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Arbitrary Cipher Attacks Against Large Language Models Do Not Require Fine-Tuning

arXiv:2609.09553v1 Announce Type: cross Abstract: Large language model safety and security research is preoccupied with, among other things, detecting and preventing jailbreak attacks: alignment bypas

safetyarxiv-cs-ai

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Are We Really Doing Few-Shot Learning? A Critical Examination of Pre-Training Assumptions

DGX agent

arXiv:2609.10851v1 Announce Type: new Abstract: Few-shot learning is commonly evaluated under protocols that pre-train a model on a large auxiliary set whose classes are disjoint from the target episo

safetyarxiv-cs-cv

11 Sept 2026

Artificial Intelligence Algorithms for the Detection of Pathologies Related to Lung Cancer through Image Analysis using Convolutional Neural Networks and Data Augmentation: a systematic mapping of the literature

arXiv:2609.10652v1 Announce Type: cross Abstract: Lung cancer is one of the leading causes of death worldwide, and its early diagnosis is crucial to improving patients prognosis and quality of life. H

Assessing the Reusability of Public Speech Resources for Low-Resource Languages: A Central Kurdish Case Study

arXiv:2609.11246v1 Announce Type: new Abstract: Kurdish is spoken by millions of people, but little technology can read it aloud. A recent study released three Kurdish voices, 35 hours of recorded spe

AUC Maximization from Biased Positive-unlabeled Data with Confidence

arXiv:2609.10928v1 Announce Type: new Abstract: Maximizing the area under the receiver operating characteristic curve (AUC) is a standard approach to imbalanced binary classification. Although positiv

safetyarxiv-cs-lg

Augustinian BabyLM: What Ostensive Definition Can and Cannot Teach a Small Language Model

arXiv:2609.11870v1 Announce Type: new Abstract: A language model normally begins training with random word embeddings: whatever 'banana' means must be learned from training corpora. I implement St. Au

Hardware

Auto-RecSys: Harnessing Autonomous Research Agents for Industry-Scale Recommender System

arXiv:2609.10922v1 Announce Type: new Abstract: Auto-research agents have shown the potential to automate hypothesis generation, experiment execution, and iterative refinement. However, scaling this p

hardwarearxiv-cs-cl

Automated Identification of Competing Narratives in Political Discourse on Social Media

arXiv:2609.11202v1 Announce Type: new Abstract: Social media platforms have become central to shaping political discourse, serving as arenas where narratives form and evolve, influencing public opinio

Automated multi-class wound assessment using dedicated instance segmentation models for boundary detection and classification

arXiv:2603.27325v2 Announce Type: replace Abstract: Accurate wound classification (WC) and boundary segmentation are essential for guiding clinical decisions in chronic and acute wound management. How

researcharxiv-cs-cv

Automatic Lyric Transcription for Greek Songs: Scaling and Task Composition Effects in Whisper Adaptation

arXiv:2609.11302v1 Announce Type: new Abstract: Automatic Lyric Transcription (ALT) remains substantially more challenging than speech recognition due to melodic variability, rhythmic irregularity, an

Autonomous-Flow-Based Generation

arXiv:2511.09902v3 Announce Type: replace Abstract: We show that using autonomous-flow-based generation, one can universally approximate orientation-preserving diffeomorphisms defined on the cube by N

agentsarxiv-cs-lg

Applications

Bayesian quantum sensing using graybox machine learning

arXiv:2601.17465v2 Announce Type: replace-cross Abstract: Quantum sensors offer significant advantages over classical devices in spatial resolution and sensitivity, enabling transformative application

applicationsarxiv-cs-lg

Applications

Beyond Benchmarks: Using VLMs to Reveal Systematic Classification Failures Under Real World Conditions

arXiv:2609.11126v1 Announce Type: new Abstract: Verification and validation (V&V) of classification models is crucial to enable a wide range of sensor processing applications. Currently, the V&V proce

applicationsarxiv-cs-cv

Beyond Noise Steering: Dual-Latent Space Reinforcement Learning for Generative Robot Policy

arXiv:2609.11270v1 Announce Type: new Abstract: Pretrained generative robot policies learn expressive action priors from demonstrations. However, existing reinforcement learning methods only steer the

safetyarxiv-cs-ro

Beyond Prompting: Efficient and Robust Contextual Biasing for Speech LLMs via Logit-Space Integration (LOGIC)

arXiv:2601.15397v3 Announce Type: replace-cross Abstract: The rapid emergence of new entities -- driven by cultural shifts, evolving trends, and personalized user data -- poses a significant challenge

