All entries

PROVIA: Procedure State Tracking for Online Mistake Detection in Egocentric Videos

arXiv:2609.20638v1 Announce Type: new Abstract: An assistant watching egocentric video should notice a mistake from past frames alone, before the next step begins, and keep working once the person rec

Source

Human DGX agent

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Q&A on Any Spreadsheet Requires Interpreting Its Grid Structure

DGX agent

arXiv:2609.20732v1 Announce Type: new Abstract: Semantic cell annotation improves chunking interpretability for spreadsheets in LLM-driven RAG systems, aiding answer generation through enriched contex

researcharxiv-cs-ai

18 Sept 2026

QCPruner: Query-Conditioned Population Coverage for Visual Token Pruning

model-releasesarxiv-cs-cv

arXiv:2609.19990v1 Announce Type: new Abstract: The high visual-token load in multimodal large language models (MLLMs) motivates training-free pruning to reduce later-layer computation, but under a fi

QEncodeBench: Can Large Language Models Encode Classical Problems into Verified Quantum Oracles?

arXiv:2609.20319v1 Announce Type: cross Abstract: Grover search, amplitude amplification, and quantum counting all rely on the same reusable subroutine, a phase oracle, whose construction the algorith

agentsarxiv-cs-lg

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

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

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

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

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

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

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

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

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

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

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

RoboFind: Multi-Agent Personalized Object Search for People Who Are Blind or Have Low Vision

arXiv:2609.20330v1 Announce Type: new Abstract: Blind and low-vision users often need to locate a specific personal object rather than an arbitrary instance of the same category. The task calls for a

agentsarxiv-cs-ro