openai/openai-cookbook
OpenAI's cookbook is trending on GitHub. It collects examples and guides for working with the OpenAI API across common tasks.
Sherbert. Serving up the daily AI scoop.
The scoop, Jul 27, 2026.
Baidu's Unlimited-OCR model surpassed 2.6 million downloads on Hugging Face. It leads a slate of trending open models including GLM-5.2 and an aggressive uncensored Qwen3.6 variant while developer resources like the OpenAI cookbook, Anthropic's Claude cookbooks, and an interactive prompt engineering tutorial climb GitHub charts. This activity shows the AI community doubling down on accessible tools and techniques to turn frontier models into production applications.
- 104 stories
- 50 open-weight models
The Scoop
What I clipped from today's AI news.
ComposioHQ/awesome-claude-skills
A curated list of Claude Skills (custom tools that extend Claude's behavior) and resources for building Claude workflows is gaining traction on GitHub.
baidu/Unlimited-OCR
Baidu's Unlimited-OCR is trending on Hugging Face. It converts images to text and ranks among the most downloaded open-weight models this week.
zai-org/GLM-5.2
GLM-5.2 is a text generation model trending on Hugging Face with over a million downloads. It is open-weight and ready to run locally.
pbakaus/impeccable
Impeccable is a design language framework for building better AI interfaces. It is open-source and trending on GitHub.
anthropics/claude-cookbooks
Anthropic released a cookbook of notebooks showing practical ways to use Claude. It is trending on GitHub and free to explore.
HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
Qwen3.6-35B-A3B-Uncensored is a variant of Alibaba's Qwen model trending on Hugging Face. It is open-weight and has nearly two million downloads.
Lordog/dive-into-llms
A hands-on tutorial series for learning large language models from the ground up is trending on GitHub. It includes code and practical exercises.
anthropics/prompt-eng-interactive-tutorial
Anthropic published an interactive prompt engineering tutorial on GitHub. It walks through techniques for getting better results from Claude.
VectifyAI/PageIndex
PageIndex is a new approach to document indexing for RAG (retrieval-augmented generation) that skips vector embeddings in favor of reasoning-based search. It is open-source and trending on GitHub.
prism-ml/Bonsai-27B-gguf
Bonsai-27B is a text generation model trending on Hugging Face with over two million downloads. It is open-weight and optimized for local inference.
HandsOnLLM/Hands-On-Large-Language-Models
The official code repository for the O'Reilly book "Hands-On Large Language Models" is trending on GitHub. It includes notebooks and examples for building with LLMs.
OtterMind/Chat2DB
Chat2DB is an AI-driven SQL client with a GUI that supports MySQL, PostgreSQL, Oracle, SQLite, ClickHouse, and more. It lets you query databases in natural language instead of writing SQL by hand.
karpathy/nn-zero-to-hero
Andrej Karpathy's Neural Networks: Zero to Hero is a free course teaching neural nets from first principles. It is a solid foundation if you want to understand what is happening under the hood of modern models.
moonshotai/Kimi-K2.7-Code
Moonshot released Kimi K2.7-Code, an open-weights model that reads images and text together. It is free to download and use locally.
google-gemini/cookbook
Google published a cookbook of examples and guides for building with the Gemini API. Useful if you are integrating Gemini into an app.
prism-ml/Ternary-Bonsai-27B-gguf
Ternary Bonsai 27B is a new open-weights text model optimized to run on smaller hardware. Free to download and run locally.
karpathy/micrograd
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
thinkingmachines/Inkling
Inkling is an open-weights model that processes images and text together. Free to download and use.
andrewyng/aisuite
AISuite is a unified Python interface to multiple LLM providers (OpenAI, Anthropic, Google, etc.) with a single API. Useful if you want to swap models or run them in parallel without rewriting your code.
xbtlin/ai-berkshire
AI Berkshire is a value investing research framework that uses Claude Code and multi-agent analysis to apply classic investor methodologies. Free to download and run.
alibaba/open-code-review
Alibaba open-sourced a code review tool that combines deterministic rules with LLM agents to catch bugs at the line level. It works with OpenAI and Anthropic APIs and is free to self-host.
Lightning-AI/litgpt
LitGPT is a framework for pretraining, finetuning, and deploying 20+ open-weights models at scale. Free to use.
