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arXiv:2609.17653v1 Announce Type: cross Abstract: GUI agents execute long-horizon tasks on dynamic graphical user interfaces, where pop-ups, delayed loads, and relocated widgets routinely invalidate p

agentsarxiv-cs-ai

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Reflections on Trusting Trust, Revisited: Contaminating Self-Modifying AI Coding Agents with Poisoned Benchmarks

DGX agent

arXiv:2609.17817v1 Announce Type: cross Abstract: Thompson's 'Reflections on Trusting Trust' showed that a compiler can be poisoned to reinsert its own backdoor, so that even recompiling clean source

model-releasesarxiv-cs-ai

17 Sept 2026

Regional Explanations via Causal Sufficiency and Necessity

arXiv:2609.18049v1 Announce Type: new Abstract: Model explainability is essential for understanding and trusting machine learning models. Existing explainable AI methods often explain predictions thro

Register Bias in Complexity-Based Large Language Model Routing

arXiv:2609.17542v1 Announce Type: new Abstract: Large language model services increasingly route each query to one of several models of differing capability, using a cheap estimate of query complexity

Regularized Least Squares Training of Quadratic Neural Networks with Applications to System Identification

arXiv:2609.17654v1 Announce Type: new Abstract: This paper proposes a least squares approach for the training of quadratic neural networks with regularization. The proposed methodology yields a lower

Reinforcement Learning for Real-Time Vision-Language-Action Policies

model-releasesarxiv-cs-lg

arXiv:2609.18207v1 Announce Type: cross Abstract: Reinforcement learning fine-tuning on top of large, pretrained Vision-Language-Action (VLA) models offers promise for highly reliable robot deployment

Relation Before Entity: Deferred Commitment in Language Model Factual Recall

arXiv:2609.17537v1 Announce Type: new Abstract: We ask whether relation-type information (e.g., capital-of) and entity-specific information (e.g., France to Paris) become causally active at the final-

researcharxiv-cs-cl

Relationally Guided Use Case Modeling with LLMs

arXiv:2609.18291v1 Announce Type: cross Abstract: Use case flows are important elements of use case modeling because they support downstream software engineering activities, including requirements ana

researcharxiv-cs-cl

Reliable learning in challenging environments

arXiv:2304.03370v3 Announce Type: replace Abstract: The problem of designing learners that provide guarantees that their predictions are provably correct is of increasing importance in machine learnin

Reliable Virtual Sensing: A Multi-Domain Benchmark for Robustness Under Sensor Failures

arXiv:2609.18396v1 Announce Type: cross Abstract: Virtual sensing, the estimation of hard-to-measure quantities from available sensor measurements, is a critical enabler for control and monitoring in

Remembering Solomon Marcus

arXiv:2609.18224v1 Announce Type: cross Abstract: From the manifest of Andre Breton, through the transdisciplinary understanding, we arrive at a post-modern manifest. A talk by Laura De Marco (Harvard

Renyi Tracking Bounds for Langevin Dynamics with Moving Targets

arXiv:2609.17577v1 Announce Type: cross Abstract: We study Langevin diffusion and Langevin Monte Carlo (LMC) when the target distribution changes over time. Under a log-Sobolev inequality (LSI), we de

REPAIR: Resolving Long-Tail Confusion in Scientific Retrievers via Fact-Verified Iterative Refinement

arXiv:2609.18262v1 Announce Type: new Abstract: Precise retrieval of scientific information is fundamentally constrained by long-tailed concepts and high fact-sensitivity of scientific corpora. These

Reporting Practice Matters: The Impact of Reference Choice on Chest X-ray Report Evaluation

arXiv:2609.19093v1 Announce Type: cross Abstract: Radiologists follow heterogeneous reporting practices. Two radiologists examining the same image and identifying the same clinical findings might neve

REQAP: Resilient Weight Packing and Quantization for Edge DNN Acceleration

arXiv:2609.17555v1 Announce Type: cross Abstract: Efficient deployment of Deep Neural Networks (DNNs) on edge accelerators requires aggressive model compression while maintaining reliability in fault-

Local Ai

ReRadar: Robust Radar Global Localization via Rotation-Equivariant Descriptor Learning

arXiv:2609.18092v1 Announce Type: new Abstract: Global localization with scanning millimeter-wave radar remains challenging because place-recognition descriptors often discard spatial structure needed

local-aiarxiv-cs-ro

Rethinking Critic Learning in PPO: Understanding and Mitigating Value Flattening

arXiv:2609.18708v1 Announce Type: cross Abstract: In reinforcement learning for large language models, Proximal Policy Optimization (PPO) commonly uses a critic to estimate state values and reduce the

safetyarxiv-cs-ai

Rethinking Domain Specialization for Open-Ended Scientific Reasoning in Astronomy Language Models

arXiv:2609.17644v1 Announce Type: cross Abstract: Domain-specialized language models are widely used for scientific question answering, but stronger general-purpose systems raise a sharper question: w

