Search: “deployment”

An Initial Study of Physiological Markers for Deepfake Speech Detection

arXiv:2610.18934v1 Announce Type: cross Abstract: Conventional deepfake speech detectors primarily target synthesis artifacts and often degrade under unseen attacks or recording conditions. Human spee

applicationsarxiv-cs-cv

Human

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Agents

ANASSA: From High-Level Framework to Low-Level Architecture for Spatial Agentic AI

DGX agent

arXiv:2610.14382v1 Announce Type: new Abstract: Agentic AI systems operating over geospatial data require more than autonomous reasoning and tool use; they must also support explicit orchestration, sp

agentsarxiv-cs-ai

15 Oct 2026

Beyond Accuracy: Counterfactual Fragility and Demographic Bias in Clinical Evaluation of LLMs

arXiv:2609.32807v2 Announce Type: replace Abstract: Clinical LLM evaluation often emphasizes answer accuracy; however, accuracy alone does not test counterfactual consistency or demographic robustness

safetyarxiv-cs-ai

Local Ai

Calibration and Risk-Budgeted Decisions with System One Models

arXiv:2610.19811v1 Announce Type: cross Abstract: LLM workflows and agents rely on a set of binary decisions like allow/block an input, or discard/retain a retrieved document. When human deferral is u

local-aiarxiv-cs-lg

Collective Learning for Unified Robotic Manipulation via Predictive Dynamics Adaptation

arXiv:2610.19141v1 Announce Type: new Abstract: Learning a collective policy for state-based Cartesian manipulation across diverse robotic embodiments presents a fundamental challenge due to embodimen

Local Ai

DD-GBP: Anytime Multi-Arm Planning and Continuous Execution via Distributed Dynamic Gaussian Belief Propagation

arXiv:2610.20460v1 Announce Type: new Abstract: Safely executing long-horizon multi-arm tasks online in complex dynamic environments remains challenging. We propose a new distributed dynamic Gaussian

local-aiarxiv-cs-ro

Decoupling Search from Reasoning: A Vendor-Agnostic Grounding Architecture for LLM Agents

arXiv:2606.18947v2 Announce Type: replace Abstract: Production LLM agents increasingly depend on real-time search, yet native search grounding bundles retrieval policy, provider choice, evidence injec

safetyarxiv-cs-ai

Divergent Paths: Learning an Outcome-Predictive Representation of LLM Agent Trajectories

arXiv:2610.19614v1 Announce Type: cross Abstract: In this work, we reframe agentic trajectories as paths through a shared embedding space of actions and environmental observations. We show that succes

safetyarxiv-cs-cl

Evaluating LLMs as Agentic Workflow Executors in Real-World Customer Support Skills

model-releasesarxiv-cs-cl

arXiv:2610.14346v2 Announce Type: replace Abstract: Enterprise customer-support agents increasingly rely on Large Language Models (LLMs) to execute bounded, tool-using workflows. We study this problem

Evidence-Anchored Overdose Death Prediction from Death Investigation Reports

arXiv:2610.19556v1 Announce Type: new Abstract: Confirmation of overdose deaths in the United States is often delayed due to the complexities of certifying drug-involved deaths. Death investigation re

researcharxiv-cs-cl

FDE-Bench: Evaluating End-to-End Delivery from Underspecified Real-World Business Requests

arXiv:2610.14539v1 Announce Type: new Abstract: Real-world business requests often leave key requirements unstated because frontline practitioners struggle to articulate rules they know from experienc

FinGREAT: Evaluating LLMs on Financial Graph-guided Retrieval And Typing

model-releasesarxiv-cs-lg

arXiv:2610.19240v1 Announce Type: new Abstract: Financial disclosures express the underlying relationships of double-entry accounting through unstructured text. While financial LLM benchmarks predomin

FLUX 3 Image Klein: Open weights image generation and editing

model-releasesr-stablediffusion

Black Forest Labs (BFL), the frontier AI research lab building visual intelligence, today announced the open weights release of FLUX 3 Image Klein, its most capable open weights image model to date. F

From Unreliable to Usable: Decomposing Failure Modes and Confidence Signals in LLM Entity Extraction - Evidence from Cyber Threat Intelligence

model-releasesarxiv-cs-cl

arXiv:2610.20417v1 Announce Type: new Abstract: Audits of large language model (LLM) extraction from full-length documents report severe unreliability, leaving two questions open: what the failures ac

Handoff Curves: Initial Selection, Later Handoff, and Supervision Targets in Multi-turn LLM Routing

arXiv:2610.15993v1 Announce Type: new Abstract: We study how initial model selection, later handoff, and training targets affect success and cost in LLM tasks that span multiple turns. We compare seve

HankelKANet: Lightweight Path Loss Estimation via Physics-Inspired Hankel Convolution

model-releasesarxiv-cs-lg

arXiv:2610.19524v1 Announce Type: new Abstract: Accurate path loss (PL) estimation is essential for wireless network planning and optimization. This paper proposes HankelKANet, a lightweight physics-i

