f
f — researcher or builder tracked in the Angestrom contributor network.
Repositories · 4
f/prompts.chat
f.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy.
frankroeder/parrot.nvim
parrot.nvim 🦜 - the plugin that brings stochastic parrots to Neovim.
youssef-jad/GYO-AGENTS
MCP server + prompt that turns any AI coding agent (Cursor, Claude Code, Cline, Kiro, Windsurf…) into your Digital Twin — generate a project-specific AGENTS.md and give every tool a shared, persistent memory of how you build.
taovietducofficial/ITLR-Fullstack-Recommender-RAG
Hybrid recommender system + RAG chatbot for IT courses (FastAPI + Express/TS + PostgreSQL), with an independent Data Lakehouse module (Spark/Kafka/dbt/Trino) and full CI/CD
News · 26
CARPL.ai Raises $10 Million in Series A Funding Led by IFC to Expand AI-Powered Medical Imaging Platform - Indian Startup Times
<a href="https://news.google.com/rss/articles/CBMi5AFBVV95cUxNTk1udk1MVXlBak5OLVltb3RTQ0NjcDBsN0NJSkUtbWR0Zl9sd2FfbE1Fa09yYXphR2xwOVpOZmFyaFJqTlVNUXU0NTZEbTlpVUljZnJ2QTBDRWpZOXMwanJVNExjU1BLVFV3NDEwYTZMS0RqcUtCOEw5MnRFbHQ0a2RPZXV0UExCQ1cyMFhMSnlDV29WZlNYR3ppbW9fbFk4MDd5Y00tRmNXWjdTN0NJSnJGa2dkbmZHRWRMR095V2RlZXZnUnJ5eEFJeGV6cHlUYkRjLWg0b0U0TDFGczRnMlMwUEk?oc=5" target="_blank">CARPL.ai Raises $10 Million in Series A Funding Led by IFC to Expand AI-Powered Medical Imaging Platform</a>
Morgan State to offer bachelor’s degree in artificial intelligence this fall - Baltimore Sun
<a href="https://news.google.com/rss/articles/CBMifkFVX3lxTE5lT1V0Ul9ZYzVub0FJZG1mWEhlcUZxRlpxbVJia2JVSXB4c0w0MThjcjg4eHo5ZHZjQmNQai1BVWRhNEtvUHFxOVNpWjhEX3pBQm80NHNvbHlTTldvdnYwMTB1SHNjSm5iUk5sRFpIMG5ZYmNjUUp5OGQzOUdUQQ?oc=5" target="_blank">Morgan State to offer bachelor’s degree in artificial intelligence this fall</a> <font color="#6f6f6f">Baltimore Sun</font>
DeepMind CEO calls for an independent standards body to regulate frontier AI
DeepMind CEO Demis Hassabis is proposing an AI "standards body" modeled after FINRA, to test frontier models and develop best practices for their release.
Cisco bets on small AI for cybersecurity - Axios
<a href="https://news.google.com/rss/articles/CBMif0FVX3lxTFBFakY4d1d0dUNDYmlUbGpVRHRyeHllZXRteVRiNTBVN0J4YnhJbkVvNUpaYkkxM3FHQjJLZXRpY2IwMmtfU2lXSnF5MnFkTFlvVmVjM29wV3oydXRiNldqWEJHNnMtME91MXcwdVBjV2xfY3ZfMmFSaGkxRDhfd0k?oc=5" target="_blank">Cisco bets on small AI for cybersecurity</a> <font color="#6f6f6f">Axios</font>
Qwen3.6 27B on a 5090, 6.4k sample tok/s distribution after tuning MTP/cache settings
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1unbi4a/qwen36_27b_on_a_5090_64k_sample_toks_distribution/"> <img alt="Qwen3.6 27B on a 5090, 6.4k sample tok/s distribution after tuning MTP/cache settings" src="https://preview.redd.it/l2k7gu5cb8bh1.jpeg?width=640&crop=smart&auto=webp&s=11ac282502da0ac77f19872da5649330e5967e69" title="Qwen3.6 27B on a 5090, 6.4k sample tok/s distribution after tuning MTP/cache settings" /> </a> </td><td> <!-- SC_OFF --><div clas
Price to sales forward of AI Artificial Intelligence Ventures Inc. – GETTEX:L1D - TradingView
<a href="https://news.google.com/rss/articles/CBMinAFBVV95cUxQY3FVVEp4M19OSlRCcy16bFNJTjVLUjJEZnptcThIanJvTExjNkFSU3g3SUFrYmtTbFRTWjNzSGZUOTh6WXUxVWZkZ1pJRXhtZWk3V3lFX05jMzNPYWZJeWtwZWZ6cjdva0prMmJoYlI4YURhdHdicEIzekF1X1c3ZVBLOWpNSkZkd0FvYVg5Y1JYSXdHQUtQQVV0OHA?oc=5" target="_blank">Price to sales forward of AI Artificial Intelligence Ventures Inc. – GETTEX:L1D</a> <font color="#6f6f6f">TradingView</font>
Open-Source AI Predicts Peptide Properties - Open Source For You
<a href="https://news.google.com/rss/articles/CBMiigFBVV95cUxOVXlGVG51NHZqeEVBTlVxdnZQVnBLS09Tdzk0X2JBWUVhZlYwaXQ1LTJZSkZKMkNNMlF6b203U0ZVQTFyZ2hIMW9PX1dtMjY2c1BkNTBycng3VEM5cWlwVFVhT1pTa1BOcTFlUXRwMUZ6NGttQWVEaFJvUVY1cmlXVEoxSEZhdWRSbXc?oc=5" target="_blank">Open-Source AI Predicts Peptide Properties</a> <font color="#6f6f6f">Open Source For You</font>
China's Infiforce Raises Nearly $150M in Funding to Develop 'Ego Native World Model' for Robots - AI Insider
<a href="https://news.google.com/rss/articles/CBMiyAFBVV95cUxNRjhWNkR2a19lSkphT296X1FvTVRKOS11SzNWc29HbUhXUl9oSGk5Wm4yNEtFcWxHVWh2Y3pBaFllNFQtQ0FyYm1NeFNEM2RyQVJJNXpyNTJGYWpBWUNiVjBCMmlRR0FBRUZ0dkw1cndSRjZlX0VKZEFiaFNMZDFqdFctNWRPNllwbXJJZmVBbU9MT3BfTjZ5d1RkajROdFVYTHJlZWlDNG91YWJaMGJJV0d1VF9WZXhPNHJMVmZKUWJFMTRnS3VOdA?oc=5" target="_blank">China's Infiforce Raises Nearly $150M in Funding to Develop 'Ego Native World Model' for Robots</a> <font color="#6f6f6f">AI Insider</font>
Papers · 8
Bake It Till You Make It: Ultrafast Spatial Texture-Atlas Splatting
Recent extensions of 3D Gaussian Splatting (3DGS) capture fine color details using hash-grid-based appearance parameterization but incur high computational cost during fragment rendering. We introduce a decoupled radiance representation that models low-frequency geometry and view dependent appearance features with 2D surfels while representing high-frequency textures via a view-independent spatial hash grid that is baked into a compact texture atlas. By including sparsity-enhancing optimizations that penalize semi-transparency and per-primitive falloff, our method aggressively prunes insignifi