Beyond Solver Verdicts: Generative Reward Models for Autoformalization

arXiv:2609.11085v1 Announce Type: cross Abstract: Neurosymbolic systems rely on mathematical solvers to guarantee reasoning correctness, yet solvers are fundamentally blind to whether a formal transla

agentsarxiv-cs-cl

Beyond Surface Imitation: Contrastive Modeling for Reasoning Path Alignment in Multimodal In-Context Learning

arXiv:2609.10177v1 Announce Type: new Abstract: In-context learning (ICL) is widely used in multimodal large language models (MLLMs) and achieves strong performance across a wide range of multimodal t

safetyarxiv-cs-ai

Beyond Training: A Feasibility Taxonomy for Inference-Time AI Governance

arXiv:2609.10105v1 Announce Type: cross Abstract: Compute governance today is a governance of training: the thresholds, reporting requirements, and frontier-AI regimes now in force attach to training

agentsarxiv-cs-ai

Beyond Visual Quality: Evaluating Physical Consistency under Ego-Motion with EgoGenEval

arXiv:2609.11172v1 Announce Type: new Abstract: Recent visual generators produce high-fidelity images yet often violate physical consistency under ego-motion, limiting their use for spatial reasoning

Beyond Word Error Rate: A Switch Aware Evaluation of ASR and Audio Language Models on English Yoruba Code-Switched Speech

arXiv:2609.11786v1 Announce Type: new Abstract: Automatic speech recognition (ASR) systems and audio language models (audio LMs) now report low error rates on monolingual benchmarks, but their behavio

local-aiarxiv-cs-cl

Bidirectional Multimodal Fusion of Sky Images and Time-Series for Solar Forecasting with Large Language Models

arXiv:2609.11135v1 Announce Type: new Abstract: Short-term photovoltaic (PV) power and global horizontal irradiance (GHI) forecasts are essential for effective dispatch, reserve scheduling, and grid o

local-aiarxiv-cs-lg

BiHDTrans: binary hyperdimensional transformer for efficient multivariate time series classification

arXiv:2509.24425v2 Announce Type: replace Abstract: The proliferation of Internet-of-Things (IoT) devices has led to an unprecedented volume of multivariate time series (MTS) data, requiring efficient

researcharxiv-cs-lg

Tutorials

Bio-inspired Learning and Decision-Making with Probabilistic In-Memory Computing Hardware: Part 1

arXiv:2609.11281v1 Announce Type: cross Abstract: Learning and decision-making in animals are often modeled as Bayesian processes, where sensory evidence is integrated with prior beliefs to guide beha

tutorialsarxiv-cs-lg

Biology-in-the-loop: Amortized Adaptive Hit Discovery in CRISPR Screens

arXiv:2609.11877v1 Announce Type: cross Abstract: Many biological discovery problems require experiments to be selected sequentially under constrained budgets. CRISPR screening is a prominent example,

Black-Box Membership Inference via Word-Level Probability Estimation

arXiv:2609.10611v1 Announce Type: cross Abstract: Membership inference attacks (MIAs) have emerged as critical tools for auditing privacy risks in large language models (LLMs), aiming to determine whe

Black-Box Red Teaming of Agentic AI: A Taxonomy-Driven Framework for Automated Risk Discovery

arXiv:2609.09647v1 Announce Type: new Abstract: Agentic systems are rapidly moving to production, where they read untrusted inputs, call tools with real permissions, and act autonomously, expanding th

agentsarxiv-cs-ai

BodyCam-VQA: Enhanced Body-Worn Camera Video Captioning via Multimodal Reasoning and Probe Question Generation

arXiv:2609.10815v1 Announce Type: cross Abstract: Police body-worn camera (BWC) footage has emerged as a critical aspect of law enforcement that ensures legal transparency, officer accountability, and

safetyarxiv-cs-cl

Brain-PACE: A Deep Siamese MRI Framework for Modelling Longitudinal Brain Acceleration

arXiv:2609.11378v1 Announce Type: new Abstract: Brain age estimation has become a popular research proxy for assessing brain health and disease, yet longitudinal trajectories of brain ageing are still

safetyarxiv-cs-cv

Breaking the Central Bias: Spatially Partitioned Experts for Coordinate-Based Neuroevolution

arXiv:2609.11518v1 Announce Type: cross Abstract: Evolvable-Substrate HyperNEAT (ES-HyperNEAT), a bio-inspired indirect encoding that determines neuron placement and connection weights from spatial co

BridgeMatch: Conditional Transport Bridges in Matching Matrix Space for 3D Deformable Registration

arXiv:2609.11472v1 Announce Type: new Abstract: Reliable non-rigid point cloud correspondences are important for deformable anatomical registration, embodied perception and manipulation, and dynamic 3

researcharxiv-cs-cv

BruNet: A Cross-Domain Transfer Framework for Bruise Segmentation

arXiv:2609.11463v1 Announce Type: new Abstract: Segmenting bruises is a challenging task in medical imaging due to limited data and annotations, diffuse boundaries, and highly variable appearance. In

local-aiarxiv-cs-cv

Hardware

Building py-kvcache: A Performance Characterization of External KV Caching for vLLM with NVMe SSDs

arXiv:2609.11744v1 Announce Type: cross Abstract: Prefix caching can reduce the time to first token (TTFT) of long-context LLM requests by reusing previously computed key-value (KV) states, but for sh

hardwarearxiv-cs-lg

Building Supervision into Hebbian Plasticity through Spike Agreement

arXiv:2601.08526v2 Announce Type: replace-cross Abstract: Supervised learning in spiking neural networks (SNNs) typically requires either gradient-based backpropagation, which sacrifices the Hebbian,

