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12 Oct 2026

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Model Releases

When Simulation Lies: A Sim-to-Real Benchmark and Domain-Randomized RL Recipe for Tool-Use Agents

DGX agent

arXiv:2605.11928v2 Announce Type: replace Abstract: Tool-use language agents are evaluated on benchmarks that assume clean inputs, unambiguous tool registries, and reliable APIs. Real deployments viol

model-releasesarxiv-cs-ai

12 Oct 2026

Applications

AI Appeals Processor: A Deep Learning Approach to Automated Classification of Citizen Appeals in Government Services

arXiv:2604.03672v2 Announce Type: replace-cross Abstract: Government agencies must register, classify and route every citizen appeal within statutory time limits, and much of this work is still done b

applicationsarxiv-cs-ai

Clinician use of language models diverges from how the models are evaluated

arXiv:2610.11069v1 Announce Type: new Abstract: Large language model (LLM) assistants are being deployed to clinicians across health systems, and judgments about their readiness rest largely on benchm

Neural Networks for Temporal Pattern Recognition and Dynamic Arm Gesture Speed Estimation for Robot Control

arXiv:2610.11631v1 Announce Type: cross Abstract: Deploying intelligent robotic systems that interact with humans through gestures requires neural networks capable of recognizing diverse temporal patt

Ranking Prior Alignment for Credit Risk Modeling: When Do External Priors Matter?

model-releasesarxiv-cs-lg

arXiv:2610.11146v1 Announce Type: new Abstract: Cold-start credit scoring -- deploying models with scarce labeled data, weak features, or minimal capacity -- is a recurring problem in financial machin

RH-Detect: A Unified Benchmark for Reward Hacking Detection

model-releasesarxiv-cs-lg

arXiv:2610.10947v1 Announce Type: new Abstract: Reward hacking, where a model exploits an evaluation signal without completing the intended task, threatens the reliability of deployed language model s

TRACE: A Governance Framework for Measuring Explainability Debt in Production AI Systems

arXiv:2610.10957v1 Announce Type: cross Abstract: Production AI systems deployed in high-stakes domains accumulate a governance liability that existing monitoring frameworks fail to detect: the progre

Walking on Roofs: Exploring the Potential of Walking Robots for Construction Work on Roofs

arXiv:2610.12272v1 Announce Type: new Abstract: This paper investigates the feasibility of deploying quadruped walking robots for the automation of work in roof environments. While quadrupeds have dem

Bounded Autonomy and Verifiable Safety for Agentic AI Enabled Automation

model-releasesarxiv-cs-lg

arXiv:2610.08815v1 Announce Type: new Abstract: Agentic AI-enabled automation cannot be safely deployed in high-stakes environments on probabilistic reasoning alone. A recurring risk is epistemic drif

Certified by Abstention: Distribution-Free Guarantees for Chain-of-Thought Verifiers at Small Calibration Budgets

arXiv:2610.09541v1 Announce Type: cross Abstract: Signals that predict whether a chain-of-thought (CoT) trace is correct are compared by AUC, but deploying one requires a threshold with a guarantee. W

Constitution-Guided Watermarking

arXiv:2610.09552v1 Announce Type: cross Abstract: Watermarking enables language model providers to identify text generated by their models. However, its desired properties can conflict (ie~stronger wa

safetyarxiv-cs-cl

Distilling Graph Geometry: Knowledge Gap from GNNs to MLPs

arXiv:2610.10520v1 Announce Type: new Abstract: GNN-to-MLP distillation aims to retain the predictive accuracy of a message-passing teacher while deploying a graph-free MLP at inference. Existing meth

How Fragile Is On-Device Language Model Safety? Localizing Safety-Critical Parameters for Sparse Fault Analysis

arXiv:2610.09000v1 Announce Type: cross Abstract: As small language models (SLMs) are increasingly deployed on resource-constrained and on-device platforms, including as components of agentic systems,

RoboPrompt: Intuitive Robot Policy Steering with Sparse Human Input

arXiv:2610.10534v1 Announce Type: new Abstract: End-to-end robot policies trained through imitation learning remain constrained by limited data diversity, making reliable zero-shot deployment in real-