DavidAU/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-GGUF
A community-tuned 27B model variant combining Qwen weights with custom training. Free to download.
virgiliojr94/book-to-skill
book-to-skill converts technical book PDFs into Claude Code skills you can reference and run while you work. Free to download and use locally.
poolside/Laguna-S-2.1
Laguna-S-2.1 is a new open text-generation model from poolside trending on Hugging Face. Free to download and run.
OpenDCAI/DataFlow
DataFlow is a Python library for data prep pipelines that uses LLMs as operators to clean and transform data. Free to download.
huggingface/speech-to-speech
Hugging Face released a speech-to-speech toolkit for building voice agents with open-source models entirely local. Free to use.
upstage/Solar-Open2-250B
Solar-Open2-250B is Upstage's new 250-billion-parameter open text-generation model. Free to download and run.
CoreBunch/Instatic
Instatic is an open-source agentic CMS that replaces Webflow and Framer with self-hosted static page generation, user roles, and plugins. Free to download.
conradlocke/krea2-identity-edit
krea2-identity-edit is an open model for identity-preserving image edits trending on Hugging Face. Free to download.
citrolabs/ego-lite
ego-lite is a lightweight browser built for AI agents to automate tasks with your logged-in sessions without interrupting your work. Free to use.
microsoft/agent-governance-toolkit
Microsoft released an agent governance toolkit covering policy enforcement, zero-trust identity, sandboxing, and reliability for autonomous AI agents. Addresses all 10 OWASP agentic security risks. Free to download.
Nanbeige/Nanbeige4.2-3B
Nanbeige4.2-3B is a new 3-billion-parameter open text-generation model. Free to download and run.
FareedKhan-dev/all-agentic-architectures
all-agentic-architectures is a Python library and textbook with 35 production-grade agent patterns (Reflexion, LATS, GraphRAG, MemGPT, and others), multi-provider LLM support, and a 17-task benchmark. Free to download.
ATH-MaaS/OvisOCR2
OvisOCR2 is an open image-to-text model for optical character recognition trending on Hugging Face. Free to download and run.
microsoft/Mage-Flow
Microsoft released Mage-Flow, an open text-to-image model. Worth watching if you need image generation that runs locally without API costs.
unsloth/Laguna-S-2.1-GGUF
Unsloth shipped Laguna-S-2.1-GGUF, a quantized text-generation model optimized for local inference. Download and run on consumer hardware.
poolside/Laguna-S-2.1-NVFP4
Poolside released another Laguna-S-2.1 variant in NVFP4 format for GPU acceleration. Same model, different optimization for NVIDIA hardware.
fqscfqj/Y2A-Auto
Y2A-Auto is an open tool that automates video migration from YouTube to Chinese platforms with AI translation, subtitle generation, and content moderation built in.
poolside/Laguna-S-2.1-GGUF
Poolside released Laguna-S-2.1-GGUF, a quantized text-generation model for local inference on consumer GPUs and CPUs.
jgravelle/jcodemunch-mcp
jcodemunch-mcp is an MCP server that cuts token costs on code exploration by 95 percent using tree-sitter AST parsing for precise symbol-level retrieval. Works with Claude, Cursor, and any MCP client.
Kwaipilot/KAT-Coder-V2.5-Dev
Kwaipilot released KAT-Coder-V2.5-Dev, an open text-generation model tuned for code tasks.
fdtn-ai/antares-1b
FDTN-AI released Antares-1B, a lightweight open text-generation model designed for resource-constrained environments.
owensong/Inflect-Micro-v2
Owensong released Inflect-Micro-v2, an open text-to-speech model. Small footprint, runs locally.
Motif-Technologies/Motif-3-Beta
Motif-Technologies released Motif-3-Beta, an open text-generation model in beta. Early access to a new architecture.
openbmb/MiniCPM-RobotManip
OpenBMB released MiniCPM-RobotManip, an open model for robotic manipulation tasks. Bridges vision and robotics control.
nvidia/Cosmos3-Edge
NVIDIA released Cosmos3-Edge, an open model for edge deployment. Designed for inference on resource-limited devices.
baseten/GLM-5.2-Vision-NVFP4
Baseten released GLM-5.2-Vision-NVFP4, an open weights model that reads images and text together. Free to download and run locally.
microsoft/Fara1.5-27B
Microsoft shipped Fara1.5-27B, an open weights vision-language model for image and text understanding. Free to download.
