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Remember that every news announcement from an AI lab is about $20,000 in product and marketing insights for free. When they provide a few bu…

model-releasesallie-k--miller--x

Remember that every news announcement from an AI lab is about $20,000 in product and marketing insights for free. When they provide a few bullets of what a new model can do, it’s based off of the prev

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Model Releases

RENSA: Rich Environment Metadata to Navigate Shared and Distributed Endpoints for Automated Federated SPARQL Query Generation

DGX agent

arXiv:2608.28963v1 Announce Type: cross Abstract: The number of knowledge graph databases has increased significantly with the proliferation of knowledge graph technologies. Knowledge graphs enable th

model-releasesarxiv-cs-cl

1 Sept 2026

Repair or Resample? Rethinking Failure Debugging in LLM Multi-Agent Systems

arXiv:2608.25920v2 Announce Type: replace Abstract: As large language model (LLM)-based multi-agent systems (MASs) are increasingly applied to long-horizon complex tasks, their reliability has emerged

agentsarxiv-cs-ai

Local Ai

RePair: Turning Retrieval Failures into Counterfactual Hard Pairs

arXiv:2608.29604v1 Announce Type: cross Abstract: Vision-language retrieval with CLIP-style dual encoders achieves strong cross-modal performance, yet practical accuracy often hinges on localized sema

local-aiarxiv-cs-cv

Repeatability Characterisation and Error Budget of a Consumer Structured-Light Scanner for 3-D Wound Geometry:A Rigid-Phantom Study

arXiv:2608.30143v1 Announce Type: new Abstract: We characterise the measurement error of a free- hand consumer structured-light scanner used to derive three- dimensional geometric wound descriptors. R

Representation Learning with Quantum Signal Processing

arXiv:2608.28828v1 Announce Type: cross Abstract: Representation learning begins when training changes the features that define similarity between data. A frozen-kernel model only reweights a fixed ge

researcharxiv-cs-ai

Reproducible macroscopic dynamics in a closed-loop human-AI learning system

arXiv:2608.30946v1 Announce Type: new Abstract: Closed-loop human-AI systems generate high-dimensional behavioural trajectories whose collective dynamics remain obscure. Using 297,915 learners' adapti

Responsible Integration of AI in Cancer Genomics: Barriers, Risks, and Pathways to Trustworthy Clinical Translation

arXiv:2608.30912v1 Announce Type: new Abstract: Artificial intelligence (AI) and natural language processing (NLP) are increasingly used to extract, integrate, and interpret biomedical knowledge relev

Rethinking Language's Role in Efficient VLA for Autonomous Vehicles: Toward Smarter, Trustworthy Driving

arXiv:2608.30144v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are reshaping autonomous driving (AD) by unifying perception, reasoning, and control through language, enabling sema

agentsarxiv-cs-ro

Rethinking the Test-Time Prompt Tuning Objective from the Perspective of Calibration

arXiv:2608.30230v1 Announce Type: new Abstract: Test-time prompt tuning (TPT) has emerged as a powerful paradigm, refining prompts for each test sample via entropy minimization (EM) over multiple augm

researcharxiv-cs-ai

Local Ai

ReTrace: Rejected-Trajectory Conditioning for Speculative Decoding

arXiv:2608.29748v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive language model inference by having a lightweight draft model propose multiple candidate tokens, which ar

local-aiarxiv-cs-cl

Retrieval-Augmented LLM Agents: Learning to Learn from Experience

arXiv:2603.18272v2 Announce Type: replace Abstract: While large language models (LLMs) have advanced the development of general-purpose agents, robust generalization to unseen tasks remains challengin

Retrofitters, pragmatists and activists: Public interest litigation for accountable automated decision-making

arXiv:2511.03211v5 Announce Type: replace-cross Abstract: This paper examines the role of public interest litigation in promoting accountability for AI and automated decision-making (ADM) in Australia

ReVA: A Region-Aware Visual Assistant for Visually Grounded Question Answering

arXiv:2608.28707v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in Visual Question Answering (VQA), yet they continue to struggle with questi

researcharxiv-cs-cl

Reverse N-Wise Output-Oriented Testing for AI/ML and Quantum Computing Systems

arXiv:2602.14275v2 Announce Type: replace-cross Abstract: Artificial intelligence/machine learning (AI/ML) systems and emerging quantum computing software present unprecedented testing challenges char

Review Before Trust: Source-Grounded Integrity Gates for AI-Assisted Personal Health Records

arXiv:2608.29965v1 Announce Type: new Abstract: Large language models can convert medical documents into structured data, but plausible output may still be unsupported by the source. Persisting such o

