Search: “deployment”

What makes Claude Projects so interesting is that it handles teams of agents really well, you talk to a main orchestrator agent and it spins up specialists. Basically it creates an organization to sol

arXiv:2609.16519v1 Announce Type: new Abstract: Scientific research increasingly relies on large, heterogeneous data sources, motivating interest in retrieval-augmented generation (RAG) systems that p

arXiv:2609.16880v1 Announce Type: new Abstract: Space robots are increasingly expected to perform long-duration, contact-rich, and multi-stage operations with limited human intervention. Recent advanc

arXiv:2609.16573v1 Announce Type: new Abstract: Multi-modal spatio-temporal forecasting (MM-STF) supports weather nowcasting, traffic prediction, and earth-system modeling by combining heterogeneous s

arXiv:2501.09166v2 Announce Type: replace-cross Abstract: Pretrained Transformers keep what they learned in their weights and lose what they observe once a session ends. The first version of this pape

arXiv:2609.16407v1 Announce Type: cross Abstract: On a delivery platform, personalized store ranking greatly influences what users find and order. Unlike digital-only domains, candidate stores are loc

Anyone interested in trying out a new inference provider? We're testing Gemma 4:26b and Qwen 3.8:27B behind an OpenAI-compatible API and looking for a few users to give them a spin and tell us how it

arXiv:2609.16338v1 Announce Type: new Abstract: Ternary Large Language Models (LLM) store every weight as one of three symbols {-1,0,+1}, so the cost of a ternary model is conventionally referenced to

arXiv:2503.05794v4 Announce Type: replace-cross Abstract: Speaker verification models are trained on large-scale public datasets whose licenses usually prohibit unauthorized commercial use, yet such i

arXiv:2609.16656v1 Announce Type: new Abstract: State space models (SSMs), particularly Mamba, have emerged as efficient alternatives to attention-based architectures and have been extended to vision

arXiv:2609.16091v1 Announce Type: new Abstract: Tabular foundation models deliver strong zero-training predictive performance via in-context learning, but their high inference latency makes them impra

arXiv:2509.12626v4 Announce Type: replace-cross Abstract: Aligning agentic AI with user intent is critical for delegating complex, socially embedded tasks, yet user preferences are often implicit, evo

arXiv:2609.16450v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer a promising parallel decoding paradigm as an alternative to autoregressive generation through iterative

arXiv:2609.17241v1 Announce Type: new Abstract: While draft-model-free speculative decoding offers a promising path to efficient LLM inference, it is frequently constrained by stale draft candidates a

arXiv:2609.16312v1 Announce Type: cross Abstract: One-to-many machine translation (MT) is computationally expensive for autoregressive (AR) systems, which suffer from linear latency scaling with both

arXiv:2609.16255v1 Announce Type: cross Abstract: We present an efficient method to distill reasoning capabilities into compact video-language models (VLMs) for video question answering (VideoQA). Our

arXiv:2507.01927v3 Announce Type: replace Abstract: While CNNs and ViTs dominate vision architectures, all-MLP models offer a structurally simpler alternative whose patch-independent processing is nat

arXiv:2609.17128v1 Announce Type: new Abstract: Comprehensive structured data on inter-firm relationships is often scarce or inaccessible because many relationships are privately negotiated, selective

arXiv:2609.17391v1 Announce Type: new Abstract: Model serving is one of the largest cost drivers in production recommender systems. Maximizing its throughput requires navigating a deeply layered hiera

arXiv:2609.16344v1 Announce Type: cross Abstract: Sustained emotional support is a long-horizon interaction task closely tied to human well-being. Recent research demonstrates generative agents' capac

arXiv:2609.17099v1 Announce Type: new Abstract: Human videos provide rich manipulation experience, but extracting action representations that preserve useful motion remains challenging. Visual reconst

arXiv:2609.16415v1 Announce Type: cross Abstract: Pedestrian-count forecasting supports pedestrian-oriented Intelligent Transportation Systems (ITS), including crowd monitoring, pedestrian-traffic sta

