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QoS-Aware Federated Learning for Multimodal In-Cabin Interaction in Smart Vehicles

arXiv:2609.20123v1 Announce Type: new Abstract: Modern smart vehicles leverage multimodal sensors, ranging from high-bandwidth vision systems to low-rate physiological monitors, to provide personalize

local-aiarxiv-cs-lg

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QUALS: Corpus Equilibrium for Universal Forecasting via Pattern Quantization and Learnability Synchronization

DGX agent

arXiv:2609.20156v1 Announce Type: cross Abstract: Ubiquitous time series data across diverse domains enables critical applications in areas such as transportation systems and power grids. Recently, tr

researcharxiv-cs-ai

18 Sept 2026

Quantifying Mechanical Intelligence in Legged Robots with Information Theory

model-releasesarxiv-cs-ro

arXiv:2609.19588v1 Announce Type: new Abstract: Mechanical intelligence, loosely defined as the reduction in control burden afforded by a robot's physical form, has become a prominent concept in robot

Agents

Quantifying Overclaiming Propensity in Frontier LLM Agents

arXiv:2609.20812v1 Announce Type: cross Abstract: Frontier coding agents are increasingly trusted to work autonomously for long periods, yet an agent's final response is often the only account of that

agentsarxiv-cs-ai

Quantum Graph Convolutional Networks: Implementation and Trainability Analysis

model-releasesarxiv-cs-lg

arXiv:2609.19983v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) achieve state-of-the-art performance on graph-structured data, but training and inference on large graphs are often bottl

QUATRO: Query-Adaptive Trust Region Policy Optimization for LLM Fine-tuning

arXiv:2602.04620v3 Announce Type: replace Abstract: GRPO-style reinforcement learning (RL)-based LLM fine-tuning algorithms have recently gained popularity. Relying on heuristic trust-region approxima

safetyarxiv-cs-lg

Queries Knew More Than We Thought: Uncovering Latent Knowledge in Segmentation Models

arXiv:2609.20283v1 Announce Type: new Abstract: Modern segmenters often fail after the expensive computation has already been done: a useful mask is present among the model's query-conditioned candida

Question: UkisAI Swift Ternary Bonsai 2 27B?

model-releasesr-localllama

Hey community, Jovan from UkisAI here, We're the team behind Swift Qwen3.8 27B, the Qwen model with token usage and overthinking error improvements Our estimate is that we can make a great improvement

Quoting Thariq Shihipar

model-releasessimon-willison

We're adding support for AGENTS.md to Claude Code. Starting today in version 2.1.277, if there is no CLAUDE.md in a folder, Claude will check for and use AGENTS.md. AGENTS.md support is built off of C

QVAC Genesis III: A Large-Scale, High-Quality Open Synthetic STEM Corpus for Efficient Language Model Pre-Training

arXiv:2609.19513v1 Announce Type: new Abstract: High-quality pre-training data is a critical bottleneck for educational and STEM-specific language models targeting edge AI and on-device deployment whe

Qwen3.8-Flash-Next (95.5 GiB) on a 64GB Mac at ~27 tok/s, checkpoint + fork

model-releasesr-localllama

I've been running Qwen3.8-Flash-Next as my main local coding model from past few weeks. The file is 95.5 GiB and my Mac has 64 GB. It works because the routed experts stay on SSD and only get read whe

Radio-Frequency Convolutional Neural Networks

arXiv:2609.19279v1 Announce Type: new Abstract: Running artificial intelligence (AI) models directly on edge devices such as smartphones, wearables, and drones offers low latency, pervasive scalabilit

Radio Frequency Detection and Classification of Microplastics in Water

arXiv:2609.20507v1 Announce Type: new Abstract: Micro- and nano-plastic particles (MPs/NPs) are ubiquitous environmental contaminants whose increasing abundance and potential health impacts have creat

RAFT: A Stateful Retrieval-Augmented Framework for Troubleshooting Agents

arXiv:2609.20754v1 Announce Type: new Abstract: Effective troubleshooting agents in enterprise customer support depend on retrieving actionable guidance from similar historical cases, yet existing ret

Applications

Randomized SVD Approximations for Spectral Co-Clustering of Word-Document Matrices

arXiv:2609.19243v1 Announce Type: cross Abstract: Spectral co-clustering is a useful tool for discovering latent structure in word-document matrices, but its reliance on singular value decomposition (

applicationsarxiv-cs-ai

RAUL: Reference-Assisted Ureteroscopy Localization for Skill Assessment

arXiv:2609.19236v1 Announce Type: new Abstract: Objective: Incomplete navigation of anatomy during ureteroscopic kidney stone surgeries can contribute to repeat interventions. While skilled surgeons h

