Knowledge catalogue
arXiv:2604.13102v1 Announce Type: cross Abstract: Enterprise software organizations face an escalating challenge in maintaining the integrity, security, and freshness of codebases that span hundreds o
arXiv:2604.11554v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training has proven effective at unlocking reasoning, self-reflection, and tool-use capabilities in large language mode
Eric Zakariasson posted on X (Twitter) announcing his attendance at AI Engineer London (AI Engineer Europe 2026) on both Thursday and Friday, inviting others to meet up with him. AI Engineer Europe...
arXiv:2610.22362v1 Announce Type: cross Abstract: Generative simulation can automate robot environment construction, but physically valid environments are not necessarily useful for training. The chal
https://preview.redd.it/kudj7xii5ivh1.png?width=1508&format=png&auto=webp&s=07712e81310b81aceb2cf8f4d8a7c2eadeb0c304 Just built a new PC, full parts list is here. I am using Deadcode's Radiance infere
Google’s Gemini 4 Argon is now generally available (GA), offering coding, knowledge‑work, enterprise‑workflow, and cyber‑defense features via the paid Gemini API, Google AI Pro/Ultra in the Gemini app
[UPDATE / RETRACTION: The '100% GTO' claim had a prompt-leakage bug] We patched the repo to pass strictly neutral states, here are the real, honest numbers: • Latency: Still ~2ms (ONNX + Absorbing Mar
arXiv:2603.08260v2 Announce Type: replace Abstract: Existing data generation methods for robot learning suffer from limited exploration, embodiment gaps, low signal-to-noise ratios, and domain shifts,
arXiv:2610.02563v1 Announce Type: cross Abstract: We present OpenGameEval, a benchmark and evaluation framework for agentic game development inside Roblox Studio. It runs language models as agents in
arXiv:2610.00797v1 Announce Type: new Abstract: Contextual security defenses prevent AI agents from taking rogue actions by synthesizing a task-specific policy and enforcing it on the agent's tool cal
arXiv:2609.38409v1 Announce Type: new Abstract: Recent progress in large language model reasoning has been driven by benchmarks and reinforcement learning environments with automatically verifiable re
arXiv:2609.37798v1 Announce Type: cross Abstract: Speech self-supervised learning aims to learn general-purpose representations for downstream speech tasks. However, current approaches rely on complex
arXiv:2609.34210v1 Announce Type: new Abstract: Coding agents are beginning to move beyond purely digital tasks to tackle physical-world challenges, particularly in robotics. Existing robotics benchma
arXiv:2609.30770v1 Announce Type: cross Abstract: General-purpose robot models increasingly rely on large and diverse datasets. For embodied 3D navigation, however, existing data sources face a fundam
Enterprises are increasingly standardizing on Google Kubernetes Engine (GKE) to run their most critical and AI-driven workloads. From Cloud Storage FUSE for high-throughput data access to custom compu
arXiv:2609.27442v1 Announce Type: new Abstract: 3D reconstruction from satellite imagery is essential for large-scale topographic analysis, yet the lack of high-fidelity training datasets with accurat
arXiv:2508.11584v3 Announce Type: replace-cross Abstract: Deploying multiple machine learning models on resource-constrained robotic platforms for different perception tasks often results in redundant
arXiv:2609.12653v1 Announce Type: new Abstract: Russian state propaganda spreads across many languages and online spaces. Yet, most computational work examines only one such space, usually social medi
arXiv:2609.10036v1 Announce Type: cross Abstract: Large language model agents produce fluent action sequences across a wide range of tasks, yet they fail in characteristic ways once the environment be
arXiv:2609.04442v1 Announce Type: cross Abstract: Large language models deployed in high-stakes settings frequently generate plausible but ungrounded claims. Standard retrieval-augmented generation (R
arXiv:2609.03199v1 Announce Type: new Abstract: Robot learning increasingly depends on broad and diverse demonstrations, yet collecting robot data remains expensive and poorly suited to covering the l
arXiv:2609.00106v1 Announce Type: new Abstract: This paper presents FAIRY, a full-stack smart-agriculture agent system developed for and deployed to an operating soybean research farm at Harbin Instit
arXiv:2608.24921v2 Announce Type: replace Abstract: Graph RAG connects facts no single passage states, but implementations pay three times: in infrastructure, keeping vector store, graph database and
I only started using some vLLM forks recently in a 4 x 48GB 4090 system. DS4F - ~5000pp/180tg (DSpark) Qwen3.8 Flash next - ~7500pp/135tg (MTP) This is amazing, like having the API in my house. But it
arXiv:2608.30627v1 Announce Type: new Abstract: As language-model compute continues to scale, high-quality training data is becoming an increasingly important bottleneck. Conventional next-token predi
arXiv:2608.19199v1 Announce Type: cross Abstract: We describe the evolution of a virtual assistant, called ATHENA, designed to support the capture, retrieval, and dissemination of knowledge for member
arXiv:2504.20823v3 Announce Type: replace Abstract: Accurate remaining useful life (RUL) estimation underpins safe operation and cost-effective maintenance of aerospace propulsion systems. We propose
arXiv:2507.14267v2 Announce Type: replace Abstract: Large language model (LLM) agents can execute long-horizon scientific workflows, but their numerical outputs are difficult to trust: agents lose con
arXiv:2603.20667v2 Announce Type: replace-cross Abstract: Existing prompt-optimization techniques rely on local signals, causing poor generalization across tasks. In addition, they also rely on weak u
arXiv:2608.10176v1 Announce Type: new Abstract: Public service chatbots are expected to deliver recommendations from an underlying public service directory, while also making sure that the recommendat
