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ReliableNet: A Chance-Constrained Approach to Trustworthy Classification in Deep Learning

model-releasesarxiv-cs-lg

arXiv:2608.09768v1 Announce Type: new Abstract: A prediction that is both confident and wrong is a critical reliability failure because it can bypass abstention and human review precisely when the mod

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REMAC: Self-Reflective and Self-Evolving Multi-Agent Collaboration for Long-Horizon Robot Manipulation

DGX agent

arXiv:2503.22122v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have demonstrated remarkable capabilities in robotic planning, particularly for long-horizon tasks that require

model-releasesarxiv-cs-ai

11 Aug 2026

ReMIND: Orchestrating Modular Large Language Models for Controllable Serendipity A REM-Inspired System Design for Emergent Creative Ideation

arXiv:2601.07121v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used not only for problem solving but also for creative ideation; however, generating ideas that

Removing Infrastructure Barriers in Human-Robot Collaboration Through Wireless Reconfigurable Cells

arXiv:2608.09658v1 Announce Type: cross Abstract: Human-Robot Collaboration (HRC) plays a vital role in dynamic, high mix, low volume industrial scenarios such as remanufacturing, which frequently fac

RenderMatte: Exact-Alpha Rendering and Group-Relative Alignment for Image Matting

model-releasesarxiv-cs-cv

arXiv:2608.08487v1 Announce Type: new Abstract: Image matting is an essential enabling technology for modern visual content production, where foreground extraction determines the realism and editabili

Renormalising Generative Models for Active Inference: Foundations, Derivations, and Verification

arXiv:2608.09512v1 Announce Type: new Abstract: Active inference offers a unified framework for perception, learning, and action, but scaling discrete active-inference models to rich spatial and tempo

Representation Matters in Longitudinal Affective Computing

arXiv:2608.07518v1 Announce Type: cross Abstract: Longitudinal, in-the-wild, wearable sensing yields day-level physiology, sleep, activity, and environmental streams, whereas affect and cognition are

local-aiarxiv-cs-ai

Reproducing and Stress-Testing Two Approaches to LLM Reasoning Reliability: Test-Time Probability Aggregation and Logic-Representation Editing

arXiv:2608.08514v1 Announce Type: new Abstract: We independently reproduce two recent methods for making large language model (LLM) reasoning more reliable, and stress-test them across domains and mod

Researchers find that feeding a frontier model's encrypted reasoning traces to a weaker model from the same provider can make it output the traces in plaintext (Will Knight/Wired)

Will Knight / Wired: Researchers find that feeding a frontier model's encrypted reasoning traces to a weaker model from the same provider can make it output the traces in plaintext — Researchers devis

model-releasestechmeme

ResemBrick: Brick Reconstruction from Photographs with Perceptual Fidelity and Buildability

arXiv:2608.09597v1 Announce Type: new Abstract: Producing a hand-buildable, colored brick model of a 3D object from a few casual photographs is a clean testbed for a broader challenge: generating 3D c

Resolution Meets Reduction: Efficient Visual Context for 3D Radiology Report Generation

arXiv:2608.08713v1 Announce Type: cross Abstract: Vision-language models offer a promising path toward automating radiology report generation, but applying them to full 3D CT volumes poses substantial

Applications

Rethink Before You Execute: Adaptive Execution for World Action Models

arXiv:2608.09492v1 Announce Type: new Abstract: World Action Models (WAMs) jointly predict future actions and the evolution of the environment. At each inference, a WAM generates a chunk of actions an

applicationsarxiv-cs-ro

Rethinking 3D Segmentation from Individual LiDAR Scans: Incidence-Aware Sampling on the SIP Benchmark

model-releasesarxiv-cs-cv

arXiv:2608.07757v1 Announce Type: new Abstract: 3D scene understanding is increasingly important in construction, yet most methods are developed on curated datasets that do not fully reflect real site

Rethinking Attention Locality in Spiking Transformers

model-releasesarxiv-cs-cv

arXiv:2608.08541v1 Announce Type: new Abstract: Spiking Transformers provide a promising paradigm for efficient visual processing with spike-driven computation, yet their Softmax-free Spiking Self-Att

Rethinking Factor Sharing in Federated LoRA: A Rank-Aware Adaptive Approach

arXiv:2608.09742v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) represents large language model (LLM) updates with two compact matrix factors, i.e., A and B, providing an efficient way to

local-aiarxiv-cs-ai

Rethinking Learning-Based Influence Maximization: Simple Neural Surrogates and Native Discrete Search

arXiv:2608.08406v1 Announce Type: new Abstract: Existing learning-based influence maximization frameworks rely heavily on complex neural architectures and continuous optimization over seed representat

researcharxiv-cs-lg

Rethinking Medical Landmark Localization with Prototype Learning-based Progressive Offset Correction

arXiv:2608.09182v1 Announce Type: cross Abstract: Accurate landmark localization in medical images is a fundamental step for quantitative clinical measurement and downstream analysis. Existing localiz

