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arXiv:2609.33384v1 Announce Type: new Abstract: Quantization errors in video diffusion transformers can be amplified or attenuated by subsequent denoising updates, making local reconstruction error an

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Q-Drift: Quantization-Aware Drift Correction for Diffusion Model Sampling

DGX agent

arXiv:2603.18095v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is a practical path to deploy large diffusion models, but quantization noise can accumulate over the denoising traj

applicationsarxiv-cs-cv

29 Sept 2026

Q-WAM: 4-Bit Quantization of World Action Models with Action-Subspace Protection

model-releasesarxiv-cs-cv

arXiv:2609.33269v1 Announce Type: cross Abstract: World Action Models (WAMs) jointly generate video and robot actions through iterative diffusion and perform strongly in robotic manipulation. However,

QAMM: Adjoint MeanFlow Matching for Few-Step Offline Reinforcement Learning

arXiv:2609.34497v1 Announce Type: new Abstract: Flow policies can model rich action distributions, but their iterative sampling limits decision speed. Adjoint matching uses the critic's action gradien

QSCP: Beyond Class-Name Prompts for Query-Guided Semantic Change Parsing

arXiv:2609.33088v1 Announce Type: new Abstract: Traditional change detection (CD) identifies changes between bi-temporal remote sensing images, while semantic change detection (SCD) assigns predefined

Query-aligned video frame selection for long video understanding

arXiv:2609.31668v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) process multimodal inputs by converting text, images, and videos into token sequences that are subsequently pro

QwenGyre: An Elastic Reinforcement Learning Framework for Training xLong-Horizon Agents

arXiv:2609.33848v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly undertake extreme-long (xlong) horizon tasks, where a single execution can span hours, hundreds of model-

R2T: Rule-Encoded Loss Functions for Sequence Tagging in Low-Resource Languages

arXiv:2510.13854v2 Announce Type: replace-cross Abstract: We introduce Rule-to-Tag (R2T), a framework that turns linguistic rules into the training signal for neural sequence taggers in low-resource l

Radiomap Blind Prediction under Incomplete Observation: Error Characterization and Correctable Propagation-Prior Learning

arXiv:2609.32836v1 Announce Type: cross Abstract: Radiomap blind prediction aims to infer radiomaps from observable representations of the propagation environment and base station configuration withou

Rate-Distortion Adaptive Primitive Selection for Omnidirectional Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2609.34367v1 Announce Type: new Abstract: Learned image codecs (LICs) achieve high reconstruction quality, but their decoding speed is often insufficient for immersive virtual reality (VR). Gaus

RecastVLA: From Past Interaction to Future Control with Adaptive Policy States

arXiv:2609.32155v1 Announce Type: new Abstract: Sequential manipulation requires a robot to track what has already happened, even when the current scene no longer reveals it. Policies with explicit hi

safetyarxiv-cs-ro

Recipe-Matching, Not Equivalence

arXiv:2609.31927v1 Announce Type: cross Abstract: MathNet-Retrieve asks a retriever to find, for a math problem, a document stating the same problem. An LLM under one fixed prompt writes each gold doc

Re:Cognize -- Open-Set Comic Character Re-Identification

arXiv:2609.34032v1 Announce Type: new Abstract: A manga reader meets a character on one page and knows them on sight a hundred pages later, without ever being handed a cast list. Re-identifying comic

Reduce, Then Encode: Multiscale Volumetric Reduction for 2D Foundation Models in Brain MRI

arXiv:2609.35405v1 Announce Type: new Abstract: Pretrained 2D foundation models offer a practical alternative to dedicated 3D pretraining for brain structural magnetic resonance imaging (sMRI), but th

Reduced Cartesian Kinetostatics for Tendon-Driven Continuum Robots: Residual-Stabilized Full-Shape Propagation

arXiv:2609.31771v1 Announce Type: new Abstract: Many planning and control tasks for tendon-driven continuum robots (TDCRs) require the complete Cartesian backbone geometry. We present a reduced Cartes

safetyarxiv-cs-ro

Reference-Tail Trust:Certified Probability Floors for Learned Updates Inside a Deployed Network

arXiv:2609.34904v1 Announce Type: new Abstract: Graph neural networks (GNNs) need to exploit improved message passing without surrendering control over predictions already trusted in deployment. We in

