Search: “models”

Evaluating Real-Time Voice Agents: From Component Quality to Grounded Outcomes

arXiv:2609.30798v1 Announce Type: new Abstract: Real-time voice agents have moved from research prototypes to production deployments, yet the literature describing them is fragmented across three comm

agentsarxiv-cs-ai

Human

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Safety

Evolutionary Safety of Recursive Self-Improving AI: Taxonomy, Risk Discovery, and Evaluation

DGX agent

arXiv:2609.31186v1 Announce Type: new Abstract: Artificial intelligence is advancing rapidly, with increasingly capable systems taking larger roles in reasoning, decision-making, scientific discovery,

safetyarxiv-cs-ai

28 Sept 2026

Forensic Twins: Self-Supervised Residual Learning for AI-Generated Image Forensics

arXiv:2609.31514v1 Announce Type: new Abstract: Detectors of AI-generated images are typically trained using samples from all Generative AI architectures they must catch, and struggle as soon as a new

From Visual Search to Movement Control: A Priority Field for Artificial Agents

arXiv:2609.30704v1 Announce Type: new Abstract: Human spatial attention is widely conceptualized as being guided by a priority map that integrates perceptual salience, current goals, and past experien

agentsarxiv-cs-ro

From Weak Data to Strong Policy: Q-Targets Enable Provable In-Context Reinforcement Learning

arXiv:2609.30391v1 Announce Type: new Abstract: Existing in-context reinforcement learning methods mainly pretrain Transformers with supervised behavior-prediction objectives. This enables task infere

safetyarxiv-cs-lg

Geometric Feature Learning for Functional Data Valued on the Symmetric Positive Definite Manifold

arXiv:2609.30487v1 Announce Type: new Abstract: We here develop a functional neural network, termed MatFAE, for learning trajectories on the Riemannian manifold of symmetric positive definite (SPD) ma

tutorialsarxiv-cs-lg

Hardware

How NVIDIA DSX MaxLPS Maximizes AI Factory Throughput and Efficiency

NVIDIA’s DSX MaxLPS employs policy‑governed power sharing to dynamically reallocate power across GPU resources, enabling up to 40 % more GPUs within the same approved power budget. In a joint test at

hardwarenvidia-developer

Hardware

I-Parakeet: Integer-Only Conformer ASR on Mobile NPU

arXiv:2609.30846v1 Announce Type: new Abstract: In this paper, we propose I-Parakeet, an integer-only implementation of NVIDIA's Parakeet-CTC (0.6B parameters) that runs on a smartphone NPU without an

hardwarearxiv-cs-cl

Improving Molecular-Morphology Contrastive Pretraining using Deep-Learning-based Morphology Profiles

arXiv:2609.30433v1 Announce Type: new Abstract: Recent advancements in image-based profiling techniques have enabled the collection of high-volume cell morphology data, allowing new molecular embeddin

tutorialsarxiv-cs-lg

Indeed OpenAI was incompetent (and arrogant in thinking they knew it all); new cybersecurity software that they should have written themselv…

Indeed OpenAI was incompetent (and arrogant in thinking they knew it all); new cybersecurity software that they should have written themselves may help. But whether it’s enough to stop all of this rem

safetygary-marcus--x

LLPR: Location-aware learning and physics-based reconstruction for raindrop removal from a single image

arXiv:2609.30758v1 Announce Type: new Abstract: Raindrops can cause occlusion and distortion in the background scenes due to their adherence to windows or camera lenses. Existing raindrop removal meth

tutorialsarxiv-cs-cv

Momentum-Guided Federated Split Distillation for Personalized Temporal Edge Intelligence

arXiv:2609.31159v1 Announce Type: new Abstract: We propose a momentum-guided federated split distillation framework for personalized, efficient, and autonomous temporal edge intelligence. We introduce

agentsarxiv-cs-ai

NVIDIA Open Agent Safety Platform: A Reference for Continuous In-Silicon Agent Monitoring

The NVIDIA Open Agent Safety Platform blends the open‑source OpenShell runtime—executing autonomous AI agents in kernel‑isolated sandboxes—with hardware‑based enforcement via NVIDIA Sentry on BlueFiel

safetynvidia-developer

OC-GS: Gaussian Splatting for Irregular Turntable Capture

arXiv:2609.31572v1 Announce Type: cross Abstract: Uneven rotation and dropped frames make equal-angle assumptions unreliable for turntable reconstruction. We present OC-GS, an object-centric Gaussian

PICO: Projection-Informed Consistency Optimisation for 6DoF Surgical Tool Pose Estimation

arXiv:2609.30989v1 Announce Type: new Abstract: Purpose: Accurate 6 DoF pose estimation of surgical tools is critical for automa- tion, robotic proprioception, and safe interaction with the tissue ope

