Search: “tutorials”

arXiv:2604.09886v1 Announce Type: cross Abstract: Accurate volume estimation of objects from visual data is a long-standing challenge in computer vision with significant applications in robotics, logi

🔐 One deployment, isolated data per user. Add custom auth so every user gets their own scoped threads, runs, and conversation history — with per-user data isolation and role-based access using any aut

arXiv:2604.09701v1 Announce Type: new Abstract: Detecting unseen anomalies in unstructured environments presents a critical challenge for industrial and agricultural applications such as material recy

Michael Roddan / The Information: Polymarket is auditing its Builders Program, which gives up to $2.5M in grants, after concerns that some participating startups are facilitating insider trading — Pol

arXiv:2602.10751v2 Announce Type: replace Abstract: We study the problem of predicting numeric labels that are constrained to the integers or to a subrange of the integers. For example, the number of

arXiv:2604.10586v1 Announce Type: cross Abstract: This paper explores Online Continual Self-Supervised Learning (OCSSL), a scenario in which models learn from continuous streams of unlabeled, non-stat

arXiv:2604.11178v1 Announce Type: cross Abstract: Forecasting neural activity in response to naturalistic stimuli remains a key challenge for understanding brain dynamics and enabling downstream neuro

arXiv:2604.11112v1 Announce Type: cross Abstract: Class-incremental learning (CIL) aims to continuously accumulate knowledge from a stream of tasks and construct a unified classifier over all seen cla

This r/ollama community guide provides a practical breakdown of which AI language models (and combinations of models) can realistically fit within the unified memory constraints of common Apple Silico

arXiv:2604.11407v1 Announce Type: cross Abstract: We revisit retrieval-augmented generation (RAG) by embedding retrieval control directly into generation. Instead of treating retrieval as an external

arXiv:2604.10929v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) provide robots with contextual reasoning abilities to comprehend human instructions. Yet, current LLM-en

arXiv:2510.03843v4 Announce Type: replace-cross Abstract: Manually editing pasted code is a long-standing developer pain point. In internal software development at Google, we observe that code is past

arXiv:2603.03197v3 Announce Type: replace Abstract: Classifying fine-grained visual concepts under open-world settings, i.e., without a predefined label set, demands models to be both accurate and spe

arXiv:2604.10071v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable reasoning capabilities yet continue to suffer from hallucination, where generated

arXiv:2604.11089v1 Announce Type: new Abstract: Image tokenizers are central to modern vision models as they often operate in latent spaces. An ideal latent space must be simultaneously compact and ge

arXiv:2604.10228v1 Announce Type: new Abstract: Current multimodal models often suffer from shallow reasoning, leading to errors caused by incomplete or inconsistent thought processes. To address this

arXiv:2501.07773v3 Announce Type: replace Abstract: Generative modeling of symmetric densities has a range of applications in AI for science, from drug discovery to physics simulations. The existing g

arXiv:2508.02204v4 Announce Type: replace Abstract: Adept manipulation of articulated objects is essential for robots to operate successfully in human environments. Such manipulation requires both eff

The second technique was two-phase post-training. We first trained purely for capability, then added a latency penalty calibrated from real dogfooding data based on the CDF of how long users stay on S

For years, the promise of “no-code” artificial intelligence has felt a bit like a “some assembly required” IKEA desk — sure, you aren’t sawing the wood yourself, but you’re trying to decipher how to a

arXiv:2509.26627v2 Announce Type: replace Abstract: Designing dense rewards is crucial for reinforcement learning (RL), yet in robotics it often demands extensive manual effort and lacks scalability.

arXiv:2604.09692v1 Announce Type: new Abstract: Synthesizing realistic piano hand motions requires both precision and naturalness. Physics-based methods achieve precision but produce stiff motions; da

