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Quantifying Data Similarity Using Cross Learning

arXiv:2510.10866v3 Announce Type: replace-cross Abstract: Measuring dataset similarity is fundamental in machine learning, particularly for transfer learning and domain adaptation. In the context of s

safetyarxiv-cs-lg

Quantum AI for Cancer Diagnostic Biomarker Discovery

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arXiv:2604.18621v1 Announce Type: cross Abstract: Quantum machine learning offers a promising new paradigm for computational biology by leveraging quantum mechanical principles to enhance cancer class

researcharxiv-cs-lg

22 Apr 2026

Quantum inspired qubit qutrit neural networks for real time financial forecasting

arXiv:2604.18838v1 Announce Type: new Abstract: This research investigates the performance and efficacy of machine learning models in stock prediction, comparing Artificial Neural Networks (ANNs), Qua

Quantum Non-Linear Bandit Optimization

arXiv:2503.03023v2 Announce Type: replace Abstract: We study non-linear bandit optimization where the learner maximizes a black-box function with zeroth order function oracle, which has been successfu

applicationsarxiv-cs-lg

Quantum spatial best-arm identification via quantum walks

arXiv:2509.05890v3 Announce Type: replace-cross Abstract: Quantum reinforcement learning has emerged as a framework combining quantum computation with sequential decision-making, and applications to t

Local Ai

R^2-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction

arXiv:2604.18995v1 Announce Type: cross Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to autoregressive generation by enabling parallel token prediction. Ho

local-aiarxiv-cs-ai

RAFT-MSF++: Temporal Geometry-Motion Feature Fusion for Self-Supervised Monocular Scene Flow

model-releasesarxiv-cs-cv

arXiv:2604.19349v1 Announce Type: new Abstract: Monocular scene flow estimation aims to recover dense 3D motion from image sequences, yet most existing methods are limited to two-frame inputs, restric

Rank-Turbulence Delta and Interpretable Approaches to Stylometric Delta Metrics

model-releasesarxiv-cs-cl

arXiv:2604.19499v1 Announce Type: new Abstract: This article introduces two new measures for authorship attribution - Rank-Turbulence Delta and Jensen-Shannon Delta - which generalise Burrows's classi

RARE: Redundancy-Aware Retrieval Evaluation Framework for High-Similarity Corpora

arXiv:2604.19047v1 Announce Type: cross Abstract: Existing QA benchmarks typically assume distinct documents with minimal overlap, yet real-world retrieval-augmented generation (RAG) systems operate o

RDP LoRA: Geometry-Driven Identification for Parameter-Efficient Adaptation in Large Language Models

arXiv:2604.19321v1 Announce Type: cross Abstract: Fine-tuning Large Language Models (LLMs) remains structurally uncertain despite parameter-efficient methods such as Low-Rank Adaptation (LoRA), as the

Real-Time Streamable Generative Speech Restoration with Flow Matching

arXiv:2512.19442v3 Announce Type: replace-cross Abstract: Diffusion-based generative models have greatly impacted the speech processing field in recent years, exhibiting high speech naturalness and sp

researcharxiv-cs-lg

Realistic Handwritten Multi-Digit Writer (MDW) Number Recognition Challenges

model-releasesarxiv-cs-cv

arXiv:2512.00676v2 Announce Type: replace Abstract: Isolated digit classification has served as a motivating problem for decades of machine learning research. In real settings, numbers often occur as

Reasoning-Aware AIGC Detection via Alignment and Reinforcement

arXiv:2604.19172v1 Announce Type: new Abstract: The rapid advancement and widespread adoption of Large Language Models (LLMs) have elevated the need for reliable AI-generated content (AIGC) detection,

Local Ai

Reasoning Over Space: Enabling Geographic Reasoning for LLM-Based Generative Next POI Recommendation

arXiv:2601.04562v2 Announce Type: replace Abstract: Generative recommendation with large language models (LLMs) reframes prediction as sequence generation, yet existing LLM-based recommenders remain l

local-aiarxiv-cs-ai

Reasoning Structure Matters for Safety Alignment of Reasoning Models

arXiv:2604.18946v1 Announce Type: new Abstract: Large reasoning models (LRMs) achieve strong performance on complex reasoning tasks but often generate harmful responses to malicious user queries. This

Recurrent Video Masked Autoencoders

model-releasesarxiv-cs-cv

arXiv:2512.13684v2 Announce Type: replace Abstract: We present Recurrent Video Masked-Autoencoders (RVM): a novel approach to video representation learning that leverages recurrent computation to mode