Preserve-and-Compose Training for Composed Image Retrieval

arXiv:2609.31202v1 Announce Type: new Abstract: Composed image retrieval (CIR) aims to retrieve images that satisfy a user-specified modification while preserving relevant visual content from a refere

Quantizing Looped Transformers: Feedback Exposure and Calibration Blindness

arXiv:2609.30820v1 Announce Type: cross Abstract: Looped transformers reuse weights across recurrence steps, making low-bit quantization especially attractive. We identify two distinct failure modes o

researcharxiv-cs-cl

Applications

REALMS: An AI-Assistant Conversational System for Real-Time Exact Audience Sizing over High-Dimensional Nested Profiles

arXiv:2609.30547v1 Announce Type: new Abstract: Audience sizing is a critical component of digital marketing. It enables precise resource allocation, campaign planning, and performance optimization. T

applicationsarxiv-cs-cl

SPADE: Escaping the Popularity-Similarity Frontier to Measure Serendipitous Recommendations

arXiv:2609.31164v1 Announce Type: cross Abstract: Recommender systems engineer serendipity to foster active exploration and break predictable consumption cycles. The problem with existing offline beyo

Statistical attribute alignment for black-box generative AI via output post-processing

arXiv:2609.31607v1 Announce Type: cross Abstract: Generative AI systems are increasingly used, but aligning their outputs with user requirements poses a continuing challenge. Here, we aim to ensure th

Subjects, Not Authors: The Authorship Hazard in Agentic Dataspaces

arXiv:2609.30614v1 Announce Type: cross Abstract: Dataspace connectors decide whether a transfer may occur, not what the transferred value contains, tolerable for contracted applications, not for LLM

The Residual Stream's Effective Depth

arXiv:2609.31098v1 Announce Type: new Abstract: We introduce effective depth (Deff), a scalar diagnostic that treats the layer-wise residual stream of a transformer as a discrete-time process, measure

researcharxiv-cs-lg

TinyCVIO: A Constellation-Aided Visual-Inertial Odometry System for Nanodrones

arXiv:2609.30358v1 Announce Type: new Abstract: Nanodrones require accurate, real-time state estimation under severe sensing and computational constraints. We present TinyCVIO, a visual-inertial odome

researcharxiv-cs-ro

Toward AI-Augmented Cooperative Engineering Workflows: Requirements and Architecture the European Rover Challenge

arXiv:2609.31136v1 Announce Type: new Abstract: The growing availability of Artificial Intelligence (AI) tools creates new opportunities to support engineering design processes, yet their current use

Training-Free Pronunciation Transcription via Text-Constrained Acoustic Rescoring

arXiv:2609.30924v1 Announce Type: new Abstract: Accurate and efficient pronunciation transcription is essential for preparing text-to-speech training data at scale. Existing approaches have different

researcharxiv-cs-cl

Transformer-based Monte Carlo Localization in Construction Meshes

arXiv:2609.31357v1 Announce Type: new Abstract: To be able to perform inspection or digitization tasks, mobile robots on construction sites must be able to localize themselves reliably with respect to

local-aiarxiv-cs-ro

Trust Guided Decision Transformer

arXiv:2609.31586v1 Announce Type: new Abstract: Decision Transformer performance degrades on long rollouts because the conditioning context drifts out of the training distribution. We show that this d

researcharxiv-cs-lg

Up and Down the Abstraction Ladder: Code-Based Skills for Language Agents

arXiv:2609.31076v1 Announce Type: new Abstract: Language agents struggle to act and learn in environments that require long sequences of low-level actions. Code-based abstractions can make these agent

local-aiarxiv-cs-ai

Vision-Based 6-DoF Grasp Pose Estimation for Robot Cloth Unfolding

arXiv:2609.31452v1 Announce Type: cross Abstract: Cloth manipulation is a challenging task due to the deformable and high-dimensional nature of cloth, which leads to complex interaction dynamics and p

What Do They Fix? LLM-Aided Categorization of Security Patches for Critical Memory Bugs

arXiv:2509.22796v2 Announce Type: replace-cross Abstract: Open-source software projects are foundational to modern software ecosystems, with the Linux kernel standing out as a critical exemplar due to

researcharxiv-cs-lg

Tools

What Jev’s probabilities reveal that repeated LLM judgments miss

I tested Jev and five LLM judges across ten Arize Phoenix evaluators to measure how often their answers changed alongside accuracy, cost, and latency. The post What Jev’s probabilities reveal that rep

toolsarize-ai

When Does Advection-Aware Graph Nowcasting Help? A Controlled Study of Distributed Solar Ramp Forecasting with a Self-Supervised Cloud-Motion Estimator

arXiv:2609.30286v1 Announce Type: cross Abstract: Short-term forecasting of cloud-induced power ramps across a network of distributed photovoltaic (PV) or irradiance sensors is a recognised pain point