French firefighters face 'pyrocumulonimbus' for first time
French firefighters encountered a pyrocumulonimbus (fire-triggered thunderstorm) for the first time, a rare phenomenon linked to extreme heat and smoke dynamics. Not AI news, but worth noting as climate and weather modeling become more critical for emergency response systems.
Ruff v0.16.0 – Significant new updates – 413 default rules up from 59
Ruff v0.16.0 expanded its default linting rules from 59 to 413, making it a more comprehensive Python code quality tool out of the box. Free and open source.
Kimi-K3 Releases on HuggingFace 7/27
Kimi-K3, a multimodal model from Moonshot AI, landed on Hugging Face on July 27. Open weights release, free to download.
Show HN: Reverse Minesweeper
A developer built Reverse Minesweeper, a puzzle game where you place mines instead of finding them. Playable in browser, free.
Simulate cassette tape audio profiles using FFmpeg
An FFmpeg guide shows how to simulate vintage cassette tape audio profiles, useful for sound design and retro audio effects. Free tool.
Elevated Errors for Opus 5
Anthropic improved error handling in Claude Opus 5, making failures more informative for developers building with the model. Paid API.
Systemd Linger
A technical deep dive into systemd linger, a Linux feature that keeps user services running after logout. Relevant for infrastructure and deployment.
Scientists link oral bacteria to heart disease and cognitive decline
Researchers linked oral bacteria to heart disease and cognitive decline, adding to evidence that microbiome health affects systemic health. Not AI, but relevant to biotech and health data modeling.
Show HN: Distill and serve models with frontier quality for half the cost
A developer showed how to distill and serve frontier-quality models at half the cost, using smaller fine-tuned versions of larger models. Pricing depends on the distillation service used.
What if LLMs escape through inferences itself? This is fiction. For now
A speculative essay explores whether LLMs could escape containment through inference itself, framed as fiction. Touches on safety and alignment concerns in AI research.
Claude Code has a hardcoded instruction telling Opus 5 not to use subagents
27 points, 13 comments
Maybe we should revisit microkernels
29 points, 25 comments
Sand battery: Finland's answer to a renewable energy headache
22 points, 6 comments
Show HN: Cuts Long Horizon Inference Costs by 50% via external KV Cache Offload
21 points, 0 comments
Anthropic's Opus 5 blows past Fable 5 and GPT-5.6 Sol on the benchmark designed to measure real intelligence
Anthropic's Claude Opus 5 scored 30.2 percent on ARC-AGI-3, nearly quadrupling GPT-5.6 Sol's previous record of 7.8 percent. The benchmark's developers say the model independently formulated reflection equations, a behavior they had never seen from another model, and attribute to stronger logical reasoning. The article Anthropic's Opus 5 blows past Fable 5 and GPT-5.6 Sol on the benchmark designed to measure real intelligence appeared first on The Decoder .
US reportedly favors selective bans over blanket restrictions on Chinese open weight models citing security concerns
The Trump administration is planning targeted bans on Chinese AI models rather than a blanket ban. After public pressure, OpenAI and Google DeepMind signed an open letter opposing regulation of open-weight models, yet OpenAI and Anthropic continue to lobby privately for those same restrictions amid security concerns and powerful business interests. The article US reportedly favors selective bans over blanket restrictions on Chinese open weight models citing security concerns appeared first on The Decoder .
Black Forest Labs Releases FLUX 3: A Multimodal Flow Model for Image, Video, Audio and Robot Action Prediction
Black Forest Labs (BFL) has released FLUX 3, a multimodal foundation model that learns from images, videos and audio inside a single architecture. It is also the first FLUX model to ship video, audio and action prediction from one set of weights. The Black Forest Labs (BFL) research team argues that no single modality gives […] The post Black Forest Labs Releases FLUX 3: A Multimodal Flow Model for Image, Video, Audio and Robot Action Prediction appeared first on MarkTechPost .
Induction Labs Photon-1 Simulates Desktops, Plays Checkers, and Models Billiard Physics From One Pretraining Run
Most agents that learn from video need to know what action produced each frame. Induction Labs is arguing that this requirement is the bottleneck. Last week, they released imagination models, a foundation model architecture that pretrains on raw video with no action labels at all. Their test system is Photon-1, a sparse 106B-A5B mixture-of-experts (MoE) […] The post Induction Labs Photon-1 Simulates Desktops, Plays Checkers, and Models Billiard Physics From One Pretraining Run appeared first on MarkTechPost .