Reduced-Order Surrogates for Forced Flexible Mesh Coastal-Ocean Models

arXiv:2602.05416v2 Announce Type: replace-cross Abstract: While proper orthogonal decomposition (POD)-based surrogates are widely explored for hydrodynamic applications, the use of Koopman autoencoder

applicationsarxiv-cs-ai

Reducing the Offline-Streaming Gap for Unified ASR Transducer with Consistency Regularization

arXiv:2604.19079v1 Announce Type: cross Abstract: Unification of automatic speech recognition (ASR) systems reduces development and maintenance costs, but training a single model to perform well in bo

ReefNet: A Large-Scale Dataset and Benchmark for Fine-Grained Coral Reef Recognition

arXiv:2510.16822v3 Announce Type: replace-cross Abstract: Coral reefs are rapidly declining under anthropogenic pressures (e.g., climate change), creating an urgent need for scalable and automated mon

ReflectMT: Internalizing Reflection for Efficient and High-Quality Machine Translation

model-releasesarxiv-cs-cl

arXiv:2604.19144v1 Announce Type: new Abstract: Recent years have witnessed growing interest in applying Large Reasoning Models (LRMs) to Machine Translation (MT). Existing approaches predominantly ad

Refute-or-Promote: An Adversarial Stage-Gated Multi-Agent Review Methodology for High-Precision LLM-Assisted Defect Discovery

arXiv:2604.19049v1 Announce Type: cross Abstract: LLM-assisted defect discovery has a precision crisis: plausible-but-wrong reports overwhelm maintainers and degrade credibility for real findings. We

Regression with Large Language Models for Materials and Molecular Property Prediction

model-releasesarxiv-cs-lg

arXiv:2409.06080v2 Announce Type: replace-cross Abstract: We demonstrate the ability of large language models (LLMs) to perform material and molecular property regression tasks, a significant deviatio

Regulating Artificial Intimacy: From Locks and Blocks to Relational Accountability

arXiv:2604.18893v1 Announce Type: cross Abstract: A series of high-profile tragedies involving companion chatbots has triggered an unusually rapid regulatory response. Several jurisdictions, including

ReImagine: Rethinking Controllable High-Quality Human Video Generation via Image-First Synthesis

arXiv:2604.19720v1 Announce Type: new Abstract: Human video generation remains challenging due to the difficulty of jointly modeling human appearance, motion, and camera viewpoint under limited multi-

Reinforcement Learning Enabled Adaptive Multi-Task Control for Bipedal Soccer Robots

arXiv:2604.19104v1 Announce Type: cross Abstract: Developing bipedal football robots in dynamiccombat environments presents challenges related to motionstability and deep coupling of multiple tasks, a

Reinforcement Learning Improves LLM Accuracy and Reasoning in Disease Classification from Radiology Reports

arXiv:2604.19060v1 Announce Type: new Abstract: Accurate disease classification from radiology reports is essential for many applications. While supervised fine-tuning (SFT) of lightweight LLMs improv

Tutorials

Relational AI in Education: Reciprocity, Participatory Design, and Indigenous Worldviews

arXiv:2604.19099v1 Announce Type: cross Abstract: Education is not merely the transmission of information or the optimisation of individual performance; it is a fundamentally social, constructive, and

tutorialsarxiv-cs-ai

Remask, Don't Replace: Token-to-Mask Refinement in Masked Diffusion Language Models

arXiv:2604.18738v1 Announce Type: new Abstract: Masked diffusion language models such as LLaDA2.1 rely on Token-to-Token (T2T) editing to correct their own generation errors: whenever a different toke

researcharxiv-cs-cl

Remote Rowhammer Attack using Adversarial Observations on Federated Learning Clients

arXiv:2505.06335v2 Announce Type: replace-cross Abstract: Federated Learning (FL) has the potential for simultaneous global learning amongst a large number of parallel agents, enabling emerging AI suc

RepIt: Steering Language Models with Concept-Specific Refusal Vectors

arXiv:2509.13281v5 Announce Type: replace Abstract: Current safety evaluations of language models rely on benchmark-based assessments that may miss localized vulnerabilities. We present RepIt, a simpl

RESFL: An Uncertainty-Aware Framework for Responsible Federated Learning by Balancing Privacy, Fairness and Utility

arXiv:2503.16251v2 Announce Type: replace-cross Abstract: Federated Learning (FL) has gained prominence in machine learning applications across critical domains by enabling collaborative model trainin

safetyarxiv-cs-cv

Resolving the Robustness-Precision Trade-off in Financial RAG through Hybrid Document-Routed Retrieval

arXiv:2603.26815v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) systems for financial document question answering typically follow a chunk-based paradigm: documents are