Byzantine-Robust Federated Fire Detection with a Rotating Coordinator

arXiv:2609.10647v1 Announce Type: new Abstract: We study the application of federated learning (FL) to indoor fire detection. Such fire-detection systems use edge cameras that record sensitive footage

researcharxiv-cs-lg

CamPilot: A Multi-Agent Cinematic Assistant for Camera-Controlled Movie Generation

arXiv:2609.10943v1 Announce Type: new Abstract: The integration of large language models (LLMs) into video generation has enabled rapid text-to-video creation and improved visual quality. However, it

Can AI Agents Deliver Verifiable Network-Wide Outcomes Across Authority Boundaries?

arXiv:2609.10181v1 Announce Type: cross Abstract: AI agents are increasingly involved in network automation, where they can initiate configuration changes through mediated operational interfaces and a

agentsarxiv-cs-ai

Can AI Agents Detect and Repair Artifact Drift in Network Experiments?

model-releasesarxiv-cs-ai

arXiv:2609.09849v1 Announce Type: cross Abstract: In recent years, AI agents have evolved into capable assistants that carry out multi-step tasks in digital environments. The network systems community

Can LLMs Normalize Databases? A Benchmark and Multi-Agent Framework for Schema Normalization

arXiv:2609.11141v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to generate structured outputs, but their reliability remains unclear when those outputs must satisfy

CAP: Continuously Adaptive Perception-Blind Humanoid Locomotion via Learned Denoising

arXiv:2609.11553v1 Announce Type: new Abstract: Humanoid locomotion across complex terrain demands forward-looking exteroception to anticipate obstacles, yet this signal is unreliable in real-world de

safetyarxiv-cs-ro

Caption-once, Frames-on-Demand: Visual-Need Routing for Budget-Aware Agentic Long Video Understanding

arXiv:2609.11899v1 Announce Type: new Abstract: Long-video understanding on edge devices must reason over hours of content under tight compute and bandwidth budgets. Subsampling visual tokens loses te

agentsarxiv-cs-cv

CARLAverse: A Highly Modular, Distributed, and Multimodal Framework for Human-in-the-Loop Simulation

arXiv:2609.11478v1 Announce Type: new Abstract: The development of autonomous driving demands comprehensive testing in mixed-traffic scenarios involving vulnerable road users (VRUs), where purely arti

agentsarxiv-cs-ro

CARTS: Contextual Autoregressive Rank Transcoding Steganography for Full-Capacity Keyed Text Encoding

arXiv:2609.10744v1 Announce Type: cross Abstract: Autoregressive language models can be used to transform a payload text into a stegotext of identical token length by preserving per-position rank info

CausalArena: Benchmarking Causal Discovery in the Foundation Model Era

arXiv:2609.11897v1 Announce Type: new Abstract: Causal discovery aims to uncover causal structures from data and is fundamental to scientific reasoning and intervention-based decision making. Its eval

CEM-TUDASR: Computationally efficient multi-modality transformer based unsupervised domain adaptive super-resolution approach

arXiv:2609.11201v1 Announce Type: new Abstract: Wireless Capsule Endoscopy (WCE) enables non-invasive visualization of the gastrointestinal tract, but its miniaturized optics, sensor limitations, and

local-aiarxiv-cs-cv

CertDW: Towards Certified Dataset Ownership Verification via Conformal Calibration

arXiv:2506.13160v2 Announce Type: replace-cross Abstract: Deep neural networks (DNNs) rely heavily on high-quality open-source datasets (e.g., ImageNet) for their success, making dataset ownership ver

Certifying Lower Bounds for Risk-Sensitive Reinforcement Learning under Adversarial State Perturbations

arXiv:2609.10866v1 Announce Type: new Abstract: Reinforcement learning (RL) agents deployed in real-world environments are often vulnerable to adversarial perturbations in state observations, creating

Characterizing Narrative Content in Web-scale LLM Pretraining Data

arXiv:2606.19468v2 Announce Type: replace Abstract: The narrative composition of web-scale LLM pretraining corpora remains largely unexplored, even though narrative is a fundamental mode of human comm

CHRONOBERG: Capturing Language Evolution and Temporal Awareness in Foundation Models

arXiv:2509.22360v2 Announce Type: replace Abstract: Large language models (LLMs) excel at operating at scale by leveraging social media and various data crawled from the web. Whereas existing corpora