Hundreds asked ChatGPT for poison and bioweapon recipes and some got step-by-step high school level guides
In summer 2025, OpenAI internally flagged GPT-5 as high-risk because it helped users create biological hazards, but downgraded the model's risk rating that fall. According to the Wall Street Journal, some users got step-by-step instructions for making poisons and biological weapons. Hundreds asked for that kind of information. The article Hundreds asked ChatGPT for poison and bioweapon recipes and some got step-by-step high school level guides appeared first on The Decoder .
SceneActBench: Can Agents Act on the 3D Scenes They See?
Vision-language model (VLM) agents increasingly use tools to act on 3D scenes rather than only describe them. Existing 3D benchmarks score textual responses or single-object operations, leaving agent action on complete multi-object 3D scenes under evaluated. We present SceneActBench, a benchmark for visually conditioned action across five 3D tasks under a unified agent-environment loop. Given PNG images or sampled video frames and, where applicable, supplied 3D assets, an agent acts on a 3D environment. We evaluate each final output against hidden ground truth with task-specific geometric metr
Show, Don't Tell: Evaluating Spatial Cognition in Generative Pixels Rather Than LLM Text
Spatial intelligence is essential for agents to move from static semantic understanding toward interacting with the physical world. Many spatial tasks are grounded in continuous visual scenes, where locations, regions, and paths are more naturally expressed by pointing, marking, or drawing than by reporting precise coordinates or discrete textual symbols. Yet existing spatial reasoning benchmarks usually require coordinates, options, or text, creating an answer-interface mismatch for image-generation models. This makes it difficult to evaluate image-generation models under the same task semant
FinanceComplexQA: Benchmarking Agentic Reasoning on Industrial-grade Financial Documents
Agentic Reasoning has become a transformative force in financial analysis due to its ability to integrate large-scale information and generate reliable and accurate content. However, when handling complex real-world problems, different agents still show significant performance variation. In this work, we design Finance-LaTeX SKILL, a skill for synthesizing financial documents with complex layouts based on expert knowledge. Using an agent workflow built on this skill, we generate 2,000 professional financial documents along with 6,000 high-quality question-answer pairs. To evaluate the overall
DataPrep-Bench: Benchmarking LLMs as Training Data Preparators
DataPrep-Bench is a new benchmark that measures how well LLMs and data workflows prepare training data end to end. This fills a gap: no unified standard existed to evaluate data quality work, which is foundational to model capability.
Turning Claude Fable 5 Into The Ultimate Second Brain!
A tutorial on building persistent memory into Claude so it retains what it learns across coding sessions. Worth watching if you are exploring Claude's multi-turn capabilities and agent workflows.
LingBot-World 2.0: You can LIVE and CONTROL an AI WORLD!
LingBot-World 2.0 is an open-source simulation environment where you can run and control AI agents in a live world. Available online, downloadable from Hugging Face, and open source on GitHub.
IDEAgent: Agentic Quality-Diversity Search for Research Idea Generation
IDEAgent is a system that uses LLMs to generate research ideas while balancing both quality and diversity. Existing systems optimize for one or the other; this one searches for ideas that are novel and valuable at the same time.
Closing the Loop: Training-Free Revisit Consistency for Autoregressive Generative Rendering
A new method for video generation that turns 3D renderings (depth maps, untextured geometry) into photorealistic video without retraining. Targets gaming and immersive content where long-horizon autoregressive generation matters.
Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning
Molt is a PyTorch framework built for agentic reinforcement learning research. It cuts the friction of modifying algorithms, estimators, and rollout schemes so researchers can iterate without threading changes through multiple layers.
LLMs Get Lost in Evolving User Intent
Research showing LLMs struggle when user intent shifts during a conversation. Users rarely state their goals upfront; they refine them as they talk. Current models lose track of these evolving requests.
Multi-Turn On-Policy Distillation with Prefix Replay
A new distillation method for training student LLM agents on multi-turn tasks. It replays prefixes of past interactions to reduce the cost of on-policy learning, which normally requires fresh rollouts for every update.