Hierarchical Residual Policy Learning for Real-World Mobile Manipulation with Sparse Human Guidance

arXiv:2610.20607v1 Announce Type: cross Abstract: Mobile Manipulation (MoMa) is a cornerstone of autonomous robotic systems, yet real-world fine-tuning remains a formidable challenge because of high-d

safetyarxiv-cs-lg

HM3D-M3: A Benchmark for Multi-Agent, Multi-Modal, Multi-Object Goal Navigation

model-releasesarxiv-cs-ro

arXiv:2610.20121v1 Announce Type: new Abstract: Rapid progress in AI agents and robotics makes it a matter of the near future that humans are served by a team of robots. Such a team will receive sever

Human Demonstrations as Post-Training Data for Any Robot Body: Retargeting the Object, Not the Hand

arXiv:2610.20351v1 Announce Type: new Abstract: Human demonstrations are today used largely for pretraining vision-language-action models, with little ability to use the same data for target-embodimen

Introducing Muse Spark Open: the most capable US open-weight model to date

model-releasesr-localllama

Hey r/LocalLlama - Today we’re excited to release Muse Spark Open, the most capable US open-weight model to date. Built for coding and agentic work, it excels at long-horizon tasks, complex software e

JAL-Turn: Joint Acoustic-Linguistic Modeling for Real-Time and Robust Turn-Taking Detection in Full-Duplex Spoken Dialogue Systems

arXiv:2603.26515v2 Announce Type: replace-cross Abstract: Efficient and robust turn-taking detection remains a significant challenge in industrial-grade voice AI agents. Existing systems often rely on

applicationsarxiv-cs-ai

Hardware

JointServe: Serving Multi-Model Agents on Memory-Constrained GPUs

arXiv:2610.19822v1 Announce Type: cross Abstract: LLM agents are evolving from a single model calling tools to planners that orchestrate multiple expert models whose capabilities live in distinct weig

hardwarearxiv-cs-lg

Kandinsky S2V 1.0: Audio-Driven Avatar Video Generation

model-releasesarxiv-cs-cv

arXiv:2610.19290v1 Announce Type: new Abstract: We present Kandinsky S2V 1.0, an open family of speech-to-video models for controllable audio-driven human animation, comprising Kandinsky S2V 1.0 Lite

Agents

Keep Your Receipts: Trustworthy Cleanup of Agent-Built Knowledge Graphs

arXiv:2610.17719v1 Announce Type: new Abstract: Agents build knowledge graphs as memory, and building them has become easy. Maintaining them has not. When a source is retracted, overruled, or erased,

agentsarxiv-cs-ai

KinoGen: Customizable Humanoid Loco-Manipulation References via Kinematically Grounded Video Generation

arXiv:2610.20552v1 Announce Type: new Abstract: We present KinoGen, a framework that synthesizes customizable humanoid loco-manipulation references through kinematically grounded video generation. Kin

researcharxiv-cs-ro

Learning from Demonstrations meets Symbolic Control - A Supervisory Control Architecture for Formal Certification of Learned Motion

arXiv:2610.19815v1 Announce Type: new Abstract: Dynamical system (DS)-based learning from demonstration generates flexible robot motions, but existing guarantees rely on certificate generation to obta

Hardware

Learning in Orbit: Onboard Training and Closed-Loop Attitude Control with a Thermal Segmentation Model on a Spacecraft

arXiv:2610.19122v1 Announce Type: new Abstract: Deep space missions increasingly require spacecraft capable of autonomously operating in environments with communication delays and bandwidth limitation

hardwarearxiv-cs-ro

Limits of Statistical Assurance for Embodied and Agentic AI under Adaptive Adversaries

arXiv:2610.18948v1 Announce Type: cross Abstract: Finite safety assessments cannot exclude an adversary that preserves unattacked behavior until certification and activates afterward. We characterize

safetyarxiv-cs-lg

Meta Muse Spark Open is live on Together AI

model-releasestogether-ai-blog

Meta’s Muse Spark Open, a high‑capacity US open‑weight model for agentic software engineering, is now live on Together AI as a Day 0 launch partner. The model supports a 1‑million‑token context window

Modeling and Understanding Neural Weights of Humanoid Policies with Diffusion

arXiv:2610.20606v1 Announce Type: cross Abstract: Recent advances in robot learning have driven rapid progress in humanoid control, enabling increasingly agile behaviors in the real world. However, hu

applicationsarxiv-cs-lg

Nvidia expands Nemotron LLM family with hyper-efficient models for agentic systems

model-releasessiliconangle

Nvidia Corp. today announced the launch of customizable Nemotron 3.5 Super LV large language models for always-on artificial intelligence agents and edge-focused 3.5 Bolt for local systems. The compan

