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Rays as Pixels: Learning A Joint Distribution of Videos and Camera Trajectories

arXiv:2604.09429v1 Announce Type: cross Abstract: Recovering camera parameters from images and rendering scenes from novel viewpoints have long been treated as separate tasks in computer vision and gr

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Re-Mask and Redirect: Exploiting Denoising Irreversibility in Diffusion Language Models

DGX agent

arXiv:2604.08557v1 Announce Type: cross Abstract: Diffusion-based language models (dLLMs) generate text by iteratively denoising masked token sequences. We show that their safety alignment rests on a

safetyarxiv-cs-ai

13 Apr 2026

REACT3D: Recovering Articulations for Interactive Physical 3D Scenes

arXiv:2510.11340v4 Announce Type: replace Abstract: Interactive 3D scenes are increasingly vital for embodied intelligence, yet existing datasets remain limited due to the labor-intensive process of a

researcharxiv-cs-cv

Realizing Immersive Volumetric Video: A Multimodal Framework for 6-DoF VR Engagement

arXiv:2604.09473v1 Announce Type: new Abstract: Fully immersive experiences that tightly integrate 6-DoF visual and auditory interaction are essential for virtual and augmented reality. While such exp

applicationsarxiv-cs-cv

Reasoning in a Combinatorial and Constrained World: Benchmarking LLMs on Natural-Language Combinatorial Optimization

arXiv:2602.02188v2 Announce Type: replace Abstract: While large language models (LLMs) have shown strong performance in math and logic reasoning, their ability to handle combinatorial optimization (CO

Reasoning Models Will Sometimes Lie About Their Reasoning

arXiv:2601.07663v3 Announce Type: replace Abstract: Hint-based faithfulness evaluations have established that Large Reasoning Models (LRMs) may not say what they think: they do not always volunteer in

Agents

Reasoning Provenance for Autonomous AI Agents: Structured Behavioral Analytics Beyond State Checkpoints and Execution Traces

arXiv:2603.21692v2 Announce Type: replace Abstract: As AI agents transition from human-supervised copilots to autonomous platform infrastructure, the ability to analyze their reasoning behavior across

agentsarxiv-cs-ai

RecaLLM: Addressing the Lost-in-Thought Phenomenon with Explicit In-Context Retrieval

arXiv:2604.09494v1 Announce Type: cross Abstract: We propose RecaLLM, a set of reasoning language models post-trained to make effective use of long-context information. In-context retrieval, which ide

Reducing Class Bias In Data-Balanced Datasets Through Hardness-Based Resampling

arXiv:2504.07031v2 Announce Type: replace Abstract: Class-bias, that is class-wise performance disparities, is typically attributed to data imbalance and addressed through frequency-based resampling.

safetyarxiv-cs-lg

Reflection of Episodes: Learning to Play Game from Expert and Self Experiences

arXiv:2502.13388v4 Announce Type: replace Abstract: StarCraft II is a complex and dynamic real-time strategy (RTS) game environment, which is very suitable for artificial intelligence and reinforcemen

Regime-Conditional Retrieval: Theory and a Transferable Router for Two-Hop QA

arXiv:2604.09019v1 Announce Type: cross Abstract: Two-hop QA retrieval splits queries into two regimes determined by whether the hop-2 entity is explicitly named in the question (Q-dominant) or only i

Region-Constrained Group Relative Policy Optimization for Flow-Based Image Editing

arXiv:2604.09386v1 Announce Type: new Abstract: Instruction-guided image editing requires balancing target modification with non-target preservation. Recently, flow-based models have emerged as a stro

safetyarxiv-cs-cv

Reinforcement-aware Knowledge Distillation for LLM Reasoning

arXiv:2602.22495v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) post-training has recently driven major gains in long chain-of-thought reasoning large language models (LLMs), but

Relational Visual Similarity

arXiv:2512.07833v2 Announce Type: replace-cross Abstract: Humans do not just see attribute similarity -- we also see relational similarity. An apple is like a peach because both are reddish fruit, but

applicationsarxiv-cs-ai

ReplicatorBench: Benchmarking LLM Agents for Replicability in Social and Behavioral Sciences

arXiv:2602.11354v2 Announce Type: replace Abstract: The literature has witnessed an emerging interest in AI agents for automated assessment of scientific papers. Existing benchmarks focus primarily on

RESample: A Robust Data Augmentation Framework via Exploratory Sampling for Robotic Manipulation

arXiv:2510.17640v3 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have demonstrated remarkable performance on complex tasks through imitation learning in recent robotic man