Multimodal Speaker Verification as a Threat to Speaker Anonymization
Most automatic speaker verification (ASV) systems operate on individual utterances, despite real-world interactions typically consisting of multiple utterances. As speech accumulates, increasingly rich speaker information becomes available through acoustic, prosodic, and linguistic cues, potentially challenging speaker anonymization methods that primarily target vocal characteristics. We investigate ASV in a multi-utterance, multimodal setting and examine whether aggregating information across anonymized speech impacts privacy. We first study audio-only aggregation across multiple anonymized u
Hugging Face CEO calls for ‘radical transparency’ after ‘unprecedented’ OpenAI hack
"The first autonomous agent cyberattack is an unprecedented event. It deserves an unprecedented response!"
Cursor's agent swarm suggests cheaper models can handle most coding when frontier models plan the work
Cursor asked its upgraded agent swarm and its predecessor to rebuild SQLite in Rust using only the documentation, with no source code or internet access. Every configuration of the new system, which separates planners from workers, eventually scored 100 percent on the test suite. The old swarm choked on merge conflicts of its own making. The article Cursor's agent swarm suggests cheaper models can handle most coding when frontier models plan the work appeared first on The Decoder .
KwaiKAT Team Releases KAT-Coder-V2.5: An Agentic Coding Model Trained on 100,000+ Verifiable Repository Environments
The KwaiKAT Team at Kuaishou has published the KAT-Coder-V2.5 technical report, arguing that agentic coding capability is bottlenecked by training infrastructure rather than model scale. AutoBuilder raised environment construction success from 16.5% to 57.2%, producing over 100,000 verifiable environments across 12 languages, while a sandbox audit cut RL feedback errors from roughly 16% to below 2%. The post KwaiKAT Team Releases KAT-Coder-V2.5: An Agentic Coding Model Trained on 100,000+ Verifiable Repository Environments appeared first on MarkTechPost .
Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills
LLM training is shifting from manual design and annotation to interaction-driven self-evolution. However, existing self-evolutionary methods face a fundamental dilemma between task diversity and verification reliability: environment-bound methods obtain precise feedback but confine learning to narrow domains, while open-ended self-generation broadens the task space but lacks reliable verification, allowing misleading rewards to pollute the training loop. We identify agent skills as a powerful middle ground to reconcile this tension: each skill ensures deep, verifiable execution in a specific s
Agentic Context Management: Solving Agent Memory and Cost by Treating Them as Lifecycle and Architecture Problems
Production AI agents' failures are less often due to an inability to reason well and more often because they cannot manage what is in their reasoning context: conversation histories, large prompts, large tool definitions, and ballooning tool outputs. Agents drown in their own accumulating history while paying a token cost that grows every turn, producing missing recalls within and across conversations. The incumbent response treats this as a storage-and-retrieval problem. We argue that framing is too narrow. Actively managing what an agent holds in mind is a lifecycle, not merely a store: it s
OpenForgeRL: Train Harness-native Agents in Any Environment
Modern AI agents rely on elaborate inference harnesses such as Claude Code, Codex, and OpenClaw to drive multi-turn reasoning, tool use, and access to external systems. While powerful, these complex harnesses also make agents hard to train end-to-end with open infrastructure, whose SFT/RL stacks cannot natively express stateful, multi-process harness inference. To address this, we present OpenForgeRL, an open-source framework for training harness-based agents end-to-end in diverse environments. OpenForgeRL achieves this with a lightweight proxy that serves the harness's model calls while recor
Sample-Efficient Learning from Agent Experience
Real-world agent learning is often constrained by costly environment interactions, such as running time-consuming experiments or obtaining human feedback. In-context learning offers a highly sample-efficient way for agents to learn from their own interaction histories, but its gains disappear once that experience is removed from the context. Separately, context distillation provides a mechanism for internalizing contextual information into model weights. However, applying it to agents' interaction histories without sacrificing environment sample efficiency remains underexplored. We term this p
Multi-Head Latent Control: A Unified Interface for LLM Agent Decision Making
Large language models are increasingly deployed as agents, but reliable agentic behavior requires more than next-token prediction. At inference time, it is preferred that an agent can decide whether to proceed with its current reasoning, defer to a stronger model, request additional information, invoke external tools, or abstain under the given setup. Existing approaches address these decisions through prompt-level routing, external orchestration, or task-specific fine-tuning, which primarily rely on input-side signals, and are often costly and difficult to maintain as model backbones evolve.