NVIDIA Nemotron 3.5 Super VL Powers Specialized Agents with Multimodal Reasoning

model-releasesnvidia-developer

NVIDIA’s open‑source Nemotron 3.5 Super VL is a 120 B parameter mixture‑of‑experts multimodal model that activates only 12 B parameters per token, enabling combined reasoning, instruction following, t

nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB · Hugging Face

model-releasesr-localllama

https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-GGUF https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-LiLiCorr-GGUF NVIDIA Nemotron 3.5 Bolt 74B-A9B 24GB is a vi

Hardware

Old friends are the best friends. Jensen rocks. The Star Mind computer being co-engineered by SpaceX and Nvidia is far better than almost an…

Old friends are the best friends. Jensen rocks. The Star Mind computer being co-engineered by SpaceX and Nvidia is far better than almost anyone expects and will reach volume production next year. Wor

hardwareelon-musk--x

OmniPoser: Flexible Human Motion Recovery in the Wild with Masked Flow Matching

arXiv:2610.19857v1 Announce Type: new Abstract: Recovering 3D human motion from sparse wearable sensors is challenging due to the inherent noise, occlusion, and instability of real-world tracking sign

applicationsarxiv-cs-cv

Agents

Penumbra: Sample-Efficient Adversarial Search for Regulatory Obligations

arXiv:2610.04693v2 Announce Type: replace Abstract: Agents are entering finance, healthcare and law, sectors where a violation leaves no lexical signature and carries real penalties. Whether an omissi

agentsarxiv-cs-ai

PLACID: Privacy-preserving Large language models for Acronym Clinical Inference and Disambiguation

model-releasesarxiv-cs-cl

arXiv:2603.23678v2 Announce Type: replace Abstract: Large Language Models (LLMs) offer transformative solutions across many domains, but healthcare integration is hindered by strict data privacy const

PolyMorph: Learning Locomotion Policy for Cross-Embodiment Adaptation

arXiv:2610.19615v1 Announce Type: new Abstract: Reinforcement learning has enabled robust locomotion for legged robots, but learned policies are typically tied to a specific robot morphology and requi

Predicting how model propensities generalize out of distribution

arXiv:2610.14937v1 Announce Type: new Abstract: How do language models generalize from their training data? This is a central challenge for alignment: models reliably learn their training distribution

Agents

Progress-Aware Distillation for Mitigating Stagnation in Small Language Model Agents

arXiv:2610.19439v1 Announce Type: new Abstract: While LLM-based agent systems have demonstrated remarkable proficiency in reasoning and solving complex real-world tasks, they also come with substantia

agentsarxiv-cs-lg

PseudoBench: Measuring How Agentic Auto-Research Fuels Pseudoscience

arXiv:2606.18060v2 Announce Type: replace Abstract: As Large Language Model based agents enter autonomous scientific research, their ability to resist pseudoscience becomes increasingly important. Oth

Local Ai

RA^2: Retain-Anchored Attraction Preserves Forget-Adjacent Utility in LLM Unlearning

arXiv:2610.19385v1 Announce Type: new Abstract: Large Language Model (LLM) unlearning is often evaluated primarily by target suppression and clean retain utility. These metrics can miss a local failur

local-aiarxiv-cs-lg

RAN-JEPA: An Action-Conditioned World Model for Energy-efficient Mobile Network Control

arXiv:2610.17584v1 Announce Type: new Abstract: Operational mobile networks are rich in observations but poor in interventions: they continuously generate large volumes of passive telemetry, while con

researcharxiv-cs-ai

RAP-WAM: Learning World-Action Models through Predictive Rehearsal and Action Perturbations

arXiv:2610.16443v1 Announce Type: new Abstract: Recent world action models draw on video generation priors to jointly predict future observations and robot actions. Adapting these priors to control re

safetyarxiv-cs-ai

RingNav: Task-Shaped Circular Memory for Visual Heading

model-releasesarxiv-cs-cv

arXiv:2610.19044v1 Announce Type: cross Abstract: Tiny robots have limited computation and memory, yet visual navigation systems often maintain more state than a task requires. We ask whether persiste

RUBATO: Decoupled Clocks Allow Full-Duplex Models to Think as Fast as They Can

arXiv:2610.14299v1 Announce Type: cross Abstract: Recent Speech Full-Duplex (FDX) models are capable of engaging in naturalistic conversation by listening and speaking at the same time. Building on th

researcharxiv-cs-ai

Running Fewer Loops Removes Refusal Behaviour in Recurrent-Depth Language Models

arXiv:2610.15218v1 Announce Type: new Abstract: A recurrent-depth language model reuses one block of weights several times in a row. The number of repetitions, which we call loops, is chosen when the

Scale Agentic Coding Workflows with Meta’s Muse Spark Open on NVIDIA GB300 NVL72

model-releasesnvidia-developer

Meta’s Muse Spark Open is an 816‑billion‑parameter mixture‑of‑experts coding model that activates only 42 billion parameters per token through top‑8 routing across 256 experts, and has been trained on