Applications

Where Does Retrieval-Based Open-Ended Evaluation Fail? Automatic Taxonomy Induction from Long-Form Medical Answer Factuality Verification

arXiv:2609.30467v1 Announce Type: new Abstract: Retrieval-based factuality evaluation, where LLM-generated claims are verified against evidence from authoritative medical corpora, has become the domin

applicationsarxiv-cs-cl

Navigating Cost Efficient Hardware in these Volatile Times

Where to even begin on this one...I guess I should start by acknowledging the risk vs reward for vendors other than nvidia, so: Yes I understand that nvidia are dominant currently on speed (llm and im

local-air-localllama

stunning confirmation of my central work

stunning confirmation of my central work Transformers struggle to generalize to tasks they were not explicitly trained on. Instead, we propose in 2026 that it is the job of the harness to generalize t

safetygary-marcus--x

“They literally told their agents to go forth and steal all the data for training with NOT SANDBOXES but open containers WITH FULL INTERNET …

“They literally told their agents to go forth and steal all the data for training with NOT SANDBOXES but open containers WITH FULL INTERNET ACCESS. I have no idea why people are not in jail over this.

safetygary-marcus--x

Which of the 16gb VRAM qwen3.8 27b’s is the best?

I’m having a hard time finding out which one gives you fastest speed, maximum context with best possible quality. I can run unsloth qwen3.8 27b iq4_xs with 65k q8 kv, context without MTP and vision of

local-air-localllama

Keep your agent harness minimal, folks. This paper from MIT CSAIL shows why. (bookmark it) While being very minimal it looks effective and p…

Keep your agent harness minimal, folks. This paper from MIT CSAIL shows why. (bookmark it) While being very minimal it looks effective and promising for building self-improving agents. They present JA

agentsdair-ai--x

26 Sept 2026

Applications

Worst thing about this is we have no idea if GPT-6 was specifically post trained on Nethack or not. Zero transparency about the training dat…

applicationsethan-mollick--x

Worst thing about this is we have no idea if GPT-6 was specifically post trained on Nethack or not. Zero transparency about the training data and environments. You can't independently evaluate the sig

26 Sept 2026

Yann LeCun, Executive Chairman of AMI Labs, explains why LLMs are mostly retrieving human knowledge rather than thinking for themselves: LeC…

Yann LeCun, Executive Chairman of AMI Labs, explains why LLMs are mostly retrieving human knowledge rather than thinking for themselves: LeCun starts with why so many people misread what these systems

researchyann-lecun--x

26 Sept 2026

A Multimodal Dataset for Survival Prediction in Resected Pancreatic Ductal Adenocarcinoma

arXiv:2609.29726v1 Announce Type: new Abstract: Survival research in pancreatic ductal adenocarcinoma (PDAC) is limited by the scarcity of datasets linking whole-slide histology with clinical, molecul

A Risk-Adaptive and Evidence-Constrained Framework for Generative AI Feedback in Programming Education

arXiv:2609.29874v1 Announce Type: new Abstract: Generative artificial intelligence can turn learning analytics into personalized support, but feedback systems must decide when to intervene, which evid

A Study of the Limits of Collaborative DCT-Based Image Denoising via Interpretable Neural Networks

arXiv:2609.29334v1 Announce Type: new Abstract: Image denoising remains a fundamental problem in image restoration, with applications in photography, biomedical, and scientific imaging. Modern deep ne

tutorialsarxiv-cs-cv

A Vision-Language Framework for Measuring Social Life on Sidewalks

arXiv:2609.28476v1 Announce Type: cross Abstract: While a number of methods exist for counting pedestrians in street-view imagery, these mostly ignore the social dimensions of pedestrian activity. A s

AERIAL: Adversarial Evaluation of Robustness in Accuracy-Preserving Low-Precision EEG Decoders

arXiv:2609.30037v1 Announce Type: new Abstract: Deployment-oriented compression is attractive for resource-constrained brain--computer interfaces (BCIs), but whether it changes adversarial vulnerabili

safetyarxiv-cs-cv

AI-based detection of worsening heart failure from low-resolution telemonitoring data

arXiv:2609.29742v1 Announce Type: new Abstract: Objective: Heart failure (HF) presents a healthcare challenge due to its high comorbidity burden, aging patient population and frequent hospitalizations

agentsarxiv-cs-ai

Anatomy-Aligned Surface Field Learning for Myocardial Reconstruction from Sparse Short-Axis Cine MRI

arXiv:2609.29825v1 Announce Type: new Abstract: Patient-specific 4D myocardial reconstruction from cine MRI supports quantitative functional assessment, regional motion analysis, and simulation-based

Anatomy-aware cross-speaker adaptation of complete vocal-tract acoustic-to-articulatory inversion

arXiv:2609.29766v1 Announce Type: cross Abstract: Cross-speaker acoustic-to-articulatory inversion requires accounting for anatomical differences between speakers. We propose a geometric adaptation fr