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Assessing Adversarial Robustness of Latent Reasoning Models

arXiv:2609.22228v1 Announce Type: new Abstract: Large language models increasingly rely on long chain-of-thought (CoT) trajectories for complex reasoning, but autoregressive generation brings substant

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Assessing Readability with LLMs: The Role of Reasoning and Few-Shot Prompting

DGX agent

arXiv:2609.24650v1 Announce Type: new Abstract: Readability assessment is essential for tailoring texts to intended audiences across educational, healthcare, and information retrieval domains. However

model-releasesarxiv-cs-cl

22 Sept 2026

Attack-Resistant Uniform Fairness for Linear and Smooth Contextual Bandits

arXiv:2602.04125v2 Announce Type: replace-cross Abstract: Modern digital platforms use contextual bandits to allocate valuable exposure and opportunities among competing participants. Fair treatment i

Attention-Enhanced Dual-Branch ConvNeXt-BiLSTM Network for Subject-Independent EEG Seizure Detection

arXiv:2609.22141v1 Announce Type: cross Abstract: Automated seizure detection from scalp electroencephalography (EEG) is difficult because seizure morphology varies among patients and seizure samples

researcharxiv-cs-lg

Attributable Post-Rationalization in RAG Citations: A Controlled Reproduction and an RLVR Comparison

arXiv:2609.23053v1 Announce Type: new Abstract: A RAG system can hand you the right answer and cite a source it did not actually use. Models output these unfaithful citations via post-rationalization:

Audio-based UAV Localization with Adaptive Temporal Correspondence via Reinforcement Learning

arXiv:2609.24218v1 Announce Type: new Abstract: Audio-based localization provides a low-cost and illumination-independent sensing solution for anti-UAV early warning. However, existing methods typical

researcharxiv-cs-ro

Auditing Bayesian Graph Alignment: Diagnostic Comparisons and Reference Failure

arXiv:2609.23232v1 Announce Type: cross Abstract: Bayesian graph alignment estimates correspondence probabilities, but convergence of an alignment-score trace need not imply accurate correspondence ma

Auditing Political Alignment in LLM Assistants: Engagement, Stance, and User Identity

arXiv:2609.23039v1 Announce Type: new Abstract: LLM-based AI systems answer political questions for hundreds of millions of people. Current audits measure what they say to an average user, but their b

Applications

Augmented Hypothesis Testing with Persona-Based LLM Simulations

arXiv:2609.24629v1 Announce Type: new Abstract: A/B testing requires large sample sizes, long timelines, and significant costs. When auxiliary predictions of experimental outcomes are available from m

applicationsarxiv-cs-lg

Augmenting PID Control with Deep Reinforcement Learning: A Hybrid Approach to the Industrial Benchmark

arXiv:2609.22584v1 Announce Type: new Abstract: As industrial processes grow in complexity, traditional Proportional-Integral-Derivative (PID) controllers are often insufficient for handling their non

AURA: Uncertainty-Routed Activation Editing for Acoustic Grounding in Speech Foundation Models

arXiv:2609.23979v1 Announce Type: cross Abstract: Attention encoder-decoder (AED) Speech Foundation Models achieve strong ASR performance but can generate acoustically unsupported text when inputs con

Authority-Preserving Evaluation of Medical Vision-Language Assistants

arXiv:2609.22302v1 Announce Type: new Abstract: Medical vision-language models can propose how urgently a skin lesion should be reviewed, but the local service retains authority to accept or replace t

Tutorials

Authorship identification under domain shift: a survey of stylistic measures and learned author representations

arXiv:2310.00436v2 Announce Type: replace Abstract: Authorship identification uses patterns in writing to infer who wrote a text, but those patterns also reflect topic, genre, and register. This surve

tutorialsarxiv-cs-cl

Agents

AutoGym: Blueprint-First Generation of Verifiable Agent Gyms

arXiv:2609.22592v1 Announce Type: cross Abstract: Training agents with reinforcement learning requires a gym, comprising a task, an executable environment in which the task can be attempted, and a ver

agentsarxiv-cs-lg

Automatic Labelling for Bimanual Mobile Manipulation

arXiv:2609.24059v1 Announce Type: new Abstract: Semantically meaningful subtask labels can provide useful contexts for long-horizon policies, but automatically identifying both reliable temporal bound

researcharxiv-cs-ro

Agents

Automatic multimodal UX improvement recommendations from LLM agent user simulations

arXiv:2609.22971v1 Announce Type: new Abstract: Evaluating user experience (UX) on live websites through user testing is expensive, subjective, and difficult to scale. LLM agents offer a promising rou

agentsarxiv-cs-cl

Autonomous Model Lifecycle Management for Digital Twin-Based Manufacturing Control

arXiv:2609.22701v1 Announce Type: new Abstract: Manufacturing AI systems must autonomously adapt to continuous distributional shift from raw-material variability, ambient changes, and equipment aging,

