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Q-Learning with Scalar Adjoint Matching

arXiv:2610.10437v1 Announce Type: new Abstract: Flow policies capture rich and diverse action distributions, and fine-tuning them with off-policy RL to improve beyond the demonstrations has drawn grow

safetyarxiv-cs-lg

Q-PACE: Dynamic Precision Allocation for Quantization-Aware Training

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arXiv:2610.09183v1 Announce Type: new Abstract: Quantization-aware training (QAT) leverages lower-precision arithmetic to reduce the cost of LLM deployment, but aggressive quantization degrades final

researcharxiv-cs-lg

8 Oct 2026

Applications

Q-PhotoMarket: A Design Space Exploration Framework for Photonic Hybrid Quantum Neural Networks in Financial Market Prediction

arXiv:2610.09641v1 Announce Type: cross Abstract: Photonic quantum computing has recently emerged as a promising platform for hybrid quantum machine learning due to its native realization of linear-op

applicationsarxiv-cs-lg

Quad-State Safety Evaluation of Open-Weight Large Language Models on Non-Canonical Inputs

model-releasesarxiv-cs-cl

arXiv:2610.09033v1 Announce Type: new Abstract: Standard safety evaluations of large language models assess harmful requests written in canonical plain text, while models in real-world deployment rout

Quadratic Weak-to-Strong Generalization in Random Feature Networks via Random Matrix Theory

arXiv:2610.09044v1 Announce Type: cross Abstract: Weak-to-strong generalization is the phenomenon where a strong student model trained with labels produced by a weak teacher model is able to generaliz

QuadTok: Quadtree Visual Tokenizer for Autoregressive Image Generation

arXiv:2610.10497v1 Announce Type: new Abstract: We introduce QuadTok, a novel framework for visual tokenization and autoregressive image generation. Compared to traditional approaches using 2D grids o

QuanLing: Cross-Branch Validation of Language Distance Quantification on Western Romance

arXiv:2610.08851v1 Announce Type: new Abstract: Quantifying language distance among closely related languages remains a core challenge in quantitative linguistics. Our previous work [1] introduced Qua

researcharxiv-cs-cl

Quantifying Volumetric Risk: Class-Aware Asymmetric Weighted Conformal Prediction for 3D Medical Image Segmentation

arXiv:2610.09392v1 Announce Type: new Abstract: Reliable volumetric segmentation is critical for clinical diagnostics, yet foundation models such as MedSAM remain deterministic and lack calibrated unc

Quantize by Drift: Label-Free Mixed-Precision Post-Training Quantization for Text Embedders

arXiv:2610.09227v1 Announce Type: cross Abstract: Mixed-precision post-training quantization needs a per-module sensitivity signal; for a text embedder the obvious one -- the retrieval quality a modul

researcharxiv-cs-cl

Applications

Quantum anomaly detection in real scarce data

arXiv:2610.09635v1 Announce Type: cross Abstract: Anomaly detection on small and unbalanced datasets remains very challenging in machine learning, although this scenario is common in several domains,

applicationsarxiv-cs-lg

Quasi-Binarized Autoencoders: An Architecture-Independent Information Bottleneck for Medical Image Anomaly Detection

arXiv:2610.09670v1 Announce Type: new Abstract: Unsupervised anomaly detection, which learns only from normal images, is a central task in medical image analysis and remains an open problem. Reconstru

Qwen 3.8 Flash Next is so much fun for three.js

model-releasesr-localllama

Having a lot of fun experimenting with three.js. Still very far from even a demo but its tons of fun. After this project I'll want to try a godot workflow. 3.8FN truly feels like Claude 4.6 at home. U

R-CNN-Based Chess Position Recognition

arXiv:2610.09191v1 Announce Type: new Abstract: Performing chess game position recognition solely from a single image of a three-dimensional board requires predicting the position and orientation of t

researcharxiv-cs-cv

RACER: Reflective Agent Coupling Query Interpretation and Tool-Based Retrieval for Frame Selection in Long Video Understanding

arXiv:2610.08954v1 Announce Type: new Abstract: Video large language models (Vid-LLMs) excel at diverse video-language tasks by reasoning over selected frames. However, frame selection for long videos

local-aiarxiv-cs-cv

Rally Up: ‘Gears of War: E-Day’ Launches on GeForce NOW

model-releasesnvidia-blog

Gears of War: E-Day leads the charge on GeForce NOW this week, bringing Marcus Fenix and Dom Santiago’s first fight against the Locust Horde to the cloud with GeForce RTX-powered performance. A new wa

