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Representation Geometry and Inductive Biases in Quantum Classifiers across Classical Visual Benchmarks

arXiv:2610.17722v1 Announce Type: cross Abstract: Quantum Machine Learning (QML) has a theoretical advantage over classical algorithms for specific synthetic data that is computationally hard. However

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Human DGX agent

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Representational Difference Distillation

DGX agent

arXiv:2610.15997v1 Announce Type: cross Abstract: Knowledge distillation transfers representational knowledge from a large teacher network to a compact student. Existing relational and contrastive dis

tutorialsarxiv-cs-cv

14 Oct 2026

RePrior: Measurement-Reconciled Prior Correction for Sparse-View CBCT Reconstruction

arXiv:2610.14102v1 Announce Type: cross Abstract: Sparse-view cone-beam computed tomography (CBCT) is severely under-constrained by limited X-ray projections. Learned reconstruction can provide comple

Local Ai

Requests of a Feather Must Flock Together: Batch Size vs. Prefix Homogeneity in LLM Inference

arXiv:2605.06046v2 Announce Type: replace Abstract: Auto-regressive token generation in large language models is memory-bound because it requires 'attending to' key and value tensors (KV cache) of all

local-aiarxiv-cs-lg

RES-MR: Risk-Aware Reasoning for Explainable and Safe Medication Recommendation

arXiv:2610.14474v1 Announce Type: new Abstract: Medication recommendations seek to deliver personalized drug combinations based on patients' clinical information, where ensuring transparent decision-m

Resample the Answer: Where to Spend Test-Time Compute in Recursive Reasoning

arXiv:2610.16427v1 Announce Type: new Abstract: Recursive reasoning models such as the Tiny Recursive Model (TRM) iteratively refine two latent states: an answer state y, decoded into the output, and

Rescuing Points Trapped Inside Incorrect Decision Regions: A target for Evaluating and Improving Forward-Forward Learning

arXiv:2610.16347v1 Announce Type: new Abstract: Forward-Forward learning replaces end-to-end backpropagation with local, layer-wise training objectives. Its variants are evaluated primarily by classif

Agents

ResearchFlow-Eval: Tracing the Execution Gap in End-to-End Multi-Claim Autoresearch

arXiv:2610.18088v1 Announce Type: cross Abstract: Autoresearch systems increasingly undertake entire research projects. In practice, scientific research requires systems to pursue multiple interdepend

agentsarxiv-cs-lg

Residual Compliant Policy: Learning Compliant Policies from Few Demonstrations

arXiv:2610.14035v1 Announce Type: new Abstract: Contact-rich manipulation requires a robot to be precise in free space to establish the intended contacts, and compliant once in contact to avoid excess

safetyarxiv-cs-ro

Hardware

Resource-Efficient 3D Shape and Orientation Estimation of Road Users using Roadside RGB Camera and 3D Radar

arXiv:2610.18417v1 Announce Type: new Abstract: End-to-end deep learning pipelines for camera-radar 3D object detection are well established in driver assistance systems and autonomous vehicles; howev

hardwarearxiv-cs-cv

Tutorials

RespFocus: Learning Temporal Evidence for Weakly Supervised Respiratory Sound Classification

arXiv:2610.15702v1 Announce Type: new Abstract: Respiratory auscultation provides a low-cost means of assessing pulmonary function, yet transient crackles and sustained wheezes can be difficult to rec

tutorialsarxiv-cs-lg

RESTA: Time-Scaling Augmentation for Data-Efficient Robot Imitation Learning

arXiv:2610.18163v1 Announce Type: new Abstract: Robot manipulation policies trained through imitation learning commonly rely on costly demonstrations recorded in one task direction and at one temporal

safetyarxiv-cs-ro

ReTerm: Recovery Training for Self-Improving Terminal Agents

arXiv:2610.18484v1 Announce Type: cross Abstract: Terminal agents have shown strong abilities in complex coding tasks. However, they often struggle to recover from errors during long-running execution

Rethinking Activation Functions: Reducing Bias Can Improve Learning

arXiv:2610.14500v1 Announce Type: new Abstract: Many widely used activation functions, including ReLU, GELU, Swish, and Sigmoid, produce predominantly positive outputs, resulting in a nonzero post-act

Rethinking Human Intent-to-CAD: Parametric CAD Model Generation via Cooperative Multi-Task Alignment and Spatial-Aware Reinforcement Learning

arXiv:2610.15681v1 Announce Type: new Abstract: Parametric Computer-Aided-Design (CAD) modeling from human intent remains challenging, particularly during the conceptual design stage, where design goa