Revisiting the Provable-Auditable Privacy Gap of DP-SGD

arXiv:2608.28934v1 Announce Type: new Abstract: Differential privacy (DP) has traditionally been used to provide theoretical upper bounds on an algorithm's stability to changing its training data. In

researcharxiv-cs-lg

ReViV: Reconstructing the Viewer and the View in 4D from Monocular Egocentric Video

arXiv:2607.17790v2 Announce Type: replace-cross Abstract: Egocentric devices, such as wearable front-facing cameras, provide a unique perspective for capturing the continuous interaction between a hum

researcharxiv-cs-ai

Applications

Reviving our data foundations is the most disruptive step to data maturity

arXiv:2608.29368v1 Announce Type: new Abstract: The most disruptive step that enterprises of small-medium size and maturity can take to make the most of the latest technological advances in AI is to s

applicationsarxiv-cs-ai

Revolutionizing Turn-by-Turn Navigation with Cloud-Edge Deep Learning

arXiv:2608.29073v1 Announce Type: new Abstract: Turn-by-turn (TBT) navigation systems are integral to modern driving experiences, providing real-time audio instructions to guide drivers safely to dest

Reward-guided Fine-Tuning of One-Step Generative Models via Wasserstein Gradient Flow

arXiv:2608.29647v1 Announce Type: new Abstract: To mitigate the time complexity of generative models, one-step generative models have recently emerged through direct mapping from noise to data in a si

Reward-Oracle MCTS for Formal Theorem Proving: Sample-Efficient Search and the Need for Kernel-Level Proof Auditing

arXiv:2608.28639v1 Announce Type: new Abstract: Formal theorem proving with large language models remains challenging due to the difficulty of navigating large proof search spaces efficiently. Existin

RIDGE: Region-Informed Derivative-Guided Evidence Selection for Long Video Understanding

arXiv:2608.29958v1 Announce Type: new Abstract: Long videos contain far more visual content than Large Vision-Language Models (LVLMs) can process under a fixed visual-token budget, making frame select

Risk-Adjusted Harm Scoring for Automated Red Teaming for LLMs in Financial Services

arXiv:2603.10807v2 Announce Type: replace-cross Abstract: Existing LLM safety evaluations rely on binary attack-success rates and domain-agnostic taxonomies, leaving regulated Banking, Financial Servi

RL-FAT: Reinforcement Learning for Fair Adversarial Training

arXiv:2608.29247v1 Announce Type: new Abstract: Deep neural networks remain highly vulnerable to adversarial perturbations, and adversarial training (AT) has become a widely used approach for improvin

RLG-TPV: Radar- and LiDAR-Guided Tri-Perspective View Fusion for Camera-Radar 3D Object Detection

arXiv:2608.29194v1 Announce Type: new Abstract: Tri-Perspective View (TPV) representations describe 3D scene structure through top, side, and front feature planes, but existing TPV lifting is primaril

RLinf-USER: A Unified and Extensible System for Real-World Online Policy Learning in Embodied AI

arXiv:2602.07837v4 Announce Type: replace Abstract: Online policy learning directly in the physical world is a promising yet challenging direction for embodied intelligence. Unlike simulation, real-wo

safetyarxiv-cs-ro

RoboGesture: Real-Time Semantic-aligned Co-Speech Gestures Generation for Humanoid Interaction

arXiv:2608.28693v1 Announce Type: cross Abstract: Enabling humanoid robots to respond to human speech with synchronized and semantically meaningful gestures is fundamental to natural human-robot inter

safetyarxiv-cs-cv

RoboPhys-3D: A Comprehensive Embodied World Model Evaluation via 3D Reconstruction

arXiv:2608.28718v1 Announce Type: cross Abstract: Video world models increasingly serve as data engines, action planners, and simulators for embodied AI, but conventional embodied world model (EWM) be

Local Ai

Robots that Collaborate: Sequential Asymmetric Imitation for Learning Coupled Robot Policies

arXiv:2606.16490v2 Announce Type: replace Abstract: Collaborative mobile manipulation requires robots to coordinate with a partially observed partner while physically interacting through shared object

local-aiarxiv-cs-ro

Robust Broad Learning System with Wave Loss for Classification under Data Uncertainty

model-releasesarxiv-cs-lg

arXiv:2608.29983v1 Announce Type: new Abstract: Broad Learning System (BLS) offers an efficient alternative to deep architectures by enabling fast learning through randomized feature mapping and close

Robust retinal biometrics for patient identity verification and retrieval across age and imaging devices

arXiv:2608.31094v1 Announce Type: new Abstract: Patient identity errors can compromise longitudinal medical records, research databases, and downstream clinical decisions. We present a retinal biometr

