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Learning and interpreting policies for simultaneous entanglement requests in quantum networks

arXiv:2609.30157v1 Announce Type: cross Abstract: Future quantum networks will make use of entanglement to perform numerous tasks, such as sending quantum information over long distances, distributed

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Learning Better Reasoning for Generative Recommendation with Semantic IDs

DGX agent

arXiv:2609.29973v1 Announce Type: cross Abstract: Generative recommendation reformulates item retrieval as sequence generation, allowing a unified model to directly generate the next item from a user'

safetyarxiv-cs-ai

25 Sept 2026

Learning Causal Structure of Time Series using Best Order Score Search

arXiv:2603.05370v2 Announce Type: replace-cross Abstract: Causal structure learning from observational data is central to many scientific and policy domains, but the time series setting common to many

safetyarxiv-cs-ai

Learning from Mixed-Quality Deployment Experience for Robot Manipulation

arXiv:2609.29000v1 Announce Type: new Abstract: Robot policies deployed in real environments naturally accumulate mixed-quality experience, including successful executions, partial progress, and failu

safetyarxiv-cs-lg

Tutorials

Learning New Words from Unlabeled Test Data in Automatic Speech Recognition

arXiv:2609.28877v1 Announce Type: cross Abstract: New words are invented every day. A human listener can learn a new word by hearing it clearly once and inferring its usage from sentence context. This

tutorialsarxiv-cs-cl

Learning to Discover Interesting Mathematics

arXiv:2609.28603v1 Announce Type: cross Abstract: Recently, Large Language Models (LLMs) have been increasingly able to solve advanced mathematical problems, including many that have been open for dec

researcharxiv-cs-ai

Learning to Ideate for Scientific Impact

arXiv:2609.29802v1 Announce Type: new Abstract: Scientific ideation is increasingly mediated by large language models, but current ideation systems are usually trained and evaluated on immediately jud

researcharxiv-cs-ai

Hardware

Less is More: Encoder-only Audio-Visual Segmentation

arXiv:2609.29121v1 Announce Type: cross Abstract: Audio-Visual Semantic Segmentation (AVSS) aims to identify, segment, and classify sound-emitting objects in video frames. Previous Transformer-based A

hardwarearxiv-cs-ai

Tutorials

Let Training Guide Selection: Online Synthetic Data Filtering via Real-Anchored Utility

arXiv:2609.29988v1 Announce Type: new Abstract: Synthetic data can scale training supervision when real-world data are limited, but noise and distribution mismatch can reduce its value. Existing synth

tutorialsarxiv-cs-lg

Lightweight Probabilistic Downscaling from a Deterministic Base Model

arXiv:2609.29383v1 Announce Type: new Abstract: Climate data downscaling is the task of increasing the spatial resolution of climate data, typically by generating fine-resolution regional climate data

Lightweight Vision Transformer-Based U-Net for Brain Tumor Segmentation from MRI

arXiv:2609.29785v1 Announce Type: new Abstract: Accurate brain tumor segmentation from Magnetic Resonance Imaging is essential for diagnosis, treatment planning, and surgical guidance. Although Convol

local-aiarxiv-cs-cv

Likelihood Ranking doesn't Scale Like Prompting in LLMs

arXiv:2609.29390v1 Announce Type: new Abstract: LLM evaluation is commonly performed either by prompting models to produce answers or by scoring candidate outputs with likelihood-based metrics. In mul

researcharxiv-cs-cl

Limited Structural Reliability in Public Educational Prediction Benchmarks: A Four-Dimension Audit of Seven Datasets

arXiv:2609.29625v1 Announce Type: new Abstract: Across seven public educational prediction datasets, three passed all four pre-modeling reliability checks; the remaining four either failed group-aware

LiveMathematicianBench: A Live Benchmark for Research-Level Mathematical Reasoning with Proof Sketches

arXiv:2604.01754v2 Announce Type: replace-cross Abstract: Mathematical reasoning is a hallmark of human intelligence, and whether large language models (LLMs) can meaningfully perform it remains a cen

LLM Agents Can Easily Tamper With Their Own Traces

arXiv:2609.30266v1 Announce Type: cross Abstract: Asynchronous monitoring, incident investigations, and compliance audits primarily rely on agent traces to reconstruct what happened. These analyses as

LLM Forensics: Where Do Backdoors Hide? Localizing and Controlling Trigger Mechanisms with Sparse Autoencoders

arXiv:2609.07746v2 Announce Type: replace Abstract: Even though backdoors in LLMs have been a growing concern, their inner workings are still under heavy scrutiny. Trigger-based backdoors are easy to

researcharxiv-cs-cl

LLM surprisal is necessary but not sufficient to capture English garden-path effects: Evidence from joint latent modeling of reading paradigms

arXiv:2602.04489v2 Announce Type: replace Abstract: Temporarily ambiguous garden-path sentences ('While the team trained the striker wondered... ') are known to cause processing difficulty, which can

researcharxiv-cs-cl

LLMersion: A Local-First AI Agent Framework for Low-Cost Home Language Learning toward Educational Equity

model-releasesarxiv-cs-cl

arXiv:2609.29672v1 Announce Type: new Abstract: Artificial intelligence helps education most where an essential provision has been rationed by cost. For language learners that provision is a teacher's