Resource-aware Mixed-precision Quantization for Enhancing Deployability of Transformers for Time-series Forecasting on Embedded FPGAs

arXiv:2410.03294v4 Announce Type: replace Abstract: This study addresses the deployment challenges of integer-only quantized Transformers on resource-constrained embedded FPGAs (Xilinx Spartan-7 XC7S1

researcharxiv-cs-lg

Rethinking Dataset Distillation: Hard Truths about Soft Labels

arXiv:2604.18811v1 Announce Type: cross Abstract: Despite the perceived success of large-scale dataset distillation (DD) methods, recent evidence finds that simple random image baselines perform on-pa

Rethinking Information Synthesis in Multimodal Question Answering A Multi-Agent Perspective

arXiv:2505.20816v2 Announce Type: replace Abstract: Recent advances in multimodal question answering have primarily focused on combining heterogeneous modalities or fine-tuning multimodal large langua

agentsarxiv-cs-cl

Rethinking Scale: Deployment Trade-offs of Small Language Models under Agent Paradigms

arXiv:2604.19299v1 Announce Type: cross Abstract: Despite the impressive capabilities of large language models, their substantial computational costs, latency, and privacy risks hinder their widesprea

Revac: A Social Deduction Reasoning Agent

arXiv:2604.19523v1 Announce Type: new Abstract: Social deduction games such as Mafia present a unique AI challenge: players must reason under uncertainty, interpret incomplete and intentionally mislea

REVEAL: Multimodal Vision-Language Alignment of Retinal Morphometry and Clinical Risks for Incident AD and Dementia Prediction

arXiv:2604.18757v1 Announce Type: cross Abstract: The retina provides a unique, noninvasive window into Alzheimer's disease (AD) and dementia, capturing early structural changes through morphometric f

Revisiting Catastrophic Forgetting in Continual Knowledge Graph Embedding

arXiv:2604.19401v1 Announce Type: cross Abstract: Knowledge Graph Embeddings (KGEs) support a wide range of downstream tasks over Knowledge Graphs (KGs). In practice, KGs evolve as new entities and fa

Revisiting RaBitQ and TurboQuant: A Symmetric Comparison of Methods, Theory, and Experiments

arXiv:2604.19528v1 Announce Type: cross Abstract: This technical note revisits the relationship between RaBitQ and TurboQuant under a unified comparison framework. We compare the two methods in terms

RF-HiT: Rectified Flow Hierarchical Transformer for General Medical Image Segmentation

arXiv:2604.19570v1 Announce Type: new Abstract: Accurate medical image segmentation requires both long-range contextual reasoning and precise boundary delineation, a task where existing transformer- a

RIFT: A RubrIc Failure Mode Taxonomy and Automated Diagnostics

arXiv:2604.01375v2 Announce Type: replace Abstract: Rubric-based evaluation is widely used in LLM benchmarks and training pipelines for open-ended, less verifiable tasks. While prior work has demonstr

RL-ABC: Reinforcement Learning for Accelerator Beamline Control

arXiv:2604.19146v1 Announce Type: new Abstract: Particle accelerator beamline optimization is a high-dimensional control problem traditionally requiring significant expert intervention. We present RLA

safetyarxiv-cs-lg

RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation

arXiv:2604.19092v1 Announce Type: cross Abstract: Recent advances in large-scale video world models have enabled increasingly realistic future prediction, raising the prospect of leveraging imagined v

Robust Continual Unlearning against Knowledge Erosion and Forgetting Reversal

arXiv:2604.19108v1 Announce Type: cross Abstract: As a means to balance the growth of the AI industry with the need for privacy protection, machine unlearning plays a crucial role in realizing the ``r

RoLegalGEC: Legal Domain Grammatical Error Detection and Correction Dataset for Romanian

arXiv:2604.19593v1 Announce Type: cross Abstract: The importance of clear and correct text in legal documents cannot be understated, and, consequently, a grammatical error correction tool meant to ass

applicationsarxiv-cs-ai

Local Ai

RoomRecon: High-Quality Textured Room Layout Reconstruction on Mobile Devices

arXiv:2604.19025v1 Announce Type: new Abstract: Widespread RGB-Depth (RGB-D) sensors and advanced 3D reconstruction technologies facilitate the capture of indoor spaces, improving the fields of augmen

local-aiarxiv-cs-ro

S2MAM: Semi-supervised Meta Additive Model for Robust Estimation and Variable Selection

arXiv:2604.19072v1 Announce Type: cross Abstract: Semi-supervised learning with manifold regularization is a classical framework for jointly learning from both labeled and unlabeled data, where the ke

applicationsarxiv-cs-ai