Agentic AI workflows using NVIDIA Omniverse libraries automate preparation of Blender scenes for robotics simulation by adding semantic labels, sensor definitions, physics properties and validating th

arXiv:2609.16964v1 Announce Type: new Abstract: Rapid extraction of structured information from social media is important for humanitarian response, yet existing disaster tweet resources mainly provid

arXiv:2609.17168v1 Announce Type: cross Abstract: Autonomous systems require reliable place recognition for efficient and effective simultaneous localisation and mapping (SLAM). Traditional geometric

arXiv:2609.17325v1 Announce Type: new Abstract: Biological cells can be viewed as individual, interacting agents whose collective dynamics give rise to adaptive behaviour at multiple levels of organis

arXiv:2609.16161v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown impressive capabilities across a range of natural language processing tasks, and LLM inference has emerged as a

arXiv:2609.17124v1 Announce Type: new Abstract: Offshore maintenance requires operations in the air, the surface, and the subsea domain and include human supervision. This paper presents LOTUSim-Energ

As enterprise organizations scale mission-critical applications, storage I/O and memory access can become severe operational bottlenecks. Whether its Oracle databases, in-memory databases like SAP HAN

Mem0 provides persistent user memory and agent memory; its vendor describes fact extraction, contradiction handling and relevant recall.

arXiv:2602.00532v2 Announce Type: replace-cross Abstract: Constraint handling is central to constrained black-box optimization (BBO), where objective improvement and feasibility restoration often prov

arXiv:2609.16252v1 Announce Type: cross Abstract: Machine-readable models such as SysML v2 are now programmatically accessible, and a growing body of work treats that access as the enabling condition

arXiv:2609.16984v1 Announce Type: new Abstract: Open-weight language models publish the strings their chat templates use to mark turns, roles and tool results, which the tokenizer maps back to the res

arXiv:2609.16873v1 Announce Type: new Abstract: Pediatric brain tumors are a leading cause of cancer-related mortality in children, and their small, rare, and often low-contrast subregions make accura

arXiv:2609.16189v1 Announce Type: new Abstract: Open-ended strategic wargames are high-stakes LM-based social simulations: they model adversaries, institutions, escalation, plan brittleness, doctrine,

arXiv:2609.16564v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) pipelines may omit a source's material relationship to the query. We study a pre-generation triage layer that treat

arXiv:2609.16427v1 Announce Type: new Abstract: This paper presents a Belarusian-specific data-cleaning pipeline and fine-tuning for English-Belarusian machine translation. Our cleaning pipeline disti

arXiv:2602.03344v2 Announce Type: replace-cross Abstract: Robustness is widely viewed as a key challenge for real-world applications. However, because current research focuses only on difficult tasks,

arXiv:2603.23983v2 Announce Type: replace-cross Abstract: Recent advances in real-time interactive text-driven motion generation have enabled humanoids to perform diverse behaviors. However, kinematic

arXiv:2609.16737v1 Announce Type: cross Abstract: Generative video models can serve as a promising backbone for robot navigation by predicting future observations as video plans. Recent approaches oft

arXiv:2607.09493v2 Announce Type: replace Abstract: Agentic LLM systems that generate code through multi-turn tool use face a fundamental context problem: each session starts from zero, discarding the

arXiv:2609.16621v1 Announce Type: new Abstract: Neural PDE solvers provide efficient surrogates for time-dependent physical systems, but autoregressive prediction over long horizons remains challengin

arXiv:2609.17035v1 Announce Type: new Abstract: Soft and continuum robots enable manipulation through distributed body deformation and contact, yet translating language and visual context into executa

arXiv:2609.16864v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have achieved impressive performance in quasi-static manipulation, but struggle in dynamic manipulation tasks beca

arXiv:2609.16256v1 Announce Type: new Abstract: Continuum robots enable smooth shape morphing and safe interaction in confined environments. However, most existing systems are task-specific and depend

TensorRT Edge‑LLM ran Qwen 3.6‑27B on a single NVIDIA Jetson AGX Thor and completed the MLPerf Edge Agentic benchmark in 24 min 36 s—52.33 tokens/s—which is 6.4× faster than the llama.cpp reference (2