torn from — the listing only (the original would not open)
Source Simon Willison
Introducing ChatGPT Images 2.5Sep 8
no limits stated155 words
What we saw
“Introducing ChatGPT Images 2.5 OpenAI's image generation models are apparently used "more than 3 billion images across ChatGPT …”
Published 2026-09-08
Fetched 2026-09-08 23:01 UTC · 816483cf8f30597f
Torn from — the listing only (the original would not open)
Source AWS ML Blog
Take on your most ambitious work with GPT-6 Astra on Amazon BedrockSep 8
no limits stated1.1k words
What we saw
“GPT-6 Astra from OpenAI is now generally available on Amazon Bedrock. It brings deeper reasoning and sharper judgment to your m…”
Published 2026-09-08
Fetched 2026-09-08 23:01 UTC · 61555b0baa6fc6fd
Torn from — the listing only (the original would not open)
Source TechCrunch AI
Hackers are stealing Claude tokens from subscribersSep 8
no limits stated1.0k words
What we saw
“Last month, a Claude user noticed his account was consuming tokens even though he wasn't working. Anthropic has since warned us…”
They claim — On August 4, Grant De Swardt, an independent AI consultant in East Sussex, U.K., noticed something strange going on with his Claude Max 20x account.
Published 2026-09-08
Fetched 2026-09-08 23:01 UTC · 54678fe5fffcfda7
Torn from — the page itself
Source TechCrunch AI
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.