RDGSplat: Render-Dedicated Geometry for Novel View Synthesis

arXiv:2610.09173v1 Announce Type: new Abstract: 3D foundation models enable efficient novel view synthesis by carrying a Gaussian head on the representation they already use for reconstruction. Howeve

researcharxiv-cs-cv

Real-Time Joint Audio-Video Generation by Parallel Adapter Composition

arXiv:2610.10343v1 Announce Type: new Abstract: Deploying a joint audio-video diffusion transformer for real-time, interactive generation normally requires two essential modifications: block-autoregre

researcharxiv-cs-cv

Hardware

RealtimeWAM: How Fast Can I Run My World Action Model?

arXiv:2610.10079v1 Announce Type: new Abstract: World Action Models (WAMs) combine visual dynamics modeling with action generation, but their high inference latency limits responsive robot control. Re

hardwarearxiv-cs-ro

Reasoning-Token Spikes Under Prompted Untruthful Responding in Large Language Models

arXiv:2610.10405v1 Announce Type: cross Abstract: Monitoring the chain-of-thought of reasoning artificial intelligence (AI) models remains a key approach to detecting deception and other forms of misb

researcharxiv-cs-cl

REFIT: Recognize, Fix, and Test Wearable Sensor Placement Shifts without Labels

arXiv:2610.08991v1 Announce Type: new Abstract: We present REFIT, an input calibration for frozen activity-recognition models whose inertial sensors are worn differently at deployment than in training

Reflected Anchored Langevin Algorithms

arXiv:2610.09522v1 Announce Type: cross Abstract: First order Langevin algorithms for constrained sampling in machine learning, such as projected Langevin Monte Carlo which are based on discretization

Agents

Rein Security raises $25M to rein in insecure AI agents

Rein Security Inc. said today it’s trying to help enterprises protect themselves against two distinct security threats relating to agentic artificial intelligence after raising 25 million in early-sta

agentssiliconangle

RELATE: An Evaluation Framework for measuring Relational Orientation of Large Language Models

arXiv:2610.09569v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for emotional support, raising concern that sustained use may draw users away from their real-world r

safetyarxiv-cs-cl

Relational Abstractions for Spatial Reasoning with Diffusion Models

arXiv:2610.09780v1 Announce Type: new Abstract: Diffusion models excel at image synthesis, but they remain limited in their ability to reliably satisfy structured spatial reasoning constraints. In con

Removing Information Content Does Not Certify Tamper Resistance in Open-Weight Models

model-releasesarxiv-cs-lg

arXiv:2610.09004v1 Announce Type: new Abstract: Does removing harmful information make open-weight models resistant to fine-tuning attacks? We show that mutual information at release alone cannot univ

Rephrase Before You Act: Characterizing and Mitigating Language Sensitivity in Vision-Language-Action Models

arXiv:2610.10526v1 Announce Type: cross Abstract: Vision-language-action models (VLAs) are strikingly sensitive to instruction phrasing and do not inherit the language robustness of the vision-languag

safetyarxiv-cs-cl

Reproducible LLM Inference Benchmarking: A Sequential Isolation Protocol for Regression Testing

model-releasesarxiv-cs-lg

arXiv:2610.09778v1 Announce Type: cross Abstract: Reproducible benchmarking of Large Language Model (LLM) inference is challenging because repeated measurements can vary with execution and system stat

Requirement-Based Testing: Enhancing Reinforcement Learning with Game Theory

arXiv:2407.18994v2 Announce Type: replace-cross Abstract: We consider the automatic online synthesis of black-box test cases from functional requirements specified as automata for reactive implementat

Research on Deep Learning-Based Semantic Segmentation Algorithms for Subcortical Brain Structures

arXiv:1907.09194v3 Announce Type: replace-cross Abstract: Segmentation of subcortical brain structures is fundamental to computer-aided diagnosis and treatment in neurology and related clinical fields

Residual Learning in Empirical Asset Pricing

arXiv:2610.09613v1 Announce Type: cross Abstract: Shallow models are special cases of deep models, and deep models theoretically have the potential to outperform the shallow ones. However, the existin

ResidualQuant: KV Cache Quantization for Looped Transformers with 2-Bit Residuals

model-releasesarxiv-cs-lg

arXiv:2610.10381v1 Announce Type: new Abstract: Looped Transformers improve parameter efficiency by repeatedly applying shared Transformer blocks over multiple recurrent loops, increasing computationa

Revisiting Explainable AI through Model-Independent Concept Dictionaries

arXiv:2610.10301v1 Announce Type: new Abstract: Modern applications of AI rely on increasingly complex models. Explainable AI (XAI) has emerged as a set of techniques aimed at improving model transpar

safetyarxiv-cs-lg

RFPO: Rectified Flow Policy Optimization for Embodied Control

arXiv:2610.10453v1 Announce Type: new Abstract: Flow-based policies provide an expressive framework for continuous robot control, but their iterative ODE integration incurs substantial inference cost.

