Search: “tutorials”

arXiv:2606.27866v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) language models scale model ability with sparsely activated experts, making this architecture a standard recipe for modern larg

arXiv:2606.28249v1 Announce Type: cross Abstract: Recently, Large Language Model (LLM)-based Text-to-Speech (TTS) models have achieved remarkable naturalness. However, the standard Supervised Fine-Tun

https://longcat.chat/blog/longcat-2.0/ People are missing out on how big a deal Longcat 2.0 by Meituan (aka 'Chinese Doordash') is. Near frontier performance, trained on 50k Chinese domestic accelerat

arXiv:2606.27784v1 Announce Type: cross Abstract: The existence of adversarial attacks is often attributed to the presence of non-robust features in neural networks. While prior defenses reduce their

arXiv:2606.27988v1 Announce Type: new Abstract: Analyzing fine-grained skill activities (e.g., sports, surgery) requires not only recognizing visual patterns but also performing step-by-step visual re

arXiv:2606.28268v1 Announce Type: cross Abstract: Test-time adaptation (TTA) has emerged as a promising paradigm for mitigating distribution shifts in deep models. However, existing TTA approaches for

LLM-as-a-Judge explained in ~10 mins. Knowing how to build AI verifiers and judges is one of the most important emerging AI skills today. Here is a quick intro on the topic and where to learn how to a

arXiv:2606.27718v1 Announce Type: new Abstract: Video frame interpolation (VFI) remains a challenging task, particularly when dealing with large, non-linear motions and complex occlusions. While flow-

Masterclass deep-dive into programmatic spawning of subagents - highly encourage taking a look! @colifran_ dropping elite ball knowledge per usual this blog covers 6 common workflow patterns we see wi

arXiv:2602.17901v3 Announce Type: replace-cross Abstract: Self-supervised learning (SSL) and diffusion models have respectively advanced representation learning and generative modeling for high-dimens

arXiv:2507.06722v2 Announce Type: replace Abstract: Understanding how large language models (LLMs) internally represent and process their predictions is central to detecting uncertainty and preventing

arXiv:2606.27440v1 Announce Type: new Abstract: Foundation models for structural biology have achieved remarkable performance in predicting biomolecular structure and show promise for the design of pr

arXiv:2511.20562v2 Announce Type: replace Abstract: While recent video generation models have achieved significant visual fidelity, they often suffer from the lack of explicit physical controllability

arXiv:2606.28220v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving nonlinear partial differential equations (PDEs), including battery

arXiv:2603.09241v2 Announce Type: replace Abstract: Visual navigation requires agents to reach goals in complex environments through perception and planning. World models address this task by simulati

arXiv:2603.07844v2 Announce Type: replace Abstract: This paper bridges some of the gap between optimal planning and reinforcement learning (RL), both of which share roots in dynamic programming applie

arXiv:2502.00168v5 Announce Type: replace-cross Abstract: Supervised dimensionality reduction maps labeled data into a low-dimensional feature space while preserving class separation. A common strateg

arXiv:2606.27681v1 Announce Type: cross Abstract: World models in partially observed environments rely on latent representations that summarize interaction history, but in many modern LLM-based archit

A think tank conducted research examining how the Space Force should respond to space warfare scenarios, with experts envisioning various ways satellites and spacecraft might be used in gray-zone or w

this blog covers 6 common workflow patterns we see with dynamic subagents (fanout and synthesize, adversarial verification, etc) if you'd prefer to learn w/ a video, check out this excellent guide fro

Token spending should be understood as organizational research and development rather than purely a productivity cost, representing an investment in discovering how to restructure business processes a

arXiv:2412.20802v3 Announce Type: replace-cross Abstract: Recommender systems are widely used in the digital landscape to match users with content fitting their preferences. However, growing concerns

arXiv:2606.28133v1 Announce Type: cross Abstract: We study whether we can learn novel manipulation skills from human actions to a bi-manual robot with parallel grippers. Human action data is cheap, ab

v14 Lite Release Notes: – Distilled the intelligence from HW4 V14 into HW3. This allows HW3 to directly learn how to handle scenarios using HW4 V14 as a guide. This process unlocks the improvements th

arXiv:2505.05517v3 Announce Type: replace Abstract: Functional grasping is essential for enabling dexterous multi-finger robot hands to manipulate objects effectively. Prior work largely focuses on po