Rethinking How We Evaluate Methodological Progress in Health AI

arXiv:2609.18134v1 Announce Type: cross Abstract: Methodological progress in artificial intelligence (AI) for electronic health records (EHRs) depends on our ability to determine which algorithms work

REVERSAL-BENCH: A Reversibility Axis and Reset Oracle for Measuring the Reset-Free RL Cliff

arXiv:2609.17745v1 Announce Type: cross Abstract: A central goal of autonomous reinforcement learning is continuous policy training without external resets. However, existing paradigms largely depend

Revisiting Distributed Sign-Based Variance Reduction

arXiv:2609.18656v1 Announce Type: new Abstract: Sign-based methods reduce communication costs in distributed environments, but aggregating local signs can introduce bias when data are heterogeneous. A

safetyarxiv-cs-lg

Applications

Revisiting the Objective of Echo Chamber Detection

arXiv:2609.18545v1 Announce Type: new Abstract: In this paper, we study the detection of an echo chamber in a social network, i.e., the identification of a set of nodes that agree on a topic, while di

applicationsarxiv-cs-lg

RideWay: Benchmarking Efficient Task Completion for Tool-Using Language Agents

arXiv:2609.17985v1 Announce Type: new Abstract: AI agents are usually evaluated by whether they complete a task. In interactive service settings, a successful agent can still frustrate users by asking

Hardware

Risk-Aware World Modeling with Flow-Guided Occupancy Evolution for Selective Trajectory Planning in Automated Driving

arXiv:2609.18442v1 Announce Type: new Abstract: Safe motion planning in automated driving requires anticipating evolving traffic risks and deciding when to revise the current planned trajectory. We in

hardwarearxiv-cs-ai

RLLBC-Lib: An Educational Code Library for Reinforcement Learning and Learning-Based Control

arXiv:2609.19074v1 Announce Type: cross Abstract: Reinforcement learning (RL) is an exciting concept as well as a remarkable success story worth sharing. However, RL builds on rather complex interacti

rMuscle: Robotic Muscle Memory for Efficient Vision-Language-Action Model Inference

arXiv:2609.19104v1 Announce Type: cross Abstract: Factory work is a promising early scenario for embodied AI: assigning repetitive manual jobs to robots has clear economic payoff, and a structured sta

safetyarxiv-cs-ai

RoboVAD: A Large Cross-Domain Evaluation Benchmark for Anomaly Detection in Robotic Arm Manipulation Videos

arXiv:2609.17843v1 Announce Type: cross Abstract: Video anomaly detection (VAD) is an actively studied task, having wide applications in typical scenarios such as public surveillance and road traffic

Robust and Efficient AI Frameworks for Scalable Material Design and Property Prediction

arXiv:2609.17646v1 Announce Type: cross Abstract: This thesis develops robust and efficient AI frameworks for accelerating crystalline materials discovery by addressing both major stages of the materi

Tutorials

Rollback the World, Keep the Reflection: Rollback-Induced Reflection for Long-Horizon LLM Agents

arXiv:2609.18304v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly tackle long-horizon tasks through multi-step environment interaction, yet a single erroneous action can a

tutorialsarxiv-cs-cl

Safety-Flag: A Unified Benchmark for the Reliability and Calibration of LLM Content Moderators

arXiv:2609.19072v1 Announce Type: new Abstract: Large language models are increasingly used for content moderation, but most evaluations still report aggregate accuracy on individual benchmarks. We in

Applications

SAGE: Governed Artifact Generation from Enterprise Guidelines

arXiv:2609.17775v1 Announce Type: new Abstract: Enterprise guideline documents mix narrative text, complex tables, and embedded images, and converting them into structured work artifacts still takes t

applicationsarxiv-cs-ai

SAiFE-gym: Model-based Environments for Automated Market Making with Concentrated Liquidity

arXiv:2609.17788v1 Announce Type: cross Abstract: We present SAiFE_gym, a Python module that provides a collection of simulation environments for studying trading problems in Constant Product Markets

SAM-on-the-Curve: Sharpness-Aware Mode Connectivity for Robust Weight-Space Interpolation

arXiv:2609.17748v1 Announce Type: new Abstract: Deep neural networks that are independently trained to similar performance can be connected by low-loss parametric curves in weight space, a phenomenon

