Knowledge catalogue
arXiv:2605.26418v1 Announce Type: cross Abstract: A properly calibrated rule-based autoscaler can beat every one of six mainstream deep reinforcement learning (DRL) algorithms on cost across every wor
Agentic artificial intelligence security startup 7AI Inc. today announced the launch of PLAID ELITE, a fully managed AI-native security operations service. The new service combines autonomous investig
arXiv:2605.24823v1 Announce Type: new Abstract: Manufacturing has passed through four widely recognized paradigms - mechanization, electrification, programmable automation, and Smart Manufacturing - e
arXiv:2605.25092v1 Announce Type: cross Abstract: Long-term conversational memory is a retrieval workload classical IR was not built for: the index grows during the query stream, query types shift int
arXiv:2512.10961v2 Announce Type: replace-cross Abstract: A growing body of empirical research suggests that generative AI narrows performance gaps between novice and expert workers on routine tasks--
arXiv:2605.25402v1 Announce Type: cross Abstract: Self-supervised pre-training paradigm has gained increasing prominence for learning transferable representations in medical imaging, yet existing meth
arXiv:2605.24520v1 Announce Type: cross Abstract: Missense variant interpretation remains challenging because pathogenicity depends on heterogeneous evidence from population frequency, evolutionary co
arXiv:2605.24381v1 Announce Type: cross Abstract: Time series forecasting drives operational decisions in areas like finance, transportation, and energy. While supervised learning approaches achieve s
arXiv:2602.19878v3 Announce Type: replace Abstract: The Open Digital Rights Language (ODRL) represents policy constraints as triples of a left operand, an operator, and a value. Several spatial operan
Release b9333 of llama.cpp adds support for Apple device IDs in the Metal framework for GPU acceleration on macOS and iOS . The build includes compiled binaries for multiple platforms including macOS,
arXiv:2605.25549v1 Announce Type: cross Abstract: High-quality expert chain-of-thought (CoT) data is one of the core bottlenecks in large language model (LLM) post-training. Existing data production m
arXiv:2605.25826v1 Announce Type: cross Abstract: We develop a branched signature kernel solver for linear and nonlinear ordinary differential equations driven by a single observed trajectory of a pos
Building agents (like software) is a deeply iterative process --> this is why we try to supply as much easy to use tooling and infra as possible so builders can start on their agent improvement journe
arXiv:2605.24696v1 Announce Type: cross Abstract: Streaming network intrusion detection systems must process flows continuously while keeping memory bounded, but most current methods leave alerting th
arXiv:2605.24300v1 Announce Type: cross Abstract: Large language models (LLMs) are widely used for code generation, but their security reliability remains inconsistent across languages and prompting s
everyone is talking about self-optimizing loops in software & agents. but what does that actually mean? in my mind, it's a system that observes it's own outputs, evaluates them, and uses that signal t
arXiv:2605.25717v1 Announce Type: new Abstract: Most of the world's offshore wind resource lies in waters too deep for fixed-bottom foundations, making floating offshore wind turbines (FOWTs) essentia
arXiv:2605.24760v1 Announce Type: new Abstract: We present a kinematic and transmission-aware design framework for a serial spherical mechanism with an additional translational degree of freedom for m
arXiv:2605.24002v1 Announce Type: cross Abstract: Computational materials science and chemistry span vast knowledge domains and fractured software ecosystems. Although large language models (LLMs) hav
arXiv:2605.24660v1 Announce Type: cross Abstract: Before an LLM agent can use a tool, a retrieval system must decide which candidate tools to show to the agent. How long should that shortlist be? Show
Huge one for developers building with AI. Excited to announce @ClementDelangue (CEO @huggingface) is joining DASH 2026 for a fireside chat with @oliveur. Open source changed software, open models are
arXiv:2605.24217v1 Announce Type: new Abstract: As Large Language Models (LLMs) transition from research environments to production deployments, evaluating their performance against strict Service Lev
arXiv:2605.24502v1 Announce Type: cross Abstract: We introduce a physics-inspired continuous relaxation framework that yields substantially improved solutions for NP-hard combinatorial optimization pr
arXiv:2605.24207v1 Announce Type: cross Abstract: Deep learning over relational databases is conventionally realized by translating data into graph representations and applying graph-based neural netw
arXiv:2605.25203v1 Announce Type: cross Abstract: We apply the influence-adaptive Walsh geometry of a companion theory paper (arXiv:2605.01637) to extreme low-bit weight-only LLM quantization. The rec
arXiv:2605.25058v1 Announce Type: cross Abstract: Current AI interaction models treat the prompt as the primary object of exchange, omitting a critical layer: the user's latent source intent, the goal
arXiv:2605.25641v1 Announce Type: new Abstract: Agentic retrieval-augmented generation (RAG) systems in complex B2B (business-to-business) settings may often receive free-form response feedback. Rathe
arXiv:2605.25141v1 Announce Type: cross Abstract: Reliable forecasting of renewable energy generation is a foundational requirement for grid stability energy trading battery scheduling and carbon awar
arXiv:2602.01086v2 Announce Type: replace Abstract: Background: As of 2026, Large Language Models (LLMs) demonstrate expert-level medical knowledge. However, deploying them as autonomous 'Clinical Age
arXiv:2605.23951v1 Announce Type: new Abstract: The companion paper introduced a four-level verification lattice on agent-skill manifests (unverified, declared, tested, formal) and left the top level
arXiv:2605.24973v1 Announce Type: cross Abstract: VLM-based OCR models have become the de facto choice for document parsing, as they can accurately extract page-level elements (e.g., paragraphs within
arXiv:2605.23917v1 Announce Type: new Abstract: Modern scientific discovery is bottlenecked not by data scarcity, but by the inability to synthesize fragmented knowledge into actionable hypotheses. Th
arXiv:2603.00857v2 Announce Type: replace-cross Abstract: MultiPUFFIN is a domain-informed multimodal foundation model for predicting thermophysical properties of small molecules, addressing a critica
arXiv:2502.10906v2 Announce Type: replace Abstract: Reward design plays a pivotal role in the training of game AIs, requiring substantial domain-specific knowledge and human effort. In recent years, s
arXiv:2605.26110v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) achieve versatility by reformulating diverse tasks into a unified instruction-following framework via instruc
arXiv:2601.06201v2 Announce Type: replace-cross Abstract: Enterprises are confronted with an unprecedented escalation in cybersecurity vulnerabilities, with thousands of new CVEs disclosed each month.