Did something happen to Opus 4.8 today? First time I've seen this happen (and I use it daily): it almost totally stopped thinking, even at highest reasoning setting. And answered terribly. I repeated

Fleet agents can be shared in channels where your company is already doing work. Slack, Teams, etc Video from Caspar showing how to bring them into Slack! For agents to spread through a company they h

Hack Your Summer I learned about this initiative from DJ Patil this morning: It’s a 4-week, high-velocity production sprint for undergraduate students, graduate students, and recent graduates who want

NEW paper worth reading. Reasoning-data curation is expensive because scoring a trace usually means reading it to the end. This new work from UCLA shows you may not have to. The quality of a reasoning

the future of AI is multi-model (including a majority of open-source ones provided by @huggingface of course!)! How to keep AI spend flat while token usage grows exponentially: Not with friction and s

The old BBC 'Industrial Revelations' series is a great overview of what makes an Industrial Revolution Steam alone wasn't enough, it required thousands of skilled workers figuring out how to apply thi

🧑‍🏫3hr Long Deep Agents Course Great course from a member of the community on Deep Agents Covers task planning, file systems for context management, subagent-spawning, and long-term memory https://www

> Better Caching – Cache misses are the easiest way to drive your cost up. All of our requests are cache aware, so we’re reusing a warm cache wherever possible. We do this for you in Deep Agents - see

How to keep AI spend flat while token usage grows exponentially: Not with friction and spend alerts. With better defaults, routing, and caching. Better Defaults (not Usage Caps) – Engineers can choose

If you use LLM-as-judge, this one is worth reading. (bookmark it) It's actually one of the most effective ways to use LLM-as-a-Judge for evals. Holistic judge scores hide both their reasoning and thei

This is very interesting. Coinbase seems to have lowered their token spend ($$) to about half, by 1) routing to cheap inference like GLM 5.2 and Kimi 2.7 that are still pretty performant 2) Smart rout

This post by Filip Hric explains how to interpret AI code review benchmarks, specifically breaking down key evaluation metrics like precision and recall that are commonly used to assess code review to

arXiv:2606.13042v2 Announce Type: replace Abstract: In intelligent video surveillance, cameras record image sequences during day and night. Commonly, this demands different sensors. To achieve a bette

Autonomy isn't the ability to act without human supervision. It's the ability to *learn* without human bottlenecks in the process. A system that is fully dependent on human training data and RL enviro

Financial Times: Binance tells EU customers that it will stop providing services for them from July 1, after Greece rejected its application for a bloc-wide license last week — World's biggest crypto

arXiv:2508.02753v5 Announce Type: replace-cross Abstract: Time Series Forecasting (TSF) faces persistent challenges in modeling intricate temporal dependencies across different scales. Despite recent

arXiv:2606.16203v3 Announce Type: replace Abstract: Post-traumatic epilepsy (PTE) is a severe complication of traumatic brain injury (TBI). Yet, early identification remains challenging due to the com

arXiv:2606.26273v1 Announce Type: new Abstract: Symmetries are important for many deep learning tasks, ranging from applications in the sciences to medical imaging. However, there is an ongoing debate

arXiv:2606.26481v1 Announce Type: new Abstract: Billions of scientific papers lead to the need to identify essential parts from the massive text. Scientific research is an activity from putting forwar

arXiv:2606.26515v1 Announce Type: new Abstract: Test Time Training (TTT) is a mechanism in which a model adapts to an incoming test-sample by performing some self-supervised (SSL) task and updating it

Forward Deployed Engineering is the most critical ingredient for Enterprise AI adoption. It’s why the most important companies on the planet are investing so heavily into it. That’s why we put togethe