Reservoir observer enhanced with residual calibration and attention mechanism

arXiv:2604.08592v1 Announce Type: new Abstract: Reservoir observers provide a data-driven approach to the inference of unmeasured variables from observed ones for nonlinear dynamical systems. While pr

researcharxiv-cs-lg

Rethinking Prospect Theory for LLMs: Revealing the Instability of Decision-Making under Epistemic Uncertainty

arXiv:2508.08992v3 Announce Type: replace Abstract: Prospect Theory (PT) models human decision-making behaviour under uncertainty, among which linguistic uncertainty is commonly adopted in real-world

Tutorials

RetinexDualV2: Physically-Grounded Dual Retinex for Generalized UHD Image Restoration

arXiv:2603.27979v2 Announce Type: replace Abstract: We propose RetinexDualV2, a unified, physically grounded dual-branch framework for diverse Ultra-High-Definition (UHD) image restoration. Unlike gen

tutorialsarxiv-cs-cv

Retrieval Augmented Classification for Confidential Documents

arXiv:2604.08628v1 Announce Type: cross Abstract: Unauthorized disclosure of confidential documents demands robust, low-leakage classification. In real work environments, there is a lot of inflow and

Revisiting Anisotropy in Language Transformers: The Geometry of Learning Dynamics

arXiv:2604.08764v1 Announce Type: new Abstract: Since their introduction, Transformer architectures have dominated Natural Language Processing (NLP). However, recent research has highlighted an inhere

researcharxiv-cs-cl

Revisiting Image Manipulation Localization under Realistic Manipulation Scenarios

model-releasesarxiv-cs-cv

arXiv:2509.20006v3 Announce Type: replace Abstract: With the large models easing the labor-intensive manipulation process, image manipulations in today's real scenarios often entail a complex manipula

Revisiting the Capacity Gap in Chain-of-Thought Distillation from a Practical Perspective

arXiv:2604.08880v1 Announce Type: cross Abstract: Chain-of-thought (CoT) distillation transfers reasoning behaviors from a strong teacher to a smaller student, but prior work reports a capacity gap: d

Local Ai

Revitalizing Black-Box Interpretability: Actionable Interpretability for LLMs via Proxy Models

arXiv:2505.12509v3 Announce Type: replace-cross Abstract: Post-hoc explanations provide transparency and are essential for guiding model optimization, such as prompt engineering and data sanitation. H

local-aiarxiv-cs-ai

Agents

RIRF: Reasoning Image Restoration Framework

arXiv:2604.09511v1 Announce Type: new Abstract: Universal image restoration (UIR) aims to recover clean images from diverse and unknown degradations using a unified model. Existing UIR methods primari

agentsarxiv-cs-cv

Local Ai

Robust 4D Visual Geometry Transformer with Uncertainty-Aware Priors

arXiv:2604.09366v1 Announce Type: new Abstract: Reconstructing dynamic 4D scenes is an important yet challenging task. While 3D foundation models like VGGT excel in static settings, they often struggl

local-aiarxiv-cs-cv

Robust Adaptive Backstepping Impedance Control of Robots in Unknown Environments

arXiv:2604.09323v1 Announce Type: new Abstract: This paper presents a Robust Adaptive Backstepping Impedance Control (RABIC) strategy for robots operating in contact-rich and uncertain environments. T

researcharxiv-cs-ro

Agents

Robust by Design: A Continuous Monitoring and Data Integration Framework for Medical AI

arXiv:2604.09009v1 Announce Type: new Abstract: Adaptive medical AI models often face performance drops in dynamic clinical environments due to data drift. We propose an autonomous continuous monitori

agentsarxiv-cs-cv

Robust Reasoning Benchmark

arXiv:2604.08571v1 Announce Type: cross Abstract: While Large Language Models (LLMs) achieve high performance on standard mathematical benchmarks, their underlying reasoning processes remain highly ov

RS-OVC: Open-Vocabulary Counting for Remote-Sensing Data

arXiv:2604.08704v1 Announce Type: new Abstract: Object-Counting for remote-sensing (RS) imagery is attracting increasing research interest due to its crucial role in a wide and diverse set of applicat

applicationsarxiv-cs-cv

SafeAdapt: Provably Safe Policy Updates in Deep Reinforcement Learning

arXiv:2604.09452v1 Announce Type: cross Abstract: Safety guarantees are a prerequisite to the deployment of reinforcement learning (RL) agents in safety-critical tasks. Often, deployment environments

SafeMind: A Risk-Aware Differentiable Control Framework for Adaptive and Safe Quadruped Locomotion

arXiv:2604.09474v1 Announce Type: cross Abstract: Learning-based quadruped controllers achieve impressive agility but typically lack formal safety guarantees under model uncertainty, perception noise,