Resist and Update: Counterfactual Report Coordinates for Incentive-Compatible LLMs
Aligned language models routinely misreport under non-evidential incentive pressure: they agree with a confident user or overstate certainty even when their internal belief is unchanged. We cast this as a failure of internal incentive-compatibility (IC) and present a method for learning and certifying counterfactual report mediators that hold a model's reports to a causal contract: invariant to forbidden influences (pressure, prestige, restyling) and responsive to licensed ones (genuine evidence). These two demands, resist and update, pull in opposite directions. We study them on a Bayesian-wi
Purified OPSD: On-Policy Self-Distillation Without Losing How to Think
On-policy self-distillation (OPSD) has emerged as a promising paradigm for improving LLM reasoning, where a privileged teacher with access to reference solutions provides token-level supervision on the student's own generated trajectories. However, we find that OPSD consistently fails on long chain-of-thought (long-CoT) reasoning models, yielding at best marginal gains while destabilizing the reflective reasoning capability these models depend on. Through a novel decomposition of the teacher's supervision signal, we identify the root cause: the teacher's supervision is dominated by a reference
AUTOPILOT VQA: Benchmarking Vision-Language Models for Incident-Centric Dashcam Understanding
Recent advances in Vision-Language Models, Large Language Models, and Multimodal Large Language Models have improved autonomous driving tasks such as scene understanding, decision making, trajectory prediction, and visual question answering. However, evaluating whether these models can reliably reason about safety-critical incidents remains challenging. To address this gap, we present AUTOPILOT-VQA, an incident-centric visual question answering benchmark for dashcam video understanding. The dataset evaluates different systems through structured questions designed around real-world driving inci
Semantic-Driven Scale and Spatial Selection for Efficient Cross-Modal Alignment in Referring Remote Sensing Image Segmentation
Referring Remote Sensing Image Segmentation (RRSIS) seeks to localize and segment the target object or region specified by a natural language expression in a remote sensing image. While existing RRSIS models have benefited from large-scale foundation models, they predominantly rely on full fine-tuning. These approaches are computationally intensive and may weaken the generalization ability of pre-trained models, as extensive fine-tuning on significantly smaller downstream datasets can distort the well-structured feature representations learned during large-scale pre-training. Although Paramete
Causal Inference for Sequential Settings under Interference and Latent Confounding
We study causal inference under outcome interference for sequential, observational settings. Specifically, we consider settings where the binary outcomes over N units are Markovian across T time steps. At each time step, the outcomes of N units have dependencies captured through an Ising model; each outcome is also impacted through an external field capturing the effects of its treatment as well as latent confounders. Similar to panel data literature, these latent confounders are modeled to have a low-rank factor structure. Our data is a single sample from this high-dimensional distribution. T
Beyond Pixel Overlap: A Framework for Decomposing Segmentation Evaluation Metrics
Evaluation metrics are central to binary target segmentation because they determine how progress is measured, compared, and interpreted. In this paper, target denotes the task-defined positive region to be segmented rather than a generic foreground object. It may be salient, camouflaged, transparent, glass-like, mirror-like, shadow-like, lesion-like, or defined by other application-specific semantics. We treat existing metrics as compositions of modular design choices rather than isolated formulas. The proposed framework decomposes each metric into five stages covering prediction representatio
World from Motion: Generative Dynamic Gaussian Reconstruction from Monocular Video
We present World from Motion, a method for generating freely renderable dynamic 3D Gaussian representations from monocular videos. Our approach conditions a video model on dense, pixel-aligned renderings that encode appearance, geometry, and 3D scene motion along both input and target camera trajectories to correct rendering artifacts and fill in missing regions from an initial reconstruction. To train this model, we construct a dataset of aligned multiview video pairs and dynamic 3DGS representations, with simulated artifacts characteristic of monocular reconstruction. At test time, we distil