Long-Tail Adaptive Flow Matching with Explicit Conditional Consistency Guidance for Precise Multimodal Face Synthesis

arXiv:2609.29581v1 Announce Type: new Abstract: Although diffusion-based methods have substantially improved the controllability of multimodal face synthesis, their semantic alignment remains suboptim

safetyarxiv-cs-cv

Looks the Same, Answers Differently: Flip-Direction Steering for Robust Vision-Language Reasoning

model-releasesarxiv-cs-cv

arXiv:2609.28851v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong visual reasoning performance, yet subtle changes from routine image capture and processing can alter their

Agents

Low-Cost Assays for Measuring Model Behavior Across Vendors and Releases

arXiv:2609.30012v1 Announce Type: cross Abstract: Language models advise people, keep them company, and write software while they sleep. Measuring what they do is hard: behavior has to be sampled repe

agentsarxiv-cs-ai

M-plicits: Neural Implicit Surfaces via Nested Multiscale Residuals

model-releasesarxiv-cs-cv

arXiv:2609.28684v1 Announce Type: new Abstract: Encoding input coordinates with sinusoidal functions into multi-layer perceptrons (MLPs) has proven effective for implicit neural representations (INRs)

M^2PFN: End-to-End Disentangled Alignment for Generalizable Multimodal In-Context Learning in Alzheimer's Disease

arXiv:2609.28836v1 Announce Type: cross Abstract: While various multimodal methods combining imaging and tabular data for Alzheimer's disease (AD) diagnosis were proposed, they are often limited in ge

safetyarxiv-cs-ai

Applications

M3GD: Multi-Modal Multi-View Geometric Diffusion for Camera--LiDAR Novel View Synthesis

arXiv:2609.30056v1 Announce Type: cross Abstract: Robotic novel view synthesis (NVS) must recover both visual appearance and metric 3D structure, yet most generative NVS methods rely only on images, o

applicationsarxiv-cs-cv

Machine Unlearning for Gibbs Supervised Learning Algorithms

arXiv:2609.29409v1 Announce Type: cross Abstract: In this paper, a method for achieving exact unlearning for Gibbs supervised learning algorithms is proposed using a variational formulation inspired b

Agents

Markerless Multi-Modal Autonomous Robotic Inspection of Large Space Structures

arXiv:2609.29644v1 Announce Type: new Abstract: Future orbital infrastructures, such as deployable antennas, solar farms, and large orbital platforms will require autonomous inspection systems able to

agentsarxiv-cs-ro

Hardware

Match4Annotate: Cross-Video Annotation Transfer in Ultrasound via Implicit Feature Flow-Guided Matching

arXiv:2603.06471v3 Announce Type: replace Abstract: Acquiring per-frame annotations for ultrasound videos is costly and requires clinical expertise, limiting learning-based analysis. We study cross-vi

hardwarearxiv-cs-cv

Matrix Aggregation Operators

arXiv:2609.28562v1 Announce Type: cross Abstract: Aggregation theory has traditionally focused on operators defined over vectors. However, many applications-including Multi-Criteria Decision Making, G

MDE-VIO: Enhancing Visual-Inertial Odometry Using Learned Depth Priors

arXiv:2602.11323v2 Announce Type: replace Abstract: Traditional monocular Visual-Inertial Odometry (VIO) systems struggle in low-texture environments where sparse visual features are insufficient for

Med-AR: Autoregressive Vision-Language Pretraining for Long-Tailed Chest X-Ray Classification and Uncertainty-Aware Evaluation

arXiv:2609.29156v1 Announce Type: cross Abstract: Long-tailed chest X-ray classification requires visual representations that capture both common abnormalities and subtle, infrequent findings. We prop

researcharxiv-cs-ai

MemGuard-Alpha: Limits of Membership Inference for Detecting and Filtering Memorization-Contaminated Signals in LLM-Based Financial Forecasting

arXiv:2603.26797v2 Announce Type: replace Abstract: Large language models are increasingly used to generate financial alpha signals, but many have memorized the historical data in their training corpo