Rethinking Reasoning with MDLMs: Early Exits, Post-hoc Reasoning, and Beyond

arXiv:2510.19990v2 Announce Type: replace Abstract: The reasoning paradigm, where language models reason before answering, has enabled breakthroughs on tasks such as mathematical problem-solving. Whil

researcharxiv-cs-lg

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines?

arXiv:2608.09629v1 Announce Type: new Abstract: Self-evolving agents are usually built around prescribed optimization pipelines: the framework decides how to gather evidence, revise a persistent artif

Retrieval-Augmented Defense: Adaptive and Controllable Jailbreak Prevention for Large Language Models

arXiv:2508.16406v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) remain vulnerable to jailbreak attacks, which attempt to elicit harmful responses from LLMs. The evolving nature

safetyarxiv-cs-cl

Retrieval-Augmented Generation-Based Color Restoration for Low-Light Image Enhancement

arXiv:2608.08211v1 Announce Type: cross Abstract: Recent low-light image enhancement (LLIE) methods have driven brightness and structural fidelity close to that of normally-exposed images, yet their o

Agents

REVEAL: A Rubric-Guided Agent for Explicit Evidence Sufficiency Verificationin Long-Video Question Answering

arXiv:2608.08612v1 Announce Type: cross Abstract: Recently, retrieval-augmented and memory-augmented methods have emerged as two promising paradigms for long-video question answering. However, existin

agentsarxiv-cs-ai

Revision or Re-Solving? Decomposing Second-Pass Gains in Multi-LLM Pipelines

arXiv:2604.01029v2 Announce Type: replace-cross Abstract: Multi-LLM revision pipelines, in which a second model reviews and improves a draft produced by a first, are widely assumed to derive their gai

Revisiting the Current Frame: Physical-Trace-Guided Network Output Correction for Video Restoration

arXiv:2608.09342v1 Announce Type: new Abstract: Video restoration methods exploit temporal information to recover information missing from degraded observations. However, reference frames within the s

Right Answer, Wrong Heat: Explanation-Aware Evaluation and Thermal-Grounded Feedback for MLLMs on Infrared Images

arXiv:2608.09145v1 Announce Type: new Abstract: General-purpose multimodal large language models (MLLMs) are increasingly applied to infrared images, where they are commonly scored by answer accuracy

RippleKV: Cross-Layer KV Cache Allocation via Perturbation Propagation

arXiv:2608.08684v1 Announce Type: cross Abstract: Long-context LLM inference is bottlenecked by KV cache memory, yet distributing a limited cache budget across layers remains challenging. Existing met

RISE-RL: Rubric-Informed Selective Exploration for Open-Ended Reinforcement Learning

arXiv:2608.09123v1 Announce Type: new Abstract: Aligning Large Language Models (LLMs) for open-ended tasks is challenging because responses must satisfy multidimensional criteria without following a s

RL-Native Distillation: Exploiting Scored Trajectories for Few-Step Image Generation

arXiv:2608.09226v1 Announce Type: cross Abstract: Efficient text-to-image generation requires both reinforcement-learning (RL)-based reward alignment and few-step distillation, yet these procedures ar

safetyarxiv-cs-ai

RMR-Net: Degradation-Evidence-Guided Road-Image Restoration for Defect Detection

arXiv:2608.08957v1 Announce Type: new Abstract: Vehicle-mounted road cameras are vulnerable to motion blur, defocus, poor illumination, and noise, which can erase thin cracks and pothole boundaries ne

RoboSeg: Online Part-Level Semantic Reconstruction for Robotic Manipulation via a Single Eye-in-Hand Camera

arXiv:2608.09778v1 Announce Type: new Abstract: Robotic manipulation requires perception systemsthat identify actionable parts such as handles, rims, triggers,and tool tips, not merely object categori

researcharxiv-cs-ro

Robotic Fabric Alignment System for Sewing Using Global Local Weighted ICP

arXiv:2608.09528v1 Announce Type: new Abstract: Accurate fabric alignment is a critical step that must be performed before sewing. This paper presents a novel automated fabric alignment system. The sy

local-aiarxiv-cs-ro

Tutorials

Robust Reputation-Driven Crowdsourced Federated Learning

arXiv:2608.08574v1 Announce Type: new Abstract: Crowdsourced Federated Learning (CrowdFL) extends traditional federated learning by enabling open and heterogeneous participation through a crowdsourcin

tutorialsarxiv-cs-lg

RobustDefect-LLM: Explainable and Robustness-Aware Industrial Surface Defect Classification with Decision Support and AI-Assisted Reporting

arXiv:2608.08589v1 Announce Type: new Abstract: This paper presents RobustDefect-LLM, an industrial surface-defect inspection framework integrating deep-learning classification, operator-facing visual

