Knowledge catalogue
arXiv:2606.29166v1 Announce Type: cross Abstract: Adaptive video streaming is a widely used technique for delivering video content over the internet. One of the key challenges is determining the optim
arXiv:2606.30388v1 Announce Type: cross Abstract: Delayed generalization (ie~grokking) refers to the phenomenon in which a neural network fits its training data early in training but only begins to ge
A study from @Stanford showed that 71.3% of chatgpt queries could be accurately answered by a local model. I suspect a major part of enterprise AI workloads could be run locally too for free (compared
Financial Times: A study of 22K US companies shows those spending most heavily on AI are adding workers faster than peers, but most gains are among tech companies and startups — Study of 22,000 US com
arXiv:2606.28337v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are often evaluated using final answer accuracy, even though their failures can originate from preprocess
arXiv:2606.28896v1 Announce Type: cross Abstract: Synthetic aperture radar (SAR) data augmentation is important for improving the generalization of data-driven SAR interpretation models, yet practical
arXiv:2606.28926v1 Announce Type: cross Abstract: In-context learning (ICL) is an emerging paradigm that employs the semantic information inherent in large language models (LLMs) for generating answer
arXiv:2606.28519v1 Announce Type: new Abstract: Training operator-learning models for large-scale problems governed by partial differential equations (PDEs) is challenging due to the curse of dimensio
arXiv:2606.29065v1 Announce Type: new Abstract: Rolling motion planning is challenging because rolling contact imposes nonholonomic constraints and the configuration evolves on a curved manifold. The
a very cool Harbor x LangSmith flow I love to help you “look at the data”: 1. you do evals or rollouts for RL 2. all reward metrics and traces and rollouts get automatically propulates into Experiment
arXiv:2606.28431v1 Announce Type: cross Abstract: Fluorescence microscopy images are degraded by noise and diffraction-induced blur, which compromise structural fidelity and limit quantitative analysi
arXiv:2606.28943v1 Announce Type: new Abstract: Learning to bid in repeated multi-unit auctions with bandit feedback poses a fundamental challenge. Existing methods often rely on rigid explore-then-ex
arXiv:2606.29090v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has become the standard way to ground large language models in external knowledge, yet most systems retrieve a fi
arXiv:2603.12575v2 Announce Type: replace Abstract: Diffusion Transformers (DiTs) are a dominant backbone for high-fidelity text-to-image generation due to strong scalability and alignment at high res
arXiv:2606.29806v1 Announce Type: cross Abstract: Action-values are foundational to many control algorithms such as Q-learning. Therefore learning action-values efficiently is central to reinforcement
arXiv:2502.18864v2 Announce Type: replace Abstract: Scientific discovery is driven by scientists generating novel hypotheses for complex problems that undergo rigorous experimental validation. To augm
arXiv:2606.29715v1 Announce Type: new Abstract: This paper presents an automatic system for recognizing pulmonary diseases in chest X-rays using geometric normalization of the lung region. The method
arXiv:2606.30072v1 Announce Type: new Abstract: Cooperative tasks in Multi-Agent Reinforcement Learning (MARL) require agents to collectively maximize a shared return. Under the Centralized Training w
arXiv:2606.28833v1 Announce Type: new Abstract: Quantum kernel estimation on near-term hardware is shot-budgeted: every entry of the kernel Gram matrix is a Bernoulli expectation that must be sampled
arXiv:2509.20848v2 Announce Type: replace-cross Abstract: In the classic point location problem, one is given an arbitrary dataset X subset R^d of n points with query access to an unknown halfspace f
arXiv:2606.30275v1 Announce Type: new Abstract: Home robots require reliable vital signs monitoring to support long-term companionship and safety in daily environments, yet obtaining respiration and h
arXiv:2511.05934v2 Announce Type: replace Abstract: Generative modeling frameworks have emerged as an effective approach to capture high-dimensional image distributions from large datasets without req
arXiv:2604.02176v3 Announce Type: replace Abstract: While textual frequency has been validated as relevant to human cognition in reading speed, its relatedness to Large Language Models (LLMs) is seldo
arXiv:2606.29275v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) are typically trained under fixed context structures, restricting denoising to predetermined token subsets. This create
arXiv:2606.29347v1 Announce Type: cross Abstract: Adaptive Financial Transformer (AFT) is proposed for stock return prediction under non-stationary financial markets. The model incorporates a Market R
arXiv:2606.28652v1 Announce Type: cross Abstract: Online high-dimensional regression requires algorithms that can update sequentially while preserving structural sparsity. We propose extit{Adaptive It
arXiv:2606.29029v1 Announce Type: new Abstract: Small Object Detection (SOD) is a fundamental yet challenging problem in computer vision due to its limited spatial resolution and weak visual cues. Alt
Added this for everyone else through the /usage command! Run `/usage` and get this breakdown wherever you use Hermes Agent :) starting today you can now see a breakdown of your context usage per sessi
arXiv:2606.28326v1 Announce Type: cross Abstract: This research aims to solve the challenge of video retrieval from massive datasets, caused by ambiguous user queries. Prevailing single-round retrieva
arXiv:2606.29665v1 Announce Type: cross Abstract: This paper examines how metric adjustments to Multidimensional Scaling (MDS) can enhance its effectiveness as a visual tool for pattern recognition. T