Rethinking Langevin Thompson Sampling from A Stochastic Approximation Perspective

arXiv:2510.05023v2 Announce Type: replace Abstract: Langevin-based Thompson Sampling (TS) methods for multi-armed bandits use likelihood gradients to approximate posterior samples when exact sampling

Rethinking LLM-Guided Visual Question Answering: Does Deeper Knowledge Integration Really Help?

arXiv:2610.17079v1 Announce Type: new Abstract: Knowledge-based Visual Question Answering (VQA) requires reasoning that extends beyond visible image content, demanding external commonsense and factual

Rethinking Opinion Measurement Interfaces for Human-in-the-Loop Optimization

arXiv:2610.14757v1 Announce Type: cross Abstract: Human-in-the-loop optimization refers to systems that present choices to a human decision-maker and query their judgment to optimize system parameters

Rethinking Projector Training in Multimodal LLMs

arXiv:2610.18598v1 Announce Type: new Abstract: Multimodal LLMs are typically trained by first aligning a vision encoder with a language model via projector training on large image-caption datasets, f

Rethinking Supervision in Document Unwarping: A Self-consistent Flow-free Approach

arXiv:2610.15445v1 Announce Type: new Abstract: In recent years, the proliferation of smartphones has led to an upsurge in the digitization of document files via these portable devices. However, image

ReTrace: Cross-Stage Failure Attribution for Self-Improving Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2610.15814v1 Announce Type: new Abstract: General-purpose multimodal foundation models are increasingly capable of directly controlling robots, yet improving their manipulation capabilities thro

Retraining-Free Depth Pruning of Vision Transformers: A Cross Domain Study of Layer Redundancy

arXiv:2610.15005v1 Announce Type: new Abstract: Transformer architectures have achieved strong results in natural language processing and computer vision, but their deployment is limited by high compu

researcharxiv-cs-cv

Retrievable Gradients: Continual Post-Training Without Cumulative Weight Drift

arXiv:2606.15734v2 Announce Type: replace-cross Abstract: Continual post-training enables models to absorb emerging knowledge after deployment, but repeatedly updating shared parameters can accumulate

RetroPlanner: Multi-Route Expansion and Multi-Objective Reasoning for LLM-Based Retrosynthesis Planning

arXiv:2610.16391v1 Announce Type: cross Abstract: Multi-step retrosynthesis planning is often considered solved once a route to purchasable starting materials is found, but such a route should also be

Revisited Support Vector Machines: A Unified Joint Optimization Framework with Nystrom Approximation for Scalable Adaptive Learning

arXiv:2610.15498v1 Announce Type: new Abstract: The theoretical elegance of Support Vector Machines (SVMs), grounded in statistical learning theory, establishes them as a reference for robust classifi

Revisiting Error Feedback for Model Quantization

arXiv:2610.18139v1 Announce Type: new Abstract: We study causal error-feedback coefficients as design variables for model quantization. Modeling instantaneous quantization errors as independent, zero-

Revisiting Natural Language Prompts from Large Language Models for Open-Vocabulary Video Recognition

arXiv:2610.16666v1 Announce Type: new Abstract: Vision-language models (VLMs) like CLIP have shown great success in image tasks, however, applying CLIP to open-vocabulary video recognition poses chall

Revisiting the 16x Pretraining Compute Gap between Diffusion and Autoregressive Language Models

arXiv:2610.17590v1 Announce Type: new Abstract: Diffusion language models (DLMs) have attracted wide attention for their fast, parallel decoding, but they are believed to be far less efficient to trai

Reviving Stale Updates: Data-Free Knowledge Distillation for Asynchronous Federated Learning

arXiv:2511.00655v3 Announce Type: replace Abstract: Federated learning (FL) enables collaborative model training across distributed clients without sharing raw data, yet its scalability is limited by

Reward-Aligned Distillation

arXiv:2610.14572v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards improves the reasoning capabilities of large language models, but remains computationally expensive and s

RF Fingerprinting of DSP Implementations using Machine Learning: An Over-the-Air Case Study

arXiv:2610.15494v1 Announce Type: cross Abstract: Radio frequency fingerprinting aims to identify transmitters by exploiting small differences in the emitted signal waveform. Common approaches exploit

RFWeave: Learning Wireless Propagation Across Scenes and Transceiver Configurations

arXiv:2610.16656v1 Announce Type: cross Abstract: Wireless propagation modeling is foundational to the evaluation and design of modern communication systems. To achieve accurate wireless propagation p