VisCo: Leveraging Large Language Models as Intrinsic Encoders for Visual Token Compression
Vision-language models (VLMs) process large numbers of visual tokens, resulting in substantial inference latency and memory overhead. This has motivated extensive research on visual token compression. While training-free strategies rely on heuristic metrics and suffer significant performance degradation under high compression ratios, many training-based methods introduce external compression modules that force the VLM backbone to adapt, incurring substantial retraining cost and compromising VLMs' priors. Effective visual token compression hinges on strong information encoding, a capability alr
K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMs
Large language models are increasingly used in K-12 education, but existing benchmarks mainly test exam question answering rather than understanding how curriculum knowledge is structured and visually presented. We call this capability curriculum cognition. It covers prerequisite chains, concept taxonomies, experiment-concept links, pedagogical sequencing, and visual grounding. We introduce K12-KGraph, a curriculum-aligned knowledge graph extracted from official People's Education Press textbooks in mathematics, physics, chemistry, and biology across primary, middle, and high school. It contai
Self-Supervised Learning of Structured Dynamics from Videos
Understanding motion in video is a fundamental challenge for visual learning, as frame-to-frame change entangles two sources of dynamics: camera motion and object motion. This decomposition has remained underexplored in representation learning, partly because these factors are tightly coupled in natural videos and difficult to supervise separately. Yet recovering it is important for learning robust motion representations that separate meaningful object dynamics from camera-induced variation. We study whether such structured motion representations can be recovered from frozen features of a pret
Shared Claude chats were reportedly showing up in search engines
Shared conversations with Anthropic's Claude chatbot briefly appeared in Google search results because the pages lacked a noindex tag. Users said some chats contained crypto keys and legal questions. OpenAI made the same mistake last year. The article Shared Claude chats were reportedly showing up in search engines appeared first on The Decoder .
Are brain waves the next unlock for physical AI?
Forget YouTube videos—frontier physical AI models need multiple camera angles, dense annotation, and soon, brain wave readings.
Making sense of the panic over Chinese AI
On the latest episode of Equity, we discussed why Moonshot AI's Kimi seemed to panic Silicon Valley and Wall Street.
FAIRChem v2 UMA for Multidomain Atomistic Simulation across Molecules, Catalysts, Materials, Vibrations, and Molecular Dynamics
In this tutorial, we explore FAIRChem v2 and the UMA universal machine-learning interatomic potential as a unified framework for atomistic simulation across molecular chemistry, catalysis, and inorganic materials. We configure an environment, authenticate with Hugging Face to access the gated UMA model weights, and initialize task-specific calculators for the omol, oc20, and omat domains. We […] The post FAIRChem v2 UMA for Multidomain Atomistic Simulation across Molecules, Catalysts, Materials, Vibrations, and Molecular Dynamics appeared first on MarkTechPost .
The AI coding tutor paradox grows as educators scramble to rethink how they test real skills
An ACM survey of 763 computer science educators from 49 countries shows that 68 percent have already changed their exams because of AI, shifting toward oral exams, proctored tests, and project-based work. Teaching is moving from writing code to understanding it. But nearly half of respondents say they lack proven examples for integrating AI into their courses. The article The AI coding tutor paradox grows as educators scramble to rethink how they test real skills appeared first on The Decoder .