arXiv:2606.28635v1 Announce Type: new Abstract: Inverse rendering requires separating illumination from surface materials, which is highly ambiguous due to their tight coupling in observed images. Whi
arXiv:2606.28416v1 Announce Type: cross Abstract: Deep neural networks (DNNs) have shown outstanding performance in visual recognition tasks within vision sensor networks; however, they are still vuln
arXiv:2606.29716v1 Announce Type: new Abstract: This paper addresses the problem of monocular metric depth estimation in aerial UAV imagery. Although recent data-driven methods have achieved remarkabl
arXiv:2606.30151v1 Announce Type: new Abstract: Integrating large language models into robotic systems holds promise for enhancing autonomy, yet practical deployment remains constrained by strict hear
arXiv:2511.01472v2 Announce Type: replace Abstract: The rapid progress of vision--language models (VLMs) has sparked growing interest in robotic control, where natural language can express the operati
arXiv:2603.07744v2 Announce Type: replace Abstract: Precise object placement remains underexplored in aerial manipulation, where most systems rely on predefined target coordinates and focus primarily
After 18 months of writing, coding, and experimenting, Build a Reasoning Model (From Scratch) is finally out! My first copies just arrived! 📚 440 full-color pages. Inference scaling, reinforcement lea
arXiv:2606.29230v1 Announce Type: new Abstract: Reconstructing continuous 3D human poses from unconstrained videos is challenging, especially in extreme motion scenarios involving severe motion blur a
arXiv:2606.29472v1 Announce Type: new Abstract: SWE-agent established the action interface as an underexplored design axis for software-engineering agents; we make the analogous case for the observati
arXiv:2606.28739v1 Announce Type: new Abstract: Large language models increasingly act as agents: they call tools, move money, delete records, and send messages on a user's behalf. To keep them safe,
arXiv:2606.28733v1 Announce Type: new Abstract: LLM agents are expected to act over multiple turns, using search, browsing interfaces, and terminal tools to complete user goals. Yet not every goal is
arXiv:2512.15044v2 Announce Type: replace Abstract: Integrated sensing and communication (ISAC) has emerged as a key development direction in the sixth-generation (6G) era, which provides essential su
This article likely explores how agentic AI systems can proactively monitor patient health data and manage clinical risks at scale, improving healthcare delivery through autonomous AI agents. It proba
The article covers the Supabase plugin for OpenCode, an AI coding agent, which bundles the Supabase MCP server and agent skills for direct database and project interaction . The plugin ships official
arXiv:2606.28347v1 Announce Type: cross Abstract: Contemporary AI safety spans pre-training interventions, post-training alignment, deployment-time controls, monitoring, and red-teaming. These methods
arXiv:2604.00835v2 Announce Type: replace Abstract: Large language models are increasingly being deployed as autonomous agents yet their real world effectiveness depends on reliable tools for informat
arXiv:2606.13669v2 Announce Type: replace Abstract: Current LLM-based research agents have advanced through agent orchestration, yet largely overlook scientific knowledge orchestration. Existing works
Code-writing AI agents can solve complex problems more effectively than agents using other approaches, but deploying them requires executing potentially untrusted generated code within sandboxed or is
arXiv:2601.23225v2 Announce Type: replace-cross Abstract: Deep reinforcement learning (RL) is increasingly deployed in resource-constrained environments, yet go-to function approximators - multilayer
agree a lot with this - the actual storage layer for memory (eg which database you use) matters less than the process around that data (retrieval, ingestion, etc) @hwchase17 what if memory is not stor
Agree is a TypeScript library by Boris Cherny that provides a schema validation and serialization system, enabling developers to define data schemas with type safety and validate data at runtime. The
Artificial intelligence is transforming what is possible in agriculture, but industry leaders should be wary of investing in AI without first laying the groundwork. The use cases are promising, especi
Ahmad Osman discusses the technological and practical reasons why locally-run AI models are becoming increasingly competitive with cloud-based alternatives, likely covering improvements in model effic
arXiv:2603.17975v2 Announce Type: replace Abstract: We present AHOY, a method for reconstructing complete, animatable 3D Gaussian avatars from in-the-wild monocular video despite heavy occlusion. Exis
Orlando Crowcroft / Financial Times: AI and vibe coding fuel a surge in game releases; ATTN Economy says 181K mobile games launched in six months to May, up 118% on iOS and 73% on Android YoY — More i
Dina Bass / Bloomberg: AI inference startup Etched raised 800M from investors including Jane Street and a TSMC-linked venture firm, and says it has signed sales contracts worth 1B — Nvidia rival says
Peter Campbell / Financial Times: AI may help transform air traffic control by processing vast amounts of data, spotting collision risks early, and easing staff shortages as air travel grows — The tec
arXiv:2606.29194v1 Announce Type: new Abstract: Automated alpha mining holds the scoring function fixed and varies the search algorithm over it. A search that converges against a fixed scorer overfits
arXiv:2606.29871v1 Announce Type: new Abstract: We present the AI Training Manager, a bounded LLM-based supervisory controller for adaptive machine learning training. Standard training pipelines often
arXiv:2606.28331v1 Announce Type: cross Abstract: The widespread deployment of generative artificial intelligence (AI) models has raised serious concerns about the proliferation of AI-generated conten