Knowledge catalogue
arXiv:2604.26561v1 Announce Type: cross Abstract: Multi-agent deliberation systems using large language models (LLMs) are increasingly proposed for policy simulation, yet they suffer from artificial c
arXiv:2603.03664v2 Announce Type: replace-cross Abstract: Learning-to-communicate (LTC) in partially observable environments has received increasing attention in deep multi-agent reinforcement learnin
arXiv:2604.26184v1 Announce Type: new Abstract: A privacy-preserving clothing classification scheme is presented to enable secure occupant-centric control (OCC) systems. Although the utilization of ca
arXiv:2604.26073v1 Announce Type: cross Abstract: Industrial chemical plants often operate under strict data confidentiality constraints, making centralized data-driven process modeling difficult. Fed
arXiv:2604.26366v1 Announce Type: cross Abstract: Data quality assessment is an essential step that ensures the reliability of the subsequent structural health monitoring (SHM) tasks. This study propo
arXiv:2603.15262v2 Announce Type: replace Abstract: Modern e-commerce search is evolving to resolve complex user intents. While Large Language Models (LLMs) offer strong reasoning, existing LLM-based
arXiv:2604.26943v1 Announce Type: new Abstract: We introduce ProcFunc, a library for Blender-based procedural 3D generation in Python. ProcFunc provides a library of easy-to-use Python functions, whic
arXiv:2604.26508v1 Announce Type: cross Abstract: Deploying Vision-Language Models (VLMs) on edge devices remains challenging due to their substantial computational and memory demands, which exceed th
This post was written in April 2026. Cloud products, feature maturity, and recommended patterns change over time, so readers should treat these examples as directional guidance. For teams already usin
arXiv:2604.06061v2 Announce Type: replace Abstract: Text-to-image generation has progressed rapidly, but faithfully generating complex scenes requires extensive trial-and-error to find the exact promp
arXiv:2604.17612v2 Announce Type: replace-cross Abstract: Multi-agent systems built on large language models (LLMs) are difficult to reason about. Coordination errors such as deadlocks or type-mismatc
arXiv:2512.23726v2 Announce Type: replace-cross Abstract: The 3D fast silent multi-parametric mapping sequence with zero echo time (MuPa-ZTE) is a novel quantitative MRI (qMRI) acquisition that enable
arXiv:2604.26018v1 Announce Type: cross Abstract: We introduce QERNEL, a foundational neural wavefunction that variationally solves families of parameterized many-electron Hamiltonians and captures th
arXiv:2604.26505v1 Announce Type: cross Abstract: Dynamic quantization emerged as a practical approach to increase the utilization and efficiency of the machine learning serving flow. Unlike static qu
arXiv:2412.11399v4 Announce Type: replace Abstract: Driven by global climate change and the ongoing energy transition, the coupling between power supply capabilities and meteorological factors has bec
arXiv:2604.26834v1 Announce Type: cross Abstract: We present a quantum feature-selection framework based on a higher-order unconstrained binary optimization (HUBO) formulation that explicitly incorpor
arXiv:2604.26413v1 Announce Type: cross Abstract: This paper presents Quantum Gatekeeper, a context-bound image steganography framework where successful payload recovery depends on both cryptographic
It's a common misconception that we can't tell who is using LLM and who is not. I'm sure we didn't catch 100% of LLM-assisted PRs over the past few months, but the kind of mistakes humans make are fun
arXiv:2604.26213v1 Announce Type: cross Abstract: Loading high dimensional distributions is an important task for utilizing quantum computers on applications ranging from machine learning to finance.
arXiv:2604.26435v1 Announce Type: cross Abstract: The rapid advancement of object detection architectures has positioned single stage detectors as the dominant solution for real-time visual perception
Variational Joint Embedding (VJE) is a framework that synthesizes joint embedding and variational inference to enable self-supervised learning of probabilistic representations in a reconstruction-free
arXiv:2510.08547v2 Announce Type: replace-cross Abstract: Towards the aim of generalized robotic manipulation, spatial generalization is the most fundamental capability that requires the policy to wor
arXiv:2604.26067v1 Announce Type: new Abstract: We present RADIO-ViPE (Reduce All Domains Into One -- Video Pose Engine), an online semantic SLAM system that enables geometry-aware open-vocabulary gro
arXiv:2604.26039v1 Announce Type: cross Abstract: The optimal kernel configuration for Mixture-of-Experts (MoE) inference depends on both batch size and the expert routing distribution, yet production
arXiv:2604.26830v1 Announce Type: cross Abstract: I propose the Random Cloud method, a training-free approach to neural architecture search that discovers minimal feedforward network topologies throug
arXiv:2602.01297v3 Announce Type: replace Abstract: Electronic medical records (EMRs), particularly in neurology, are inherently heterogeneous, sparse, and noisy, which poses significant challenges fo
arXiv:2604.26450v1 Announce Type: new Abstract: Dynamical systems (DS) methods for Learning-from-Demonstration (LfD) provide stable, continuous policies from few demonstrations. First-order dynamical
Evinova is a customer case study from Cognition AI showcasing how their Devin AI platform was applied to solve real-world development challenges. The case study likely demonstrates specific productivi
arXiv:2503.17897v2 Announce Type: replace-cross Abstract: We present a real-time global illumination approach along with a pipeline for dynamic 3D Gaussian models and meshes. Building on a formulated
arXiv:2603.20133v2 Announce Type: replace Abstract: Large Language Models (LLMs) achieve strong performance on many reasoning benchmarks, yet these evaluations typically focus on isolated tasks that d