Agents

REFINE: A Resilient Evolution Framework for Intelligent Enterprise Alert Triage in Security Operations Centers

arXiv:2609.32516v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) process large volumes of alerts daily. Alert triage prioritizes high-risk threats while reducing manual review of b

agentsarxiv-cs-lg

RefineDrive: Reliable Failure-Guided Learning for Vision-Language-Action Driving

arXiv:2609.35078v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models for autonomous driving rely heavily on successful expert demonstrations, leaving model-specific failures underexploi

Refinement Symmetry in Multimodal Transformers

arXiv:2609.32669v1 Announce Type: cross Abstract: Attention weights depend on token counts, which change with the representation of a signal. We study refinement symmetry: splitting a representation w

ReFM: Semantic-Aware Refinement Flow Model for Motion Retargeting

arXiv:2609.32068v1 Announce Type: new Abstract: Motion retargeting transfers motion across characters with different skeletal structures while preserving semantic intent and physical plausibility. Des

Reinforcement Learning from Intermediate Renders for Image-to-Code Generation

arXiv:2609.34587v1 Announce Type: new Abstract: Reinforcement learning is increasingly used to post-train vision-language models for image-to-code generation, such as generating SVG code from a refere

Relational Compression: A Framework for Relational Fidelity in Constrained Representations

arXiv:2609.31816v1 Announce Type: new Abstract: What should a compressed representation preserve when the information of interest lies in relationships among elements rather than in the elements thems

Resolving State-Representation Mismatch: State-Space Visual Reasoning for Open-Loop VLA Planning

arXiv:2609.33412v1 Announce Type: new Abstract: Despite rapid progress in vision-language-action (VLA) models, existing reasoning paradigms still face a fundamental state-representation mismatch in op

Resource-Aware Parameter-Efficient Model Adaptation for Onboard High-Dimensional Data

model-releasesarxiv-cs-cv

arXiv:2609.33687v1 Announce Type: new Abstract: Onboard satellite models often require frequent updates, but the weights adapted to earlier data distributions can quickly become outdated. However, upd

Applications

Rethinking Causal Action Tokenization with Conditional Annealing in Flow Matching

arXiv:2609.35469v1 Announce Type: cross Abstract: Autoregressive Vision-Language-Action (VLA) models offer a scalable path to robot learning, yet existing action tokenizers treat tokenization as a com

applicationsarxiv-cs-lg

Rethinking Latent Visual Reasoning: Grounding Latent Reasoning in Visual Evidence

arXiv:2609.34563v1 Announce Type: new Abstract: Latent visual reasoning (LVR) enables multimodal large language models (MLLMs) to perform intermediate computation in continuous latent tokens rather th

Rethinking the Fully Hyperbolic Vision Transformer in Polar Coordinates

arXiv:2609.32899v1 Announce Type: new Abstract: Hyperbolic space can embed intrinsic hierarchies in data with low distortion due to the exponential growth of volume with distance from the origin. Howe

Retracing Hodgkin and Huxley: State Recovery Does Not Certify Mechanism

arXiv:2609.34566v1 Announce Type: new Abstract: Predicting observed dynamics does not establish recovery of the underlying physical mechanism. Can machine learning retrace the hidden-state reasoning b

Agents

Retrieved but Not Delivered: Multimodal Memory Delivery for Long-Term Agents

arXiv:2609.32590v1 Announce Type: new Abstract: Work on memory for multimodal agents optimizes what is written, updated and retrieved. Between retrieval and the answer, however, is a stage that multim

agentsarxiv-cs-cv

Retrospective Distillation Attribution via Normalized Response Similarity

arXiv:2609.32749v1 Announce Type: cross Abstract: Model distillation transfers capabilities through supervised fine-tuning (SFT) on teacher responses, often collected from commercial APIs, raising que

Reuse or Relearn? A Spectral View of Earth Observation Foundation Models

arXiv:2609.32756v1 Announce Type: new Abstract: Foundation models are rarely used as generic, frozen feature extractors; instead, they are fine-tuned for the target downstream application. This practi

ReVision3D: Attribution-Guided Recursive Self-Improvement for 3D Medical Perception

arXiv:2609.32984v1 Announce Type: new Abstract: Recursive self-improvement (RSI) offers a promising path for overcoming the limited visual capability of current medical imaging agents. Yet applying RS