Research

Compositional Concept Erasure in Text-to-Image Diffusion Models via Hierarchically Grounded Semantic Surgery

arXiv:2610.07337v1 Announce Type: new Abstract: Removing copyrighted, unsafe, or user-specified concepts from a deployed text-to-image diffusion model is now a practical requirement. Weight-editing me

researcharxiv-cs-cv

Local Ai

Do I Need the Cloud? Uncertainty-Aware Step-Level Handoff for Small Language Model Agents

arXiv:2610.07816v1 Announce Type: new Abstract: Small language models (SLMs) are attractive as local agent controllers because they reduce remote inference, latency, and deployment footprint, yet stru

local-aiarxiv-cs-ai

Does a Learned Corrector Beat a Simple Retreat? Evidence from a Frozen VLA

model-releasesarxiv-cs-ro

arXiv:2610.06921v1 Announce Type: new Abstract: Before deploying runtime recovery for a frozen vision-language-action (VLA) policy, one must establish that an intervention improves success beyond ordi

Local Ai

DySCo: Dynamic Sharding for Collaborative Edge-Cloud LLM Inference with Depth-Synchronized Batching

arXiv:2610.08268v1 Announce Type: cross Abstract: Pervasive intelligent applications are increasingly deployed on mobile and Internet of Things (IoT) edge devices. Consequently, Large Language Models

local-aiarxiv-cs-ai

Research

How Much Planning Is Enough? Reducing Search and Computation in World-Model Planning

arXiv:2610.08350v1 Announce Type: cross Abstract: Visual world models enable goal-directed control through decision-time action search, but their deployment efficiency is often limited by conservative

researcharxiv-cs-ai

Lost in the bf16 Cast: Exporting Ternary Language Models Can Revert Most Low-Learning-Rate Code Changes

arXiv:2610.07853v1 Announce Type: cross Abstract: Ternary language models such as BitNet b1.58, Falcon-E and BitCPM are fine-tuned with higher-precision latent weights and deployed as ternary codes pr

managed deep agents 0.9 is here! things we shipped: ⏰ agents can schedule tasks OBO themselves or the user 🏭 dynamically configure your mda…

model-releasesharrison-chase--x

managed deep agents 0.9 is here! things we shipped: ⏰ agents can schedule tasks OBO themselves or the user 🏭 dynamically configure your mda per run (models, tools, skills, etc.) 👀 Slack reactions show

Research

MobileVISTA: Generative Data Augmentation for Pose Generalization in Mobile Manipulation

arXiv:2610.07511v1 Announce Type: cross Abstract: Mobile manipulators such as humanoid robots are increasingly deployed in dynamic, unstructured environments to perform dexterous manipulation tasks. H

researcharxiv-cs-cv

Performative Prediction with Selective Labels

arXiv:2610.08272v1 Announce Type: new Abstract: Many social applications of machine learning exhibit performative effects: population behavior changes in response to deployed models. Performative pred

Quantization Effects on Tool-Failure Recovery Vary Across Prompts and Evaluation Designs

arXiv:2610.07781v1 Announce Type: new Abstract: Post-training quantization reduces the cost of deploying language-model agents, but its effect on recovery from temporary tool failures can depend on ho

Local Ai

Selective Critique for Cost-Aware LLM Agents in Long-Horizon Decision Making

arXiv:2610.07335v1 Announce Type: cross Abstract: Improving the reliability of large language model (LLM) agents in long-horizon decision-making remains a key challenge. When deployed as autonomous ag

local-aiarxiv-cs-ai

Sensitivity Shaping for Latent Modeling

arXiv:2606.14585v2 Announce Type: replace-cross Abstract: Generative dynamics models enable planning in challenging systems, but safe deployment requires detecting policy-induced out-of-distribution (

SPEAR: Five Principles for Interactive Human-Agent Alignment

arXiv:2610.07204v1 Announce Type: cross Abstract: Recent AI alignment work often frames alignment as a pre-deployment optimization problem: collect human feedback, learn preferences or principles, fin

Tutorials

The Premise Is the Problem: Exchangeability Failure in Self-Monitored Test-Time Adaptation

arXiv:2610.07038v1 Announce Type: new Abstract: Modern forecasting models are often updated after deployment so they can respond to changing data. These updates can also make predictions worse, so pra

tutorialsarxiv-cs-lg

A Unified Dynamics Framework for Reinforcement Learning and Classical Control of a Six-DOF Pipeline-Tracking ROV in NVIDIA Isaac Sim

arXiv:2610.04949v1 Announce Type: new Abstract: Reinforcement learning controllers for underwater vehicles are usually trained against one physics representation and deployed against another, so repor

AFP-GIC: Controllable Generative Image Compression [R]

model-releasesr-machinelearning

Hi ML Community, I am excited to share our latest framework, AFP-GIC, officially published in IEEE Access (2026). We have released the deployment codebase and hosted an interactive visual playground.