Applications

RawSLAM: Online HDR Gaussian SLAM from Linear Radiance

arXiv:2609.20589v1 Announce Type: new Abstract: Current dense visual SLAM systems rely almost exclusively on 8-bit tonemapped Low Dynamic Range (LDR) inputs, limiting their robustness in extreme light

applicationsarxiv-cs-cv

Reach or Solve? Attributing Agentic RL Gains with Checkpoint Handoffs

arXiv:2609.19636v1 Announce Type: new Abstract: Reinforcement learning now trains language-model agents that act over dozens of steps in live environments. The gains are large, and they are read as be

REACT: A Fully Spiking State-Space Model for Real-Time Event-Driven Temporal Perception

arXiv:2609.19204v1 Announce Type: cross Abstract: Robotic systems operating in dynamic environments require visual perception that evolves continuously with the incoming sensory stream. Event cameras

local-aiarxiv-cs-ai

Reading Emotions in the Token Space: Discriminative Adaptation of SpeechLLMs for Emotion Recognition

arXiv:2609.20081v1 Announce Type: cross Abstract: SpeechLLMs have shown strong potential for emotion recognition, yet they read the predicted emotion off a generative decoder not suited for classifica

researcharxiv-cs-ai

Agents

REARL: A Closed-loop Autonomous Driving Simulation Enhancement Framework with Real Traffic Data and Large Language Models

arXiv:2609.19903v1 Announce Type: new Abstract: Accurate simulation is crucial for autonomous driving development, yet capturing real-world traffic complexity remains challenging. Existing simulators

agentsarxiv-cs-lg

Recency Forcing: Bridging the Long-Horizon Gap in Autoregressive Video Generation

arXiv:2609.19729v1 Announce Type: new Abstract: Autoregressive (AR) video generation degrades over long horizons due to an overlooked train-inference discrepancy we term KV eviction mismatch: models t

safetyarxiv-cs-cv

Hardware

Recovering Aggressively Pruned Vision-Language-Action Models with Offline Hidden-State Distillation

arXiv:2609.19579v1 Announce Type: new Abstract: Vision-language-action (VLA) models let robots follow language instructions, but their language backbones of several billion parameters are the main obs

hardwarearxiv-cs-ro

Recursive Quantum Long Short-Term Memory for Stable Short-Horizon Temperature Forecasting

arXiv:2609.20594v1 Announce Type: new Abstract: Quantum long short-term memory (QLSTM) models extend recurrent sequence learning with variational quantum circuits, but their optimization behavior can

Red-Teaming Auto Mode: Improving Blocking Classifiers Against Malign Coding Agents

arXiv:2609.19587v1 Announce Type: cross Abstract: To keep coding agents from going off the rails, production systems now review each proposed action with a blocking monitor that can reject it before i

Redact or Keep? A Fully Local AI Cascade for Educational Dialogue De-Identification

arXiv:2606.18372v2 Announce Type: replace-cross Abstract: Educational dialogue is a valuable but sensitive resource for research: the same transcripts that capture authentic learning often capture per

local-aiarxiv-cs-ai

Redemption Score: A Multi-Modal Evaluation Framework for Image Captioning via Distributional, Perceptual, and Linguistic Signal Triangulation

model-releasesarxiv-cs-cl

arXiv:2505.16180v3 Announce Type: replace-cross Abstract: Evaluating image captions requires cohesive assessment of both visual semantics and language pragmatics, which is often not entirely captured

Refinement Is Inherently Editable: Training-Free Prompt-to-Prompt Image Editing with Generative Refinement Network

arXiv:2609.20633v1 Announce Type: new Abstract: Text-guided image editing must introduce the requested changes while preserving unrelated source content. Diffusion-based editors rely on spatial contro

Reflective Recovery: A Self-Supervised Method for Reasoning by Learning from Mistakes

model-releasesarxiv-cs-cl

arXiv:2609.19156v1 Announce Type: new Abstract: Data-driven fine-tuning is widely adopted to enhance reasoning in Large Language Models (LLMs) due to its simplicity and efficiency. However, mainstream

Refuse, Decompose, Refresh: A Claim-Safe Protocol for Closed-Loop AI Evaluation

arXiv:2609.20538v1 Announce Type: new Abstract: An AI evaluation can be perfectly reproducible and still support the wrong claim. This risk is acute in closed-loop systems: policy determines visited s

Region-Level Policy Optimization for Fine-grained MLLM Perception

arXiv:2609.19745v1 Announce Type: new Abstract: Fine-grained visual perception in MLLMs is commonly improved by raising the resolution, but the added visual tokens inflate vision-encoding and language

local-aiarxiv-cs-cv

Regularized Emphatic Temporal-Difference Learning: Stability under Constant Stepsizes

arXiv:2609.19170v1 Announce Type: new Abstract: Emphatic temporal-difference learning (ETD) stabilizes the expected off-policy TD update and changes its projection geometry, but neither property deter