arXiv:2604.26903v1 Announce Type: cross Abstract: This paper provides a concise yet comprehensive review of recent advancements in millimeter-wave (mm-wave) oscillators below 100 GHz and sub-terahertz
arXiv:2604.26479v1 Announce Type: cross Abstract: Safety-critical prediction systems, such as autonomous vehicles, weather forecasters, and medical monitors, commonly rely on probabilistic forecasters
arXiv:2604.26242v1 Announce Type: cross Abstract: Digital biomarkers for depression have largely relied on static acoustic descriptors, pooled summary statistics, or conventional machine learning repr
The recent KubeCon + CloudNativeCon Europe event did not read like a celebration so much as an admission. AI is everywhere, but the systems underneath it are strained — not by models, but by layout. T
Safe agents don’t guarantee a safe ecosystem of interconnected agents. Microsoft Research examines what breaks when AI agents interact and why network-level risks require new approaches. The post Red-
Jonathan Vanian / CNBC: Reddit reports Q1 revenue up 69% YoY to 663M vs. 611M est., DAUq up 17% to 126.8M, above est., forecasts Q2 revenue above est.; RDDT jumps 13%+ after hours — Reddit reported be
arXiv:2507.21420v3 Announce Type: replace-cross Abstract: The computational cost of training multimodal large language models (MLLMs) grows rapidly with the number of processed tokens. Existing effici
arXiv:2602.15983v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can translate natural language into optimization code, but silent failures pose a critical risk: code that execut
Replit announced its 10th anniversary milestone and is making their Agent product free to users. The company is hosting a buildathon partnership event with Anthropic and offering prizes to encourage d
🎂 Replit turns 10 this weekend, and we're giving every Replit user free Agent for 24 hours on Saturday.🤯 Clear your Saturday. And tune in live tomorrow, Friday at 9 AM PT, when we go live to walk you
arXiv:2604.26031v1 Announce Type: new Abstract: This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challen
Scientists have reengineered bacteria to run a core part of their cellular machinery with just 19 amino acids instead of the standard 20 , focusing on eliminating isoleucine through AI-guided protein
resharing this note, find it helpful given all the great open evals work + teams building vertical agents Evals are a proxy for the behavior we want our agent to exhibit in production Model+Harness pu
arXiv:2604.26851v1 Announce Type: cross Abstract: When generative AI (genAI) systems are used in high-stakes decision-making, its recommended role is to aid, rather than replace, human decision-making
arXiv:2604.25975v1 Announce Type: cross Abstract: Key-value (KV) caching is essential for large language model inference, yet its memory overhead poses a critical bottleneck for long-context generatio
arXiv:2603.10225v3 Announce Type: replace-cross Abstract: Cross-entropy loss has long been the standard choice for training deep neural networks, yet it suffers from interpretability limitations, unbo
arXiv:2604.05190v2 Announce Type: replace-cross Abstract: Screening patients for enrollment is a well-known, labor-intensive bottleneck that leads to under-enrollment and, ultimately, trial failures.
arXiv:2505.20414v2 Announce Type: replace-cross Abstract: Motion forecasts of road users (i.e., agents) vary in complexity depending on the number of agents, scene constraints, and interactions. In pa
arXiv:2604.00809v2 Announce Type: replace Abstract: Building on existing approaches, we revisit Human-in-the-Loop Object Retrieval, a task that consists of iteratively retrieving images containing obj
arXiv:2604.26130v1 Announce Type: cross Abstract: Every RLHF-trained language model is shaped by a reward model, yet the mechanistic interpretability toolkit -- logit lens, direct logit attribution, a
The Trump administration has appealed a federal judge's ruling that blocked Health Secretary Robert F. Kennedy Jr.'s overhaul of the nation's childhood vaccine schedule . The March 16, 2026 federal co
arXiv:2604.24966v1 Announce Type: cross Abstract: Frontier AI companies first deploy their most advanced models internally, for weeks or months of safety testing, evaluation, and iteration, before a p
arXiv:2603.07955v3 Announce Type: replace-cross Abstract: We develop a reinforcement learning pipeline for simplifying knot diagrams. A trained agent learns move proposals and a value heuristic for na
Cecilia D'Anastasio / Bloomberg: Roblox reports Q1 bookings up 43% YoY to 1.7B, vs. 1.73B est., and DAUs up 35% to 132M, below analysts' estimates of 143.8M; RBLX drops 16%+ after hours — Roblox Corp.
Clem Delangue announced an upcoming robotics announcement and asked for recommendations on journalists who cover the robotics field. The post seeks to identify credible tech journalists with expertise
arXiv:2604.26496v1 Announce Type: new Abstract: Adversarial Training (AT) is one of the most effective methods for developing robust deep neural networks (DNNs). However, AT faces a trade-off problem
arXiv:2508.12672v4 Announce Type: replace-cross Abstract: Federated Learning (FL) enables collaborative model training across multiple clients without sharing private data. We consider FL scenarios wh
arXiv:2604.26128v1 Announce Type: cross Abstract: We consider learning from labeled data collected across multiple environments, where the data distribution may vary across these environments. This pr
Todd Spangler / Variety: Roku reports Q1 revenue up 22% YoY to 1.25B, ad revenue up 27% to 613M, subscription revenue up 30%, raises 2026 profit guidance; ROKU jumps 8%+ after hours — Roku beat Wall S
arXiv:2509.07523v4 Announce Type: replace Abstract: Detecting rare events and anomalies in large-scale signals is essential in fields such as astronomy, physical simulations, and biomedical science. I