ROEVO: Robust Organized Edge Feature-based Visual Odometry Using RGB-D Cameras

arXiv:2608.09112v1 Announce Type: new Abstract: This work presents a visual odometry (VO) system that leverages image edge features. Edges are spatially expressive cues commonly present across diverse

researcharxiv-cs-ro

RoSE: A Robotic Soft Esophagus for Endoprosthetic Stent Testing

arXiv:2608.09891v1 Announce Type: new Abstract: Soft robotic systems are well suited for developing devices for biomedical applications. A bio-mimicking robotic soft esophagus (RoSE) is developed as a

researcharxiv-cs-ro

RotaryQuant: Fitting 120B MoE Models on Consumer Hardware via Fused Compressed-Space Attention

model-releasesarxiv-cs-lg

arXiv:2608.08081v1 Announce Type: cross Abstract: Large mixture-of-experts (MoE) language models with 26--120 billion parameters exceed the memory capacity of consumer devices through three simultaneo

Hardware

Route AI Agent Workloads Across Models with NVIDIA NeMo Switchyard

NVIDIA NeMo Switchyard is a routing platform that directs AI agent workloads to the most suitable specialized or frontier model for each step of a task, balancing performance, cost, and latency. It of

hardwarenvidia-developer

RouteGuard: Certifying Routing Gain in LLM Multi-Agent Systems When Complementarity Is Not Enough

model-releasesarxiv-cs-lg

arXiv:2608.07583v1 Announce Type: cross Abstract: Multi-agent LLM systems route among model-backed advisors, yet a deployer rarely knows before shipping whether routing will help at all. Prevailing ro

Router Sensitivity Under Lightweight Fine-Tuning Identifies Prunable Experts in Mixture-of-Experts Models

arXiv:2608.07890v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models decouple total parameters from per-token compute, but deployment still requires storing every expert. Recent theory sh

Routesplain: Towards Faithful and Intervenable Routing for Software-related Tasks

arXiv:2511.09373v2 Announce Type: replace-cross Abstract: LLMs now tackle a wide range of software-related tasks, yet we show that their performance varies markedly both across and within these tasks.

researcharxiv-cs-cl

Rumored 50-series Super refresh bumps everything +50% VRAM

leaked Super specs have the 5070 Ti and 5080 going 16GB to 24GB and the 5070 to 18GB, thanks to the new 3GB GDDR7 modules. 24GB on a Ti-class card is actually the number people here have been waiting

local-air-localllama

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance

arXiv:2608.09853v1 Announce Type: cross Abstract: General-purpose reward models are increasingly the bottleneck for scaling robot learning, yet the recipe for learning value-related capabilities from

Industry

Saber denies replacing Rideshare Stimulator’s writers with ChatGPT

After a former lead writer claimed Saber 'replaced me with ChatGPT,' CEO Matthew Karch now claims, 'Neither Saber nor Unigine have replaced any writers with AI,' for the Rideshare 'Stimulator' game an

industrythe-verge-ai

SAFE-CHEM: Uncertainty-Aware Policy Switching for Robust Robotic Chemistry

arXiv:2608.09303v1 Announce Type: cross Abstract: The deployment of autonomous robotic systems in chemistry laboratories is accelerating experimental workflows and providing the foundational data for

safetyarxiv-cs-lg

Tutorials

SafeQL: Search-based Refinement for Safe and Efficient LLM-based Text-to-SQL

arXiv:2608.09260v1 Announce Type: cross Abstract: Large language models (LLMs) have advanced Text-to-SQL by enabling natural language interfaces to databases without task-specific fine-tuning. However

tutorialsarxiv-cs-ai

SafeSceneReason: A Multimodal Reasoning Benchmark Connecting Industrial Hazards with Accident Knowledge

arXiv:2608.09230v1 Announce Type: new Abstract: Industrial-safety understanding requires more than detecting workers, equipment, and personal protective equipment. Models must also assess compliance,

Safety Cost of Steering Vectors Is Separable and Reducible

arXiv:2608.08383v1 Announce Type: new Abstract: Steering vectors are a lightweight tool for controlling LLM behavior. However, emerging evidence shows that steering vectors can unintentionally comprom

safetyarxiv-cs-cl

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems

model-releasesarxiv-cs-cl

arXiv:2608.08237v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems in production operate under strict service level objectives (SLOs) on tail latency and infrastructure cos