Robust Semi-passive Velocity Field Control with Boundedness Guarantees for Safe Interaction between Mechanical Systems and Physical Environment

arXiv:2608.30193v1 Announce Type: cross Abstract: Controllers that guarantee energetic passivity with respect to the pair of external force and velocity realize safe interaction between the mechanical

safetyarxiv-cs-ro

Robustness of Vision Language Models Against Split-Image Harmful Input Attacks

arXiv:2602.08136v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are now a core part of modern AI. Recent work proposed several visual jailbreak attacks using single/ holistic i

RoSe-SLAM: Robust Semantic-Aware Gaussian Splatting SLAM from Dynamic Monocular Videos

arXiv:2608.29003v1 Announce Type: cross Abstract: In dynamic and unstructured environments, conventional SLAM systems generally suffer from significant accuracy degeneration due to their static assump

Tutorials

Rotational Equivariance in Machine Learning: A Comprehensive Tutorial

arXiv:2608.31045v1 Announce Type: new Abstract: Rotational symmetry is one of the most important structural principles in machine learning on 3D data. In applications ranging from physics and material

tutorialsarxiv-cs-lg

RouteSparse: Input-Conditional Pattern Routing for Budgeted Long-Context Prefilling

model-releasesarxiv-cs-cl

arXiv:2608.29058v1 Announce Type: new Abstract: Dynamic sparse attention can reduce the quadratic cost of long-context prefilling without changing model weights. MInference assigns each attention head

RSLM: Training-Free Vector Quantization for Approximate Nearest Neighbor Search

model-releasesarxiv-cs-lg

arXiv:2608.30384v1 Announce Type: new Abstract: By introducing RSLM (Rotated Scaled Lloyd-Max), a family of training-free vector quantization codecs compressing embeddings to 1--4 bits per dimension,

RSPO: Regularized Self-Play Alignment of Large Language Models

arXiv:2503.00030v3 Announce Type: replace-cross Abstract: Self-play-based policy optimization has emerged as an effective approach for fine-tuning large language models (LLMs), formulating preference

Rubric-to-Code Credit Assignment for Reinforcement Learning

arXiv:2608.27906v2 Announce Type: replace Abstract: Interactive web application generation requires models to produce usable HTML, CSS, and JavaScript applications from natural language requests. Unli

Runtime Safety Filtering for Learned Small UAS Separation Policies under GNSS Degradation

arXiv:2607.10014v2 Announce Type: replace-cross Abstract: Learning-based separation assurance for small Unmanned Aircraft Systems (sUAS) achieves near-zero collision rates in simulation, but assumes a

RWKV-7 G1j (100% RNN) release 🙂 much better at agent/coding/STEM and everything. Demo: https://rwkv.com Weights: https://huggingface.co/Bli…

RWKV-7 G1j (100% RNN) release 🙂 much better at agent/coding/STEM and everything. Demo: https://rwkv.com Weights: https://huggingface.co/BlinkDL/rwkv7-g1 RWKV-7 G1i (100% RNN) release 🙂 Demo: https://r

agentsjeremy-howard--x

S3C-LLM: Skill-Code Guided Agentic Language Models for Spectrum-to-Structure Elucidation

arXiv:2608.30910v1 Announce Type: cross Abstract: Spectroscopic structure elucidation is central to molecular analysis, but recent Large Language Model (LLM)-based methods mostly formulate it as direc

agentsarxiv-cs-cl

S3Gym: Can LLMs Turn Self-Testing and Self-Judging into Self-Improvement?

model-releasesarxiv-cs-cl

arXiv:2608.31100v1 Announce Type: new Abstract: Large language models (LLMs) increasingly interact with external environments and accumulate substantial behavioral experience, yet existing agent bench

Safe to Resume? Breaking Execution Continuity of Agent Execution via Rollback

arXiv:2608.29381v1 Announce Type: cross Abstract: AI agents are moving toward persistent, stateful execution across various applications, accumulating execution state and external effects that are cos

agentsarxiv-cs-ai

SafeAtlas-VL: Beyond Binary Multimodal Safety with Large-Scale Data and Guard Models

arXiv:2608.29098v1 Announce Type: new Abstract: Multimodal safety moderation requires distinguishing risks arising from visual content, user intent, and assistant behavior. Existing safeguards, howeve

SafeMath: Inference-time Safety improves Math Accuracy

arXiv:2603.25201v2 Announce Type: replace Abstract: Recent research points toward LLMs being manipulated through adversarial and seemingly benign inputs, resulting in harmful, biased, or policy-violat

safetyarxiv-cs-cl

Safety Screening for Voltage Control in Active Distribution Grids via Distributionally Robust Conformal Screening

arXiv:2608.30889v1 Announce Type: cross Abstract: Deploying a new control policy for voltage control in active distribution grids requires evidence that physical limits will be satisfied before the po