Peter Diamandis announced the launch of his book 'WE ARE AS GODS: A Survival Guide for the Age of Abundance,' which he described as his best work to date. The book likely explores themes of technologi

arXiv:2604.11193v1 Announce Type: new Abstract: Multi-hop Knowledge Graph Question Answering (KGQA) requires coherent reasoning across relational paths, yet existing methods often treat each reasoning

arXiv:2602.18679v2 Announce Type: replace Abstract: Large-scale foundation models for scientific machine learning adapt to physical settings unseen during training, such as zero-shot transfer between

arXiv:2604.10848v1 Announce Type: new Abstract: Sequence modelling requires determining which past tokens are causally relevant from the context and their importance: a process inherent to the attenti

arXiv:2604.10074v1 Announce Type: new Abstract: Transformer-based diffusion models have demonstrated remarkable performance at generating high-quality samples. However, our theoretical understanding o

arXiv:2604.10056v1 Announce Type: new Abstract: Unsupervised optical flow methods typically lack reliable uncertainty estimation, limiting their robustness and interpretability. We propose U^{2}Flow,

arXiv:2604.11729v1 Announce Type: cross Abstract: General first-order methods (GFOM) are a flexible class of iterative algorithms which update a state vector by matrix-vector multiplications and entry

arXiv:2604.09948v1 Announce Type: new Abstract: Although hyperspectral image (HSI) classification is critical for supporting various environmental applications, it is a challenging task due to the spe

arXiv:2604.11111v1 Announce Type: cross Abstract: The rapid adoption of AI tools such as ChatGPT has significantly transformed academic practices, offering considerable benefits for both students and

arXiv:2604.10970v1 Announce Type: new Abstract: Background: Task-specific microscopy datasets are often small, making it difficult to train deep learning models that learn robust features. While self-

arXiv:2604.09885v1 Announce Type: new Abstract: Recent work has shown that probing model internals can reveal a wealth of information not apparent from the model generations. This poses the risk of un

The author provided an update on several ongoing technical projects, including the ATOM Report, a new post-training course, and

arXiv:2604.11809v1 Announce Type: new Abstract: Finding matching keypoints between images is a core problem in 3D computer vision. However, modern matchers struggle with large in-plane rotations. A st

⚡️ Zig 0.16 is out. And the new I/O model is a huge shift. • Swap implementations (threaded, evented, etc.) • Write code that looks blocking but runs async • Composable like allocators https://ziglang

Another great AiE in the books, this time in 🇪🇺 Europe for Arize AI and @arizephoenix So great to see all the homies again and learn a few things myself in one of my favorite cities Great themes this

arXiv:2412.18735v3 Announce Type: replace-cross Abstract: In recent years, researchers have leveraged social relations to enhance recommendation performance. However, most existing social recommendati

arXiv:2604.09201v1 Announce Type: new Abstract: Camera-controllable video generation aims to synthesize videos with flexible and physically plausible camera movements. However, existing methods either

arXiv:2604.08723v1 Announce Type: cross Abstract: Preference optimization methods such as DPO and KTO are widely used for aligning language models, yet little is understood about what properties of pr

arXiv:2604.08922v1 Announce Type: new Abstract: Complex degradations like noise, blur, and low resolution are typical challenges in real world image fusion tasks, limiting the performance and practica

arXiv:2408.01257v2 Announce Type: replace-cross Abstract: Coordination is a fundamental aspect of life. The advent of social media has made it integral also to online human interactions, such as those

arXiv:2604.08554v1 Announce Type: cross Abstract: The public text record -- the material from which both people and AI systems now learn -- is increasingly shaped by its own outputs. Generated text en

from my experience, even the best models (Opus 4.6, 5.4 xhigh / 5.3 codex) cannot write good code today without an amount of work that is equivalent to just doing the work myself am excited for a worl

arXiv:2510.24718v3 Announce Type: replace Abstract: Autoregressive video diffusion models are capable of long rollouts that are stable and consistent with history, but they are unable to guide the cur

This post demonstrates how Lambda enables scalable, cost-effective reward functions for Amazon Nova customization. You'll learn to choose between Reinforcement Learning via Verifiable Rewards (RLVR) f