Reimagining service delivery in the agentic era with Google Public Sector

model-releasesgoogle-cloud-ai

State and local governments are driven by a shared mission to provide responsive, equitable, and accessible services. However, achieving this goal is often hindered by legacy technical debt, disconnec

Relational Attention for Data-Efficient Language Modeling

arXiv:2609.20530v1 Announce Type: new Abstract: We present Relational BabyLM, a system submission to the BabyLM 2026 challenge that combines two cognitively motivated inductive biases in a single deco

researcharxiv-cs-cl

Replan, Repair, or Edit? A Unified Empirical Evaluation of Travel Agents for Itinerary Revision under Resource Disruptions

arXiv:2609.19654v1 Announce Type: new Abstract: Travel-planning agents generate itineraries that may become infeasible after acceptance because of flight cancellations, hotel unavailability, or attrac

Reproducibility is not construct validity: LLM measurement of institutionally situated communication

arXiv:2609.19866v1 Announce Type: new Abstract: High annotation reproducibility does not necessarily imply that an LLM-inferred measure captures the construct it is intended to measure. We test this d

Reproducing Transparent and Scrutable Recommendations: Exploring Open-Weight Models via Natural-Language User Profiles

arXiv:2609.19831v1 Announce Type: cross Abstract: In this reproducibility study, we investigate the transparency and scrutability of recommender systems enhanced by incorporating generated natural-lan

researcharxiv-cs-ai

Researchers used Claude to hack OpenAI

model-releasesars-technica

In September 2026 Hacktron AI researchers used Anthropic’s Claude to exploit a flaw in OpenAI’s community‑forum hosting configuration, giving them access to an employee’s ChatGPT account and confident

ReShoot: Generative Visual Domain Randomization of Recorded Robot Demonstrations for Visuomotor Policy Learning

arXiv:2609.19661v1 Announce Type: new Abstract: Imitation-learned robot policies are frequently overfit to the visual conditions present in their training demonstrations. Consequently, variations in o

safetyarxiv-cs-ro

Resilient Motion Planning for Free-Flying Space Robots under Actuator Failures

arXiv:2609.20407v1 Announce Type: new Abstract: Free-flying robots rely on multiple thrusters to maneuver in space. If one or more of these thrusters fail, the robot may lose control authority and ris

local-aiarxiv-cs-ro

ResNLS: An Improved Model for Stock Price Forecasting

arXiv:2312.01020v3 Announce Type: replace Abstract: Stock prices forecasting has always been a challenging task. Although many research projects try to address the problem, few of them pay attention t

Resolution limits for process comparison from event data

arXiv:2609.20489v1 Announce Type: cross Abstract: One hospital runs bloods and imaging at the same time. Another runs them one after the other, in either order, equally often. Knowing which actually h

Agents

Rethinking Multi-Agent Collaboration: When More Is Less

arXiv:2609.19759v1 Announce Type: new Abstract: The rapid advancement of large language models and single-agent harnesses has reshaped the landscape of autonomous systems, raising a critical question

agentsarxiv-cs-ai

RetireOPD: Self-Retiring On-Policy Distillation for Agentic Reinforcement Learning

arXiv:2609.20784v1 Announce Type: cross Abstract: Multi-turn agents trained with reinforcement learning (RL) receive a single scalar reward per trajectory, which motivates self on-policy distillation

RGS: Reflection-aware Gaussian Splatting via Learning Geometry Continuity for Reflective Objects

arXiv:2609.19421v1 Announce Type: new Abstract: Gaussian Splatting has significantly improved the quality of novel view synthesis with explicit Gaussian representation. However, we observed that exist

Riemannian--Lorentz Fusion of Vision Transformers and State-Space Models

arXiv:2609.19384v1 Announce Type: cross Abstract: Scaling deep learning faces critical bottlenecks: data exhaustion, exponential training costs, and resource concentration. Model merging combines pre-

Applications

RISC-V and machine learning: a survey

arXiv:2609.20677v1 Announce Type: new Abstract: The intersection of open-source processor architectures and machine learning is driving the demand for customizable, efficient, and accessible hardware.

applicationsarxiv-cs-lg

Risk-Set Transported Synthetic Control with Difference-in-Differences Adjustment under Staggered Treatment Adoption

arXiv:2609.20264v1 Announce Type: cross Abstract: In staggered treatment-adoption designs, later-treated units are valid controls for an earlier-treated cohort only until their own treatment begins, s