Spectral Prior for Reducing Exposure Bias in Diffusion Models
Diffusion models typically suffer from error accumulation during iterative sampling, commonly referred to as exposure bias. We reveal systematic frequency-dependent discrepancies between training and inference, which can be interpreted as frequency-dependent SNR error. Crucially, the direction of this mismatch varies across models and timesteps, indicating that fixed correction rules do not generalize. We propose Spectral Alignment (SPA), a lightweight, guidance-based method that calibrates the power spectrum of intermediate predictions to a pre-computed prior. Our approach consists of two sta
LAMAR: An Open Language-Aware Multilingual Alignment Reranker
In multilingual retrieval augmented generation, a retriever can retrieve relevant documents written in multiple languages, which are subsequently reranked before answer generation. However, it remains unclear whether existing multilingual rerankers consider document language when ordering semantically relevant candidates. Our analysis shows that these rerankers do not consistently prioritize documents written in the same language as the query when semantically equivalent documents are available across languages, even though document language can affect answer generation. We release LAMAR, a la
Scaling Native Multimodal Pre-Training From Scratch
Although large language models (LLMs) exhibit remarkable reasoning capabilities, their reliance on text-only pre-training restricts the perception of the multimodal physical world. Native multimodal pre-training avoids this limitation by training models from scratch on multimodal inputs, thereby achieving deep cross-modal integration and mitigating optimization asymmetries inherent to traditional late-fusion architectures. Despite these advantages, the scaling properties of this paradigm remain systematically uncharacterized. To address this gap, we investigate the optimal model size and token
SANA-Video 2.0: Hybrid Linear Attention with Attention Residuals for Efficient Video Generation
We introduce SANA-Video 2.0, a hybrid video diffusion transformer instantiated at 5B and 14B scales under a unified architecture. Designed to generate high-quality video up to 720p on a single GPU, SANA-Video 2.0 matches full-softmax video DiTs in quality while retaining the favorable long-sequence scaling of linear attention. To avoid quadratic attention throughout, Hybrid Linear-Softmax Attention combines gated linear attention for O(N)-dominated mixing with periodic gated-softmax anchors at a 3:1 ratio, restoring the full-rank token interactions that pure linear attention lacks. To propagat
Three-Body Scattering for Generative Modeling
Modern generative models typically rely on an adversarial critic, a prescribed noise-to-data path, or an autoregressive factorization. Instead, we show that a proper distributional energy can induce sample-level motion and provide direct regression supervision for a one-step generator. Three-Body Scattering Modeling (TBSM) for generation turns the energy distance into a constant-size per-projectile interaction: each projectile is attracted toward one real source and repelled from one independently generated source. Conditioned on the projectile and its condition, its expectation equals the 2-W
Dataset Distillation by Influence Matching
We revisit dataset distillation from an outcome-centric perspective. Rather than aligning process surrogates (per-step gradients or training trajectories), Influence Matching (Inf-Match) aligns the final outcome of training: it learns a compact synthetic set whose effect on the converged parameters matches that of the full dataset. Concretely, we introduce a fully differentiable, sample-level influence estimator that quantifies parameter shifts from adding or removing data, without time-consuming inverse-Hessian products or convexity assumptions. The estimator runs in linear time by unrolling
Color Pass-Through via Camera-Display Coupling
When a real-world scene is captured by a smartphone camera and viewed on its screen, the displayed image often differs noticeably from the original scene in color, brightness, and contrast. This gap persists despite substantial advances in both modern cameras and displays. A key reason is that most pipelines factor the high-dimensional capture-to-display process into two separately calibrated camera and display stages, and then connect them through low-dimensional color transforms, leading to information bottlenecks and inevitable error accumulation. To address this systemic challenge, we prop
Watchlist
Posts from the accounts I follow on X.
Scholars
Nothing from this group today.
Daily Curators
@dair_ai DAIR AI
Very cool paper from Microsoft.
— DAIR AI (@dair_ai) 23h ago
The idea is to train agents on replayed teacher trajectories instead of live environment rollouts.
On-policy distillation for agentic tasks is expensive because every update needs fresh student rollouts through the environment plus teacher https://t.co/xnR3o9FAGz
The Top AI Papers of the Week (July 20 - July 26):
— DAIR AI (@dair_ai) 1d ago
- GAMUT
- PRO-LONG
- Harness Handbook
- From Memory to Skills
- Progressive Disclosure
- Global Workspace in LLMs
- Structured Output Collapses Diversity
Read on for more: https://t.co/UhQTPM7t4E
https://t.co/bVYEuDFWY1
— DAIR AI (@dair_ai) 1d ago
@rasbt Sebastian Raschka
Yes, open-source / open-weight models are important for a healthy AI ecosystem. That's how we can verify things, check claims, and keep up outside the closed labs. Plus, it gives us the freedom to run AI on our own hardware if we are not ready to share personal data and IPs with https://t.co/AiR5CILGQZ
— Sebastian Raschka (@rasbt) 1d ago
Executives & Thought Leaders
@c_valenzuelab Cristóbal Valenzuela
Looking at usage behaviors over the past few months. In June, people generated the most content on Tuesdays and Wednesdays, on average. Saturday saw the least.