AVTR-1: Open Stack for Real-Time Interactive Avatars

arXiv:2609.22913v1 Announce Type: new Abstract: Talking-head and dyadic models now achieve real-time inference, yet fast motion generation alone does not produce an interactive conversation. A live sy

AWR-Net: Decoupling Anatomy and Appearance for 3D Fetal Brain Ultrasound Synthesis

arXiv:2609.22635v1 Announce Type: cross Abstract: Three-dimensional fetal brain ultrasound offers non-ionizing, cost-effective imaging with rich spatial information for comprehensive anatomical assess

researcharxiv-cs-cv

BabelArena: A Large-Scale Multilingual Benchmark for LLM Agents

arXiv:2609.23490v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly execute multi-step workflows through tool use and interaction with users and environments. However, curre

BackdoorVLM: A Benchmark for Backdoor Attacks and Defenses on Vision-Language Models

arXiv:2511.18921v2 Announce Type: replace Abstract: Backdoor attacks undermine the reliability and trustworthiness of machine learning systems by injecting hidden behaviors that can be maliciously act

BadWAM: When World-Action Models Dream Right but Act Wrong

arXiv:2607.15207v2 Announce Type: replace Abstract: World-action models (WAMs) are emerging as a promising foundation for embodied control: rather than predicting actions alone, they learn representat

Balancing Reasoning and Hardware Constraints in RAG Pipelines for Ukrainian Multi-Domain Document Understanding

arXiv:2609.22124v1 Announce Type: new Abstract: This paper describes the system submitted to the UNLP 2026 Shared Task on Multi-Domain Document Understanding. The challenge required extracting precise

Barrier Certificate Synthesis for Non-Polynomial Robotic Dynamics via Polynomial Lifting

arXiv:2609.22885v1 Announce Type: new Abstract: Safe operation of robotic systems requires trajectories to remain within a prescribed safe set under admissible control inputs. Barrier certificates pro

safetyarxiv-cs-ro

Local Ai

BarrierFormer: Transformer-Guided Predictive Barrier Enforcement for Safe Robot Control

arXiv:2609.23896v1 Announce Type: new Abstract: Control barrier functions (CBFs) have become one of the most popular tools for encoding and enforcing state constraints in safety-critical robotics. Sta

local-aiarxiv-cs-ro

Tutorials

Bayesian Deck-of-cards-based Ordinal Regression with Sequential Preference Elicitation

arXiv:2609.23212v1 Announce Type: cross Abstract: The Deck-of-cards-based Ordinal Regression (DOR) infers a value function from a ranking of reference alternatives in which the Decision Maker (DM) ins

tutorialsarxiv-cs-lg

Bayesian Filtering in Physical Systems via Test-time Trained Flow Matching

arXiv:2609.23383v1 Announce Type: cross Abstract: Bayesian filtering provides a principled framework for online state estimation under uncertainty, yet its application to systems with high-dimensional

Applications

BayesianGS-SLAM: Uncertainty-Aware Neural Rendering SLAM via Probabilistic Formulation

arXiv:2609.24140v1 Announce Type: new Abstract: Neural-rendering-based SLAM relies on rendered RGB-D residuals for camera tracking and map optimization, but the reliability of these predictions can va

applicationsarxiv-cs-ro

BEACON: Belief-Enabled Adaptive CONtrol for Imitation Learning under Uncertainty

arXiv:2609.22730v1 Announce Type: new Abstract: Robot manipulation tasks often involve hidden state information that cannot be directly observed and must be inferred through sequential physical intera

safetyarxiv-cs-ro

Hardware

Becoming a Fruit Ninja: Real-Time Probabilistic Kinodynamic Planning for Manipulator Projectile Interception

arXiv:2609.22608v1 Announce Type: new Abstract: Projectile interception is a challenging dynamic manipulation problem. Intercepting a thrown object with a robot arm requires reaching a point on the ob

hardwarearxiv-cs-ro

Beetle: A Bilingual Model Suite for Modelling Second-Language Processing

arXiv:2609.22633v1 Announce Type: new Abstract: Bilingual language models (LMs) offer a controlled setting for studying how training conditions shape second-language (L2) behaviour, but prior work typ

safetyarxiv-cs-cl

Applications

Behavior Trees for Robotic Systems: An Empirical Study on Practices and Experiences

arXiv:2609.22404v1 Announce Type: new Abstract: Over the last decade, behavior trees (BT) have become one of the dominant behavior models for coordinating missions of robotic systems. Yet empirical ev

applicationsarxiv-cs-ro

Belted Engression: Sufficient Dimension Reduction for Generative Distributional Regression

arXiv:2609.23789v1 Announce Type: new Abstract: Modern conditional generative models face significant challenges when learning complex covariate dependencies. While sufficient dimension reduction (SDR