SAGE: A Service Agent Graph-guided Evaluation Benchmark

arXiv:2604.09285v1 Announce Type: new Abstract: The development of Large Language Models (LLMs) has catalyzed automation in customer service, yet benchmarking their performance remains challenging. Ex

Sample Complexity of Composite Quantum Hypothesis Testing

arXiv:2601.08588v4 Announce Type: replace-cross Abstract: This paper investigates symmetric composite binary quantum hypothesis testing (QHT), where the goal is to determine which of two uncertainty s

researcharxiv-cs-lg

Tutorials

Sample-Efficient Neurosymbolic Deep Reinforcement Learning

arXiv:2601.02850v2 Announce Type: replace Abstract: Reinforcement Learning (RL) is a well-established framework for sequential decision-making in complex environments. However, state-of-the-art Deep R

tutorialsarxiv-cs-ai

SatQNet: Satellite-assisted Quantum Network Entanglement Routing Using Directed Line Graph Neural Networks

arXiv:2604.09306v1 Announce Type: cross Abstract: Quantum networks are expected to become a key enabler for interconnecting quantum devices. In contrast to classical communication networks, however, i

applicationsarxiv-cs-ai

Scalable High-Recall Constraint-Satisfaction-Based Information Retrieval for Clinical Trials Matching

arXiv:2604.08849v1 Announce Type: cross Abstract: Clinical trials are central to evidence-based medicine, yet many struggle to meet enrollment targets, despite the availability of over half a million

Scaling flow-based approaches for topology sampling in SU(3) gauge theory

arXiv:2510.25704v2 Announce Type: replace-cross Abstract: We develop a methodology based on out-of-equilibrium simulations to mitigate topological freezing when approaching the continuum limit of latt

researcharxiv-cs-lg

Scene-Agnostic Object-Centric Representation Learning for 3D Gaussian Splatting

arXiv:2604.09045v1 Announce Type: new Abstract: Recent works on 3D scene understanding leverage 2D masks from visual foundation models (VFMs) to supervise radiance fields, enabling instance-level 3D s

safetyarxiv-cs-cv

ScheMatiQ: From Research Question to Structured Data through Interactive Schema Discovery

arXiv:2604.09237v1 Announce Type: new Abstract: Many disciplines pose natural-language research questions over large document collections whose answers typically require structured evidence, tradition

applicationsarxiv-cs-cl

Scheming in the wild: detecting real-world AI scheming incidents with open-source intelligence

arXiv:2604.09104v1 Announce Type: cross Abstract: Scheming, the covert pursuit of misaligned goals by AI systems, represents a potentially catastrophic risk, yet scheming research suffers from signifi

SCoRe: Clean Image Generation from Diffusion Models Trained on Noisy Images

arXiv:2604.09436v1 Announce Type: new Abstract: Diffusion models trained on noisy datasets often reproduce high-frequency training artifacts, significantly degrading generation quality. To address thi

safetyarxiv-cs-cv

Score-Driven Rating System for Sports

arXiv:2604.09143v1 Announce Type: new Abstract: This paper introduces a score-driven rating system, a generalization of the classical Elo rating system that employs the score, i.e. the gradient of the

safetyarxiv-cs-lg

Scrapyard AI

arXiv:2604.08803v1 Announce Type: cross Abstract: This paper considers AI model churn as an opportunity for frugal investigation of large AI models. It describes how the incessant push for ever more p

applicationsarxiv-cs-ai

Screen, Cache, and Match: A Training-Free Causality-Consistent Reference Frame Framework for Human Animation

arXiv:2601.22160v2 Announce Type: replace-cross Abstract: Human animation aims to generate temporally coherent and visually consistent videos over long sequences, yet modeling long-range dependencies

SEA-Eval: A Benchmark for Evaluating Self-Evolving Agents Beyond Episodic Assessment

arXiv:2604.08988v1 Announce Type: new Abstract: Current LLM-based agents demonstrate strong performance in episodic task execution but remain constrained by static toolsets and episodic amnesia, faili

See, Hear, and Understand: Benchmarking Audiovisual Human Speech Understanding in Multimodal Large Language Models

arXiv:2512.02231v2 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) are expected to jointly interpret vision, audio, and language, yet existing video benchmarks rarely a

Seeing is Believing: Robust Vision-Guided Cross-Modal Prompt Learning under Label Noise

arXiv:2604.09532v1 Announce Type: cross Abstract: Prompt learning is a parameter-efficient approach for vision-language models, yet its robustness under label noise is less investigated. Visual conten