RIECNN: Real-Time Image Enhanced CNN for Traffic Sign Recognition

arXiv:2610.15127v1 Announce Type: new Abstract: Traffic sign recognition plays a crucial role in the development of autonomous cars to reduce the accident rate and promote road safety. It has been a n

Tutorials

Riemannian Graph Tokenizer for Structural Knowledge Transfer

arXiv:2610.15427v1 Announce Type: new Abstract: Foundation models are at the forefront of artificial intelligence. A tokenizer, converting the raw input into discrete representations that the model ca

tutorialsarxiv-cs-lg

RIFT: Token Influence Follows the Path of Least Resistance

arXiv:2610.16349v1 Announce Type: cross Abstract: Which context tokens drive a language model's answer? Graph-based tools such as attention rollout and attention flow answer this from a single forward

Risk-Averse Inference-Time Diffusion Model Alignment with Finite-Sample Guarantees

arXiv:2610.17579v1 Announce Type: cross Abstract: Inference-time alignment steers diffusion models toward downstream objectives without costly fine-tuning, but existing methods typically optimize expe

Tutorials

RM-WAM: Reliable Memory-Augmented World Action Models for Long-Horizon Robot Manipulation

arXiv:2610.15305v1 Announce Type: new Abstract: World Action Models (WAMs) improve robotic manipulation by jointly predicting future visual states and actions, yet most existing methods make decisions

tutorialsarxiv-cs-ro

RoboBugBench: Benchmarking Automated Repair of Real Robot Software Under an Audited Behavioral Oracle

model-releasesarxiv-cs-ro

arXiv:2610.16369v1 Announce Type: new Abstract: Language agents increasingly modify robot software, but whether they can repair it is unmeasured, because the domain supplies no oracle to inherit: a ro

RoboFake: Are Deepfake Detectors Ready for Humanoid Face Robots?

arXiv:2610.14269v1 Announce Type: new Abstract: Humanoid face robots can now move their lips in sync with speech and show detailed facial expressions. Give such a robot the face of a real person and d

researcharxiv-cs-cv

RoboFQE: Rollout-Free Evaluation of Visual Robot Policies from Offline Trajectories

arXiv:2610.18699v1 Announce Type: new Abstract: Evaluating robot policies before deployment typically requires producing new trajectories through real-world execution, simulators, or learned world mod

safetyarxiv-cs-ro

RoboHarness: A Simple Harness Outperforms VLA and World Actions Models

model-releasesarxiv-cs-ro

arXiv:2610.14018v1 Announce Type: new Abstract: The rise of large language models (LLMs) has opened a path toward generalist embodied AI, raising the question of how LLMs can act in the physical world

Agents

RoboSimStudio: An Interactive Toolkit for Rapid Real2Sim of Robot Manipulation Tasks

arXiv:2610.18835v1 Announce Type: cross Abstract: It is difficult to accurately model the physics of the interaction between a robot and the objects it manipulates, including contact mechanics, couple

agentsarxiv-cs-lg

Robust Detection of Directional Adversarial Attacks in Deep Neural Networks for Radiological Imaging

arXiv:2610.15628v1 Announce Type: new Abstract: Deep learning is now central to radiology, helping detect changes on X-rays, CTs, and MRIs. However, these systems are highly vulnerable to adversarial

applicationsarxiv-cs-cv

Robust Logical Anomaly Detection under Capture Shifts via Synthetic Anomalies

arXiv:2610.18295v1 Announce Type: new Abstract: Detectors of logical anomalies, such as missing, extra or wrongly combined parts, usually score a test image by its distance from normal (good) images.

Robust Marathi Sentiment Analysis using Domain-Adaptive Pre-training and Data Augmentation Approaches

arXiv:2610.15761v1 Announce Type: cross Abstract: For languages with limited resources, Sentiment Analysis remains a challenging problem due to limited annotated data and strong domain variability acr

Robustly Reliable Learning for Regression

arXiv:2610.17381v1 Announce Type: new Abstract: We introduce the problem of robustly reliable learning for the regression setting in adversarial environments. Given a test point x_{test}, a training d

RootSLAM: Square Root Bundle Adjustment for Visual-Inertial SLAM

arXiv:2610.15157v1 Announce Type: cross Abstract: Efficient perception is a prerequisite for the small, low-power devices targeted by robotics, mixed reality, autonomous driving, and drone application

Rotate the Loop: Blockwise Conformality for Looped Transformers

arXiv:2610.14030v1 Announce Type: new Abstract: Looped transformers reuse one shared block across many recurrent steps, so depth becomes a quantity that can be spent at runtime rather than a stack of