arXiv:2608.02919v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in complex, compound AI systems where performance hinges on the quality of prompts. Recent state-
arXiv:2608.03335v1 Announce Type: new Abstract: Video diffusion transformers (vDiTs) generate high quality but pay quadratic self-attention cost, making inference prohibitive at video-token scales. Th
Advanced Micro Devices Inc. delivered another strong quarter Tuesday, beating Wall Street expectations as its artificial intelligence infrastructure business continued its rapid expansion. The company
arXiv:2607.21588v1 Announce Type: new Abstract: Learning effective robot manipulation policies requires diverse, high-quality demonstrations, yet existing data pipelines are often difficult to scale b
arXiv:2607.16619v2 Announce Type: replace Abstract: Safe and socially compliant navigation in open human-robot environments requires robots to reason about heterogeneous participants with different dy
arXiv:2607.13154v1 Announce Type: new Abstract: Learning open-world mobile manipulation policies requires vast data to achieve spatial generalization, long-horizon robustness, and scene generalization
arXiv:2607.08252v1 Announce Type: new Abstract: Long-term persona agents must remain identifiable while adapting to new events, relationships, evidence, and social conditions. We identify self-locking
As organizations scale modern workloads — from high-throughput databases and network/security appliances to real-time analytics and AI/ML inference — network and block storage performance can quickly
arXiv:2607.06495v1 Announce Type: cross Abstract: Live sports commentary is grounded generation under a deadline: statements concern real, named athletes, the grounding state changes every few seconds
arXiv:2607.01522v1 Announce Type: cross Abstract: Mode shape recognition is a fundamental task in automotive NVH development, yet it remains dependent on manual visual inspection by experienced engine
arXiv:2606.32004v1 Announce Type: new Abstract: Policy-grounded document review requires determining whether a target document complies with organization-specific policies, guidelines, or playbooks. W
arXiv:2606.26359v1 Announce Type: new Abstract: Ray Kurzweil described a thesis of accelerating returns, which is the most influential narratives in discussions of technological progress. Its central
arXiv:2606.24420v1 Announce Type: new Abstract: In high-stakes document processing pipelines, including financial reconciliation, compliance verification, and procurement automation, an LLM extraction
arXiv:2603.21639v2 Announce Type: replace-cross Abstract: Accurately estimating human mobility in peripheral regional economies presents a fundamental measurement challenge: physical ground-truth sens
arXiv:2606.09900v1 Announce Type: cross Abstract: Long-term memory is the missing layer for LLM agents: across sessions they forget, and the common workaround -- replaying the whole history into the p
arXiv:2601.12263v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) integrate visual and textual knowledge into unified representations that increasingly underpin modern retrieval
arXiv:2606.07020v1 Announce Type: new Abstract: Multilingual and multicultural benchmarks now cover dozens of languages and model families, but the resulting score landscapes remain metric-rich and in
arXiv:2606.06159v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) have the potential to emerge as the third generation of neural networks and have attracted increasing attention across
arXiv:2603.22867v1 Announce Type: cross Abstract: Multimodal stacks that mix ViTs, CNNs, GNNs, and transformer NLP strain embedded platforms because their compute/memory patterns diverge and hard real
arXiv:2605.29107v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly rank products, documents, and recommendations for user queries, which makes manipulating these rankings a gr
British software supply chain security startup RevEng.AI says it has raised 15 million in early-stage funding after developing technology similar to Anthropic PBC’s Mythos model and working out a way
arXiv:2605.23809v1 Announce Type: cross Abstract: The Open Radio Access Network (O-RAN) architecture allows AI to be embedded directly into the RAN through modular xApps and rApps, yet creating these
arXiv:2605.23274v1 Announce Type: new Abstract: Retrieving events from large-scale video datasets is challenging due to complex temporal, spatial, and multimodal information. This paper presents U-CES
arXiv:2605.18334v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) has revolutionized real-time photorealistic view synthesis, its fundamental reliance on symmetric Gaussian distributi
arXiv:2605.15343v1 Announce Type: new Abstract: LLM-based agents are increasingly used to simulate deliberative interactions such as negotiation, conflict resolution, and multi-turn opinion exchange.
arXiv:2601.05300v2 Announce Type: replace-cross Abstract: Reasoning-oriented language models typically expose explicit reasoning as a long, front-loaded chain of 'thinking' tokens before the main outp
Most enterprise AI pilots are failing to deliver measurable AI business value, and Appian Corp. is suggesting that the culprit isn’t the technology. The gap between AI experimentation and real enterpr
arXiv:2604.25646v1 Announce Type: new Abstract: Robotic ultrasound has advanced local image-driven control, contact regulation, and view optimization, yet current systems lack the anatomical understan
arXiv:2505.02922v3 Announce Type: replace Abstract: Recent large language models (LLMs) are rapidly extending their context windows, yet inference throughput lags due to increasing GPU memory and band
arXiv:2604.21352v1 Announce Type: new Abstract: Mental health challenges are increasing worldwide, straining emotional support services and leading to counselor overload. This can result in delayed re