Scalable Music Cover Retrieval Using Lyrics-Aligned Audio Embeddings

arXiv:2601.11262v2 Announce Type: replace-cross Abstract: Music Cover Retrieval, also known as Version Identification, aims to recognize distinct renditions of the same underlying musical work, a task

Applications

Scaling Articulated Rationales for MLLM-based Recommendation

arXiv:2609.17639v1 Announce Type: cross Abstract: Modern recommendation systems largely infer user preferences from implicit behaviors such as clicks, watch time, and negative feedback, but these sign

applicationsarxiv-cs-ai

Agents

ScienceIDE: Turning World's Scientific Codebase into Agent Learnable Environments

arXiv:2609.19134v1 Announce Type: new Abstract: Scientific code repositories encode decades of human knowledge in executable models, methods, and tools. Yet fragmented toolchains, implicit domain conv

agentsarxiv-cs-cl

SEA-LION-v4.8: A Technical Report

arXiv:2609.18310v1 Announce Type: new Abstract: We introduce Nemotron-SEA-LION-v4.8, a family of Southeast Asian Languages in One Network (SEA-LION) built upon NVIDIA Nemotron 3. The family includes 3

SEAM: Submap-Anchored Evidence for Lifelong LiDAR Mapping under Trajectory Deformation

arXiv:2609.18819v1 Announce Type: new Abstract: We propose SEAM, a LiDAR-based lifelong mapping framework. Instead of relying on a single anchor spanning the entire session, SEAM generates evidence ba

safetyarxiv-cs-ro

Securing quantum error correction against misleading advice from AI agents

arXiv:2609.19090v1 Announce Type: cross Abstract: Can an attacker turn influence over an artificial intelligence (AI) adviser into a harmful quantum error-correction update? We identify an ambiguity i

Local Ai

Selection Is Retrieval, Abstention Is Not: On-Device Tool Routing over 70 Korean-English Actions

arXiv:2609.18672v1 Announce Type: new Abstract: An AI assistant that calls tools makes two decisions on every request: which tool to invoke, and whether any available tool applies. In the usual design

local-aiarxiv-cs-cl

Selective Prediction and Uncertainty-Aware Referral for Pap Smear Classification

arXiv:2609.17545v1 Announce Type: new Abstract: Deep learning models for cervical cytology are almost always evaluated as if every prediction must be acted upon, yet a screening system deployed alongs

researcharxiv-cs-cv

Tutorials

Self-Supervised Learning for Robust Resonance Mass Regression in Cascade Decays

arXiv:2609.17726v1 Announce Type: cross Abstract: Reconstructing the mass of a heavy resonance from its decay products with missing energy is one of the central tasks that directly determine the sensi

tutorialsarxiv-cs-lg

Semantic CSI Feedback for Beam Selection: When Task-Aware Embeddings from Sparse Pilots Outperform Full-Bandwidth Reconstruction

arXiv:2609.18368v1 Announce Type: cross Abstract: Classical CSI feedback in FDD massive MIMO transmits a compressed reconstruction of the channel, optimizing fidelity to the original signal regardless

Semantic-ITC: A Frame-wise Indoor Mobile Laser Scanning Dataset and Benchmark for Semantic Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.18493v1 Announce Type: new Abstract: Semantic labels for indoor mobile laser scanning (MLS) frames remain largely absent from current point cloud semantic segmentation benchmarks, which mai

SetPlanner: A Lightweight Plug-in Point-Set Planner for Frozen SAM

model-releasesarxiv-cs-cv

arXiv:2609.18037v1 Announce Type: new Abstract: Segment Anything Models provide reusable priors, yet they require user prompts and cannot support fully automatic instrument segmentation. Automatic pro

SFT or RL for Tool-Calling Agents? A Controlled Study Across Data, Method, and Scale

arXiv:2609.17848v1 Announce Type: new Abstract: Limited controlled evidence exists on how training data, adaptation method, and model scale jointly affect tool-calling performance in language-model ag

Sharp margin-based generalization bounds for realizable SVM

arXiv:2609.17845v1 Announce Type: cross Abstract: Let the exact homogeneous hard-margin support vector machine be trained on (m) independent observations from a Borel probability law on a real Hilbert

ShotFinder: Imagination-Driven Open-Domain Video Shot Retrieval via Web Search

arXiv:2601.23232v4 Announce Type: replace-cross Abstract: In recent years, large language models (LLMs) have made rapid progress in information retrieval, yet existing research has mainly focused on t