Local Ai

RICE-Alpha: Reliability-Informed Correction with Event Graphs for LLM-Agent Stock Forecasting

arXiv:2609.34004v1 Announce Type: new Abstract: Equity-relevant news evolves through temporally dependent corporate events, making historical information useful only when event continuity, information

local-aiarxiv-cs-lg

RoboFFT: Finetuning generative robot policy via online reinforcement learning with forward process

arXiv:2609.32236v1 Announce Type: new Abstract: Generative models, such as diffusion and flow-based models, have shown strong promise for robot policy learning by capturing complex and multimodal acti

safetyarxiv-cs-ro

Applications

RoboSTAR: Next-Scale Autoregressive Sign Language Translation for Humanoid Robots

arXiv:2609.32250v1 Announce Type: new Abstract: Sign-language interpretation in public communication relies on qualified professional interpreters and can be difficult to scale, motivating robotic sig

applicationsarxiv-cs-cv

RoGSW4RLD: Feed-Forward 4D Gaussian Lifting for Robot World Model Rollouts

arXiv:2609.35311v1 Announce Type: new Abstract: Action-conditioned video world models predict future robot interactions from multiple cameras, yet their outputs remain disparate video collections rath

Applications

Rondo: Unsupervised Discovery of Recurring Temporal Structure

arXiv:2609.32500v1 Announce Type: new Abstract: Many real-world time series data exhibit structural properties at multiple scales, from short, recurring units to complex sequences composed of these un

applicationsarxiv-cs-lg

Routing Drift Alone Does Not Diagnose Failure in Merged MoE LLMs

arXiv:2609.32821v1 Announce Type: cross Abstract: Model merging efficiently combines specialized large language models (LLMs) without joint retraining, but can substantially alter expert routing in Mi

RPA: Residual Patch-Token Adapter for Image Retrieval from EEG and MEG

arXiv:2609.31698v1 Announce Type: new Abstract: Most existing MEG and EEG (M/EEG) visual decoding methods align brain signals with a single global embedding extracted from a pretrained visual encoder,

RubiCap: Rubric-Guided Reinforcement Learning for Dense Image Captioning

arXiv:2603.09160v2 Announce Type: replace Abstract: Dense image captioning is critical for vision-language pretraining and for text-to-image generation, but scaling expert-quality annotations is prohi

Tutorials

S^2COPE: Self-Supervised Concept Discovery via Preference Learning

arXiv:2606.14586v2 Announce Type: replace Abstract: Self-supervised learning can learn useful representations from unlabeled images. Yet these representations remain largely opaque, making it difficul

tutorialsarxiv-cs-cv

SafeMol: Dual-Modality Safety Alignment for Molecular Multimodal Models

arXiv:2609.33640v1 Announce Type: new Abstract: Molecular multimodal models support diverse understanding and generation tasks but may introduce safety vulnerabilities when handling hazardous molecule

SAGE: Semantic Audio Generative Encoder

arXiv:2609.32755v1 Announce Type: cross Abstract: Audio autoencoders compress waveforms into compact latent representations that serve as the interface between raw audio and downstream models. Current

SAGE: Symbolic Action-Gating and Editing for LLM Task Planners

model-releasesarxiv-cs-ro

arXiv:2609.34268v1 Announce Type: new Abstract: Large language models (LLMs) are now the default cognitive core of embodied household agents, yet the plans they emit are rarely checked against a groun

SAMBAR: Selective Anchoring via Method of Multipliers for Balanced Knowledge Acquisition and Retention in Vision-Language-Action Models

arXiv:2609.32108v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models leverage large-scale pretraining to ultimately achieve generalist manipulation. Deployed VLA policies must support c

Scalable and Data-Driven Decision Support in the Maintenance, Repair, and Overhaul Process

arXiv:2609.33641v1 Announce Type: cross Abstract: Several businesses apply maintenance, repair, and overhaul (MRO) principles to the life-cycle of their existing products. In cases like casted gas tur

Scalable Attribution and Control of Model Behavior During Training

arXiv:2609.33667v1 Announce Type: new Abstract: Attributing and controlling model behavior during training requires identifying each example's contribution quickly enough to act before the next update

Scalable In-Context Reinforcement Learning with Recurrent Algorithm Distillation

arXiv:2609.35333v1 Announce Type: new Abstract: Algorithm Distillation (AD) has demonstrated the remarkable ability of Transformers to perform in-context reinforcement learning without explicit weight