ASCENT: Online Test-Time Training of Long-Horizon Agents via Self-Distillation of Verified Experience

arXiv:2610.05303v1 Announce Type: new Abstract: A large language model (LLM) agent solves long-horizon tasks through many reasoning-action turns, with one verification signal at termination. Deployed

Agents

Building A Multi-Sensor Platform For Autonomous Driving Research: Challenges and Lessons Learned

arXiv:2610.05604v1 Announce Type: new Abstract: This paper reports on the challenges encountered and lessons learned during the development and deployment of a flexible multi-sensor platform for auton

agentsarxiv-cs-ro

Demonstration-Calibrated Port-Hamiltonian Retuning for Manipulation Policies

arXiv:2610.05755v1 Announce Type: new Abstract: Diffusion and VLA policies for manipulation are often deployed through downstream impedance controllers. The stiffness and damping gains of these contro

Agents

IBPA: Real-time Free-form Manifold Mesh Reconstruction via Incremental Ball Pivoting with Integrated Hole Detection

arXiv:2607.11627v2 Announce Type: replace-cross Abstract: Both Remotely Operated underwater Vehicles (ROVs) and Autonomous Underwater Vehicles (AUVs) are frequently deployed to acquire geometric bathy

agentsarxiv-cs-ro

On Semi-Markov Suboptimality in Hierarchical Reinforcement Learning

arXiv:2610.05338v1 Announce Type: new Abstract: Hierarchical reinforcement learning uses temporally extended subtasks for exploration, yet committing to their execution can restrict both deployment an

Agents

Proxy Confidence: Auditing Black-Box LLM Agents with a Surrogate's Log-Probabilities

arXiv:2610.03894v1 Announce Type: cross Abstract: A deployed LLM agent emits tool calls, queries, and code that can be silently wrong -- by the time the error surfaces, the action has run. Frontier ch

agentsarxiv-cs-lg

Hardware

Rethinking Streaming-Perception Evaluation on Heterogeneous Edge Platforms

arXiv:2610.05578v1 Announce Type: cross Abstract: Multi-camera streaming perception is increasingly deployed on heterogeneous edge platforms shared with co-resident workloads, yet accelerator placemen

hardwarearxiv-cs-cv

Applications

16-bit Precision of Convolutional Neural Networks on Microcontroller Units for 8-bit Costs

arXiv:2610.03402v1 Announce Type: new Abstract: To deploy deep neural networks on edge hardware, highly efficient inference schemes are necessary that retain high accuracy. This work presents W16A16,

applicationsarxiv-cs-lg

Designing the Future of User Feedback for Generative AI

arXiv:2610.02631v1 Announce Type: new Abstract: Post-deployment feedback from users can be a cost-effective, scalable, and representative means to monitor and improve generative AI systems and feature

DNAlign: Dynamic Null-Space Safe Alignment for LLMs

arXiv:2610.02844v1 Announce Type: new Abstract: Ensuring the safe and reliable deployment of large language models (LLMs) remains a fundamental challenge. Existing safety alignment approaches either i

From Migration to Calibration: Preserving Agent Capabilities across Models, Jurisdictions, and Scale

arXiv:2609.35149v2 Announce Type: replace Abstract: Deploying, migrating, or scaling an agent can change its model, harness, infrastructure, application, and intended users. We formulate agent calibra

Hardware

Hardware-Native Joint Sparse-Quantization for Trillion-Scale Mixture-of-Experts

arXiv:2610.02241v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures allow frontier language models to scale to trillions of parameters, but their deployment is constrained by mass

hardwarearxiv-cs-ai

Hardware

Lightweight and Resource-Efficient Perception for Robotic Guide Dogs

arXiv:2610.03187v1 Announce Type: cross Abstract: Multi-camera streaming perception is increasingly deployed on heterogeneous edge platforms shared with co-resident workloads, yet accelerator placemen

hardwarearxiv-cs-cv

Self-Repairing Recurrent Ensembles for Real-Time Recovery from Distribution Shift

model-releasesarxiv-cs-ro

arXiv:2610.03249v1 Announce Type: cross Abstract: Deploying a pretrained controller exposes it to conditions that are absent from its training data. Sensor drift, outright sensor failure and accumulat

Syntheses

Synthesis: R-Chatgpt

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Auto-generated synthesis of 2074 entries about r-chatgpt

4 Oct 2026

Syntheses

Synthesis: Techmeme

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Auto-generated synthesis of 3157 entries about techmeme

4 Oct 2026

Agent Evaluation Reliability: More Tasks Won't (Always) Fix An Agent Leaderboard

arXiv:2610.00651v1 Announce Type: new Abstract: Agent evaluations are increasingly used to compare LLMs and inform deployment decisions, yet ranks can reflect not only the model but also the effects o