The NVIDIA RTX PRO 4500 accelerates genomic sequencing and drug discovery by slashing processing times. This professional desktop GPU features 32GB of ultra-fast GDDR7 memory and Blackwell architectur
arXiv:2605.24016v1 Announce Type: cross Abstract: Diffusion inference remains costly for edge deployment, yet existing accelerators focus almost exclusively on score networks because standard drift is
arXiv:2605.23967v1 Announce Type: cross Abstract: In biological systems, sensing is not performed by the brain alone: the body deforms, vibrates, and filters external stimuli before they are transduce
arXiv:2506.18543v2 Announce Type: replace-cross Abstract: The rapid proliferation of Large Language Models (LLMs) has heightened concerns regarding their exposure to jailbreak attacks, which craft adv
arXiv:2605.26014v1 Announce Type: cross Abstract: Many video reasoning tasks require tracking motion, temporal order, and evolving visual states across frames. Existing methods built on large vision-l
arXiv:2605.25566v1 Announce Type: new Abstract: Clinical decision-making requires reasoning over incomplete, imprecise, and linguistically expressed patient narratives. While large language models (LL
arXiv:2605.24239v1 Announce Type: cross Abstract: Many existing Artificial Intelligence (AI) solutions on mobile devices rely on an extensive collection of sensitive data, raising privacy concerns and
arXiv:2605.23263v1 Announce Type: cross Abstract: Embodied agents, which couple intelligent decision-making with physical actuation in the real world, impose far more stringent and heterogeneous commu
arXiv:2605.23247v1 Announce Type: new Abstract: In this paper, we introduce the first machine learning framework for predicting optimal processing times in Single-Level Tree Network (SLTN) architectur
arXiv:2605.23471v1 Announce Type: cross Abstract: Aggressive driving is a major cause of traffic accidents and poses a serious threat to road safety. Although deep learning methods have shown promisin
arXiv:2605.23699v1 Announce Type: new Abstract: Video prediction is increasingly viewed as a path toward generalizable world models, yet it remains unclear whether these systems learn underlying causa
arXiv:2605.23262v1 Announce Type: new Abstract: The development of LLM agents has led to a growing body of work on knowledge-work AI, including coding, research, and healthcare. However, current knowl
arXiv:2502.17119v2 Announce Type: replace-cross Abstract: Deep generative models have made rapid progress in image, text, audio, and video generation, and are increasingly being applied to structured
arXiv:2511.13904v2 Announce Type: replace Abstract: Cameras are a core sensing modality in modern intelligent transportation systems (ITS), providing rich visual information on road-user activities. M
arXiv:2605.23271v1 Announce Type: cross Abstract: The rapid evolution of generative video foundation models has propelled the field toward professional-grade cinematic synthesis. To achieve such deman
arXiv:2605.22848v1 Announce Type: cross Abstract: Global food security depends on predicting crop responses to climate variability, yet process based crop models remain too computationally expensive f
Its very limiting that a big set of very hard problems that we have just lying around are Erdos problems. Don’t get me wrong, they are quite cool, but we really need hard problems repositories for man
arXiv:2605.23643v1 Announce Type: cross Abstract: Tools like Tamarin and ProVerif have achieved notable success in analyzing and verifying complex real-world protocols such as EMV, 5G, and WPA2, even
Listen to my conversation with @jerryjliu0 of @llama_index on Spotify: https://bit.ly/3v1R0Tu Apple: https://bit.ly/4bTCwpD Youtube: https://bit.ly/3uXthnv LinkedIn: http://bit.ly/3Xs8GQP Website: htt
arXiv:2605.23102v1 Announce Type: cross Abstract: Large language models (LLMs) offer a scalable mechanism to elicit domain-informed prior information for high-dimensional variable selection. However,
arXiv:2602.13473v2 Announce Type: replace Abstract: Although foundation models have demonstrated remarkable success in general domains, the application of these models to electroencephalography (EEG)
nice write up from the HuggingFace folks aggregating works on defining agents, harnesses, environments, RL, etc. The more we can roughly have a shared vocabulary the better…I still find it confusing (
arXiv:2605.23712v1 Announce Type: cross Abstract: Reconstructing flow fields from sparse measurements is a fundamental problem in fluid mechanics with broad implications for modeling, control, and des
arXiv:2605.23296v1 Announce Type: new Abstract: Long-horizon LLM agents accumulate growing conversation histories that eventually exceed the model's context window. Context compaction via LLM-based su