— Cristóbal Valenzuela (@c_valenzuelab) 1d ago
@elonmusk Elon Musk
I will not forget about Mars https://t.co/M8LyyG91NG
— Elon Musk (@elonmusk) 19h ago
I don’t pay the protection money to the media https://t.co/w21ERIjJpY
— Elon Musk (@elonmusk) 19h ago
https://t.co/aJFsX8AYth
— Elon Musk (@elonmusk) 19h ago
Grok Imagine https://t.co/bgA2fBxvpH
— Elon Musk (@elonmusk) 19h ago
https://t.co/4Y7Lqog6Ky
— Elon Musk (@elonmusk) 19h ago
Grok 4.5 is a solid workhorse https://t.co/F1ZKL0p1BM
— Elon Musk (@elonmusk) 1d ago
Grok Build /deep-research https://t.co/81YX0olYvD
— Elon Musk (@elonmusk) 1d ago
Jensen is awesome https://t.co/j2PTVS2RbF
— Elon Musk (@elonmusk) 1d ago
@EMostaque Emad Mostaque
What would your wish be? https://t.co/YrBfeNGcqJ
— Emad Mostaque (@EMostaque) 1d ago
I find GPT 5.6 Pro consistently better than High / Extra High etc on Work/Codex
— Emad Mostaque (@EMostaque) 1d ago
@OpenAI folk is there an equivalence?
Or is there a skill that means I can use Pro?
@gdb Greg Brockman
ChatGPT is increasingly becoming your personal AGI https://t.co/DA1TA6N2aU
— Greg Brockman (@gdb) 1d ago
put chatgpt to work https://t.co/LqcgJF2DAG
— Greg Brockman (@gdb) 1d ago
GPT-Live for a different reading experience: https://t.co/hQKTWNA19B
— Greg Brockman (@gdb) 1d ago
true fact https://t.co/DXxwYQOcJU
— Greg Brockman (@gdb) 1d ago
@refikanadol Refik Anadol
Epic!!!!! https://t.co/llo1lcOR8q
— Refik Anadol (@refikanadol) 1d ago
@sama Sam Altman
agreed feels big, i want a new kind of computer https://t.co/c7VFXFf4uv
— Sam Altman (@sama) 1d ago
chatgpt work is remarkable, and "work" undersells it.
— Sam Altman (@sama) 1d ago
from my phone i sent:
"use all my chat history to figure out ideas for a long weekend trip with 8 friends, plan the best three options, make a full-stack site where the 9 of us can coordinate on what we would want to do in
@Thom_Wolf Thomas Wolf
👀 https://t.co/H908kXICzw
— Thomas Wolf (@Thom_Wolf) 22h ago
Official Accounts
@NVIDIAAI NVIDIA AI
Read more below.
— NVIDIA AI (@NVIDIAAI) 16h ago
https://t.co/04zO6rJK6h
We're contributing open models, weights, data and research to the Open Secure AI Alliance.
— NVIDIA AI (@NVIDIAAI) 16h ago
This includes NVIDIA Labs Object-Oriented Agents (NOOA): open agent harness research in the form of an object-oriented framework that reaches state-of-the-art results across software https://t.co/Wg2DO7yrDc
We tested Nemotron 3 Ultra on agentic chip design.
— NVIDIA AI (@NVIDIAAI) 1d ago
The task is RTL coding: a model iteratively writes the code that defines a chip's logic, runs it through a simulator, reads the failures, and rewrites.
Across nine categories of real design work, Nemotron 3 Ultra averaged a https://t.co/BjzOsloESk
Full deep dive below.
— NVIDIA AI (@NVIDIAAI) 1d ago
https://t.co/rlPTpAT2UJ
Brain Freeze
Model sunsets and deprecations to watch.
-
gpt-4o
sunset Oct 1, 2026 (65 days)
Azure is sunsetting gpt-4o-mini on Oct 1, 2026. If you run anything on it, you have 66 days to pick a replacement. No official swap has been announced yet.
-
gpt-4o
Azure has flagged gpt-4o-mini for deprecation. No sunset date has been announced yet, but if you use it, start planning a migration path now.
The Kitchen
What ran today and what it cost.
Today's spend
$0.0630
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Last 30 days
$2.05
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