Tutorials

Benchmarking Hybrid Deep Learning Architectures for Predictive Maintenance in Industry 4.0

arXiv:2609.22583v1 Announce Type: new Abstract: Predictive maintenance in Industry 4.0 refers to using data from sensors, machines, and production systems to estimate when equipment is likely to fail,

tutorialsarxiv-cs-lg

Benchmarking Off-the-Shelf Multimodal AI Models Against Dermatologists on Patient-Captured Skin Images

arXiv:2609.24190v1 Announce Type: new Abstract: Artificial intelligence (AI) has advanced at a rapid pace in recent years. Initially, breakthroughs in large language models caught widespread attention

Beyond Accuracy and Surface Fluency: Risk-Sensitive Evaluation of LLMs for Legal Clause Generation

arXiv:2609.22127v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to draft contractual language, yet conventional accuracy or preference-based evaluations are poorly m

Beyond Appearance Shifts: Task-Semantic Action Calibration for VLA Models

arXiv:2609.23650v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have achieved strong performance in embodied manipulation, but still lack a clear mechanism to balance behavioral

Beyond Average Error through Oracle-Informed Stress Tests for Time-Series Forecasting

arXiv:2609.22820v1 Announce Type: new Abstract: Average squared error cannot reveal whether forecasting performance degrades because the future becomes less predictable or because forecasts move farth

Beyond Emotion Prompts: Fine-Grained Text-to-Image Generation Driven by Valence-Arousal-Dominance

arXiv:2609.24215v1 Announce Type: new Abstract: Although text-to-image models can accurately depict subjects and scenes, creators still struggle to specify the fine-grained emotions an image should co

safetyarxiv-cs-cv

Beyond Final-Token Classification: Heterogeneous Readouts for Evidence-Grounded Suicide Risk Detection

arXiv:2609.22767v1 Announce Type: new Abstract: The IEEE BigData Cup benchmark combines three prediction problems with different output structures: ordinal suicide-risk classification, multi-label psy

Local Ai

Beyond Linear Context: Graph-Guided Evidence Navigation for Long-Novel Reasoning with a Local 9B Language Model

arXiv:2609.22939v1 Announce Type: cross Abstract: Long-context models read a novel the way a person reads a printout: one token after another, in narrative order, with the whole history competing for

local-aiarxiv-cs-cl

Beyond Point Prediction: Artificial Representative Trees with Uncertainty

arXiv:2609.24528v1 Announce Type: cross Abstract: Random forests (RFs) predict well but are opaque, whereas single decision trees are interpretable but unstable. Artificial representative trees (ARTs)

Local Ai

Beyond Raw Context Transfer: Representation-based Federated Retrieval-Augmented Generation

arXiv:2609.22162v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves the factuality of large language models (LLMs) and vision-language models (VLMs) by grounding generation i

local-aiarxiv-cs-cl

Beyond Relevance: Structured Semantic Supervision for Product Search with LLM-Augmented Annotations

arXiv:2609.23646v1 Announce Type: cross Abstract: E-commerce search requires distinguishing products that are merely related to a query from those that directly satisfy the user's shopping intent. We

Beyond Similarity: Coverage-Aware Prompt Selection for Time Series Forecasting with LLMs

arXiv:2609.22977v1 Announce Type: cross Abstract: Similarity-based retrieval is the dominant rule for conditioning large language models (LLMs) in in-context learning, retrieval-augmented generation,

Agents

Beyond Single-Model Injection: A Threat Model and Defense Architecture for Prompt Injection in Multi-Agent Systems

arXiv:2609.22949v1 Announce Type: cross Abstract: Existing prompt injection research focuses on single-model chatbot scenarios, where an attacker manipulates one LLM through crafted input. Multi-agent

agentsarxiv-cs-cl

Beyond Task Completion: Training Capable and Safe Computer-Use Agents

arXiv:2609.22178v1 Announce Type: cross Abstract: Computer-use agents (CUAs) have made rapid progress in completing complex tasks through graphical user interfaces, yet post-training centered on task

safetyarxiv-cs-cl

Beyond the Leaderboard: Counterfactual Diagnosis of End-to-End and VLA Driving Policies Under Domain Shift

arXiv:2609.22582v1 Announce Type: new Abstract: End-to-end and vision-language-action (VLA) driving policies are compared by leaderboard rank, but a rank reports an outcome, not the behaviour behind i