Right Number, Wrong State? Measuring Cross-Jurisdiction Substitution in LLM Recall of State Policy

model-releasesarxiv-cs-cl

arXiv:2610.09458v1 Announce Type: new Abstract: When an LLM answers a state-specific policy question wrongly, it may be hallucinating, or it may be returning a real value that holds in another state.

RLHND: Video Foundation Models as Physically Grounded Hand Trackers for Robot Learning

arXiv:2610.09455v1 Announce Type: new Abstract: Recently, approaches that leverage human video datasets for robot policy training have become increasingly prevalent. However, most existing hand tracke

RoBART: Bayesian Additive Regression Trees with Tree-Specific Rotations

arXiv:2610.10214v1 Announce Type: cross Abstract: Bayesian additive regression trees (BART) can require many splits to approximate boundaries misaligned with the predictor axes. RoBART assigns each tr

RoboFAC: A Comprehensive Framework for Robotic Failure Analysis and Correction

arXiv:2505.12224v5 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have recently advanced robotic manipulation by translating natural-language instructions and visual observations

local-aiarxiv-cs-ro

Applications

RoboJEPA: Scaling Robotic Latent World Models

arXiv:2610.10515v1 Announce Type: cross Abstract: Latent world models have shown a remarkable ability to predict future states and to plan in the real world. In practice, however, we lack a principled

applicationsarxiv-cs-ro

RoboPace: Contact-Aware Time-Optimal Retiming for Action-Chunk Policies

arXiv:2610.09696v1 Announce Type: new Abstract: Robot manipulation data collection has been shifting from teleoperation toward robot-free demonstrations, through interfaces such as the Universal Manip

RoboPilot: Generalizable Dynamic Robotic Manipulation with Dual-thinking Modes

model-releasesarxiv-cs-ro

arXiv:2510.00154v2 Announce Type: replace Abstract: Despite rapid progress in robotics, complex or long-horizon tasks remain a fundamental challenge. Most current approaches follow an open-loop paradi

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-

RoboQuest: Generalist Physical Agents that Search, Inspect and Test

arXiv:2610.10388v1 Announce Type: cross Abstract: Recent advances in multimodal foundation models have made them capable generalist physical agents for a range of manipulation tasks. However, successf

RoboRender: Robot-Oriented Video Generation for Visual Sim-to-Real Transfer

arXiv:2610.09254v1 Announce Type: new Abstract: Simulation enables large-scale, low-cost robot data generation, but policies trained in simulation often fail to transfer to the real world due to the s

RobotAPO: Adversarial Physics Preference Optimization for Robotic Manipulation Video Generation

arXiv:2610.09454v1 Announce Type: new Abstract: Robotic manipulation videos are increasingly used as visual plans for embodied agents, but optimizing purely for visual plausibility often fails to capt

local-aiarxiv-cs-ro

Robotic Boomerang Throwing via Model-Based Release Design

model-releasesarxiv-cs-ro

arXiv:2610.10472v1 Announce Type: new Abstract: Throwing objects that generate aerodynamic lift can greatly extend robot throwing beyond ballistic flight. A returning boomerang is a challenging exampl

Tutorials

Robotic Ultra-Long-Horizon Manipulation Skills via Human-guided Lifelong Code Generation

arXiv:2509.18597v3 Announce Type: replace Abstract: Large language models (LLMs) can translate natural-language instructions for robotic manipulation into executable code, but ambiguity, noisy generat

tutorialsarxiv-cs-ro

RobotWorld: Benchmarking Multimodal Agents for Robot Use Across Diverse Tasks and Embodiments

arXiv:2610.10409v1 Announce Type: cross Abstract: General-purpose agents increasingly write code, use tools, and complete complex digital tasks, raising the question of how far these capabilities carr

Robust Decentralized Fairness Auditing

arXiv:2610.10199v1 Announce Type: new Abstract: Emerging legislation requires large language models (LLMs) to be audited for compliance with regulatory standards, particularly fairness. Such black-box

local-aiarxiv-cs-lg