MeshHeal: Two-Timescale Self-Healing for Gray Failures in Decentralized LLM Agent Networks

arXiv:2609.29015v1 Announce Type: new Abstract: Decentralized LLM-based multi-agent systems coordinate through local interactions, but an agent can remain responsive while its task-solving quality per

local-aiarxiv-cs-ai

MEVL-STP: Multi-Encoder and Vision Language Model for Arbitrarily Shaped Scene Text Spotting

arXiv:2609.28857v1 Announce Type: new Abstract: Scene text spotting remains challenging for arbitrarily shaped text instances such as curved signs and dense multi-oriented characters in natural images

local-aiarxiv-cs-cv

MF-SCBO : Multi-fidelity Scalable Constrained Bayesian Optimization

arXiv:2609.29941v1 Announce Type: new Abstract: Many real-world optimization problems rely on expensive simulations or experiments, making the efficient use of available data essential. Multi-fidelity

MILO: Efficient Many-shot In-Context Learning with Block-wise Low-rank Compression

arXiv:2609.29913v1 Announce Type: new Abstract: Many-shot in-context learning (ICL) enables large language models (LLMs) to adapt to complex tasks by conditioning on thousands of demonstration example

local-aiarxiv-cs-cl

Mind the Gap: Mesh-Guided Repair of Broken Vessels

arXiv:2609.29779v1 Announce Type: new Abstract: Vessel segmentation is commonly optimized as voxel-wise classification, but small local errors can strongly disrupt vascular connectivity while having l

Mind What Matters for Reasoning: Aligning Cross-Modal Attention via Selective Probability Mass Concentration

arXiv:2609.29940v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) achieve strong performance on visual reasoning tasks, yet remain prone to hallucinations and over-reliance on

Minimally Invasive Steering of Language Models

arXiv:2609.30218v1 Announce Type: cross Abstract: Pre-logit steering adapts a frozen language model to a test-time reward by adding vectors to its final hidden states. Unregularized reward optimizatio

local-aiarxiv-cs-ai

MLPerf Automotive

arXiv:2510.27065v2 Announce Type: replace Abstract: We present MLPerf Automotive, the first standardized public performance benchmark for evaluating Machine Learning systems that are deployed for AI a

Modeling Load-, Velocity-, and Temperature-Dependent Transmission Errors of Cycloidal Drives for Industrial Robots Using Fourier Series

arXiv:2609.29112v1 Announce Type: new Abstract: Industrial robots are rarely used for machining tasks due to their limited path accuracy. This accuracy is mainly limited by inaccuracies in the drive t

researcharxiv-cs-ro

Modelling dynamic systems transfer functions from events in computational neuromorphic imaging

arXiv:2609.29863v1 Announce Type: new Abstract: Event Vision Sensing (EVS) report threshold crossings of log-irradiance, so a static optical system imaging a static scene produces no output at all. Th

ModularSQL: A Runtime Guardrail for the Multiplicity Blind Spot in Text-to-SQL

model-releasesarxiv-cs-cl

arXiv:2609.29573v1 Announce Type: new Abstract: Text-to-SQL systems are increasingly deployed on production databases, where queries that pass benchmark evaluation can still produce results that disto

Monitoring Urban Traffic Dynamics at Fine Spatiotemporal Resolution Using Distributed Acoustic Sensing and Deep Learning

arXiv:2609.28793v1 Announce Type: new Abstract: Mapping the distribution of traffic dynamics at high spatiotemporal resolution is a fundamental question in transportation research. Distributed acousti

MOOSEnger: A Simulation-Aware AI Agent Framework for the MOOSE Ecosystem

arXiv:2603.04756v3 Announce Type: replace Abstract: MOOSEnger is a modeling and simulation AI agent framework for the Multiphysics Object-Oriented Simulation Environment (MOOSE) ecosystem, built aroun

MORE-PLR: multi-output regression employed for partial label ranking

arXiv:2609.29386v1 Announce Type: new Abstract: The partial label ranking problem is a supervised learning scenario that aims to fit a preference model that predicts a bucket order defined over a set

Tutorials

MorphIK: Morphology-Conditioned Neural Inverse Kinematics for Unknown Robots

arXiv:2609.29908v1 Announce Type: cross Abstract: Neural models can learn to generate various solutions to the inverse kinematics problem from data, but are usually limited to a single robot. We prese

tutorialsarxiv-cs-ai

Morphometric Imitation: From Morphology and Contact Aware Hand Retargeting to Sim-to-Real Visuomotor Policy

arXiv:2609.28660v1 Announce Type: new Abstract: Human hand-object interactions (HOIs) provide a rich source of demonstrations for dexterous manipulation, but learning directly from them presents chall

safetyarxiv-cs-ro

MoSign: Challenge-Response Motion-Watermark Authentication for Anonymous Virtual-Reality Users

arXiv:2609.29603v1 Announce Type: cross Abstract: Social virtual reality (VR) creates a paradox. A user's body motion is a high-entropy biometric: head and hand trajectories alone re-identify users am