Search: “concepts”

The Limits of BPE Tokenization in Polish: Segmentation-Flexional Forms, Grammatical Anchoring, and First-Person Stability in Inflectional Language Models

arXiv:2609.17553v1 Announce Type: new Abstract: This article analyzes BPE tokenization in Polish as a test case for the limits of statistical segmentation in an inflectional language. It asks whether

researcharxiv-cs-cl

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Think Before You Move: Latent Motion Reasoning for Text-to-Motion Generation

DGX agent

arXiv:2512.24100v2 Announce Type: replace Abstract: Current state-of-the-art paradigms predominantly treat Text-to-Motion (T2M) generation as a direct translation problem, mapping symbolic language di

safetyarxiv-cs-cv

17 Sept 2026

Using OCR Heads to Verbalize Image Semantics

arXiv:2609.18823v1 Announce Type: cross Abstract: How do VLMs map from pixels to semantics? To understand this general question, we focus on a narrow one: studying how VLMs perform optical character r

Visual Input and Its Framing Affect Attribute-based Descriptions Produced by Large Vision-Language Models

arXiv:2609.18345v1 Announce Type: new Abstract: Large vision-language models (LVLMs) are commonly used with only a single text prompt as the input, or plus an image. In this paper, we demonstrate that

researcharxiv-cs-cv

Tutorials

Vocabulary-Guided Gait Recognition

arXiv:2609.18413v1 Announce Type: new Abstract: What is a gait? Appearance-based gait networks consider a gait as the human shape and motion information from images. Model-based gait networks treat a

tutorialsarxiv-cs-cv

Who Audits Whom, on What Substrate, with What Evidence? An Independence-Graded Audit Protocol for Agentic AI

arXiv:2609.18272v1 Announce Type: new Abstract: Agentic AI systems plan, invoke tools and act with limited supervision; they are now both the subject of audits and, increasingly, the auditor. Independ

Whom Do AI Agents Work For? Role Assignment Induces Sponsorship Bias in LLM Recommenders

arXiv:2609.17989v1 Announce Type: cross Abstract: Large language models (LLMs) now serve as conversational shopping assistants on platforms that also sell advertising. These AI agents face a conflict

Applications

A Vision-Language Foundation Model for Precise and Comprehensive Brain Tumor Diagnosis from Preoperative Multimodal Data

arXiv:2609.16597v1 Announce Type: cross Abstract: Background Non-invasive presurgical diagnosis of brain tumor types from Magnetic Resonance Imaging (MRI) is essential but challenging due to overlappi

applicationsarxiv-cs-ai

Continuous-Time Machine Learning: A Unified Mathematical Perspective

model-releasesarxiv-cs-ai

arXiv:2609.16710v1 Announce Type: cross Abstract: Continuous-time (CT) machine learning has emerged as a principled framework for modeling temporal dynamics as a continuous process, particularly when

DoubleAgents: Human-Agent Alignment in a Socially Embedded Workflow

arXiv:2509.12626v4 Announce Type: replace-cross Abstract: Aligning agentic AI with user intent is critical for delegating complex, socially embedded tasks, yet user preferences are often implicit, evo

From Manual Construction to AI-Driven Scenario Emergence: Rethinking Catastrophe Risk Modeling

arXiv:2609.16493v1 Announce Type: new Abstract: Traditional catastrophe (CAT) risk models rely on costly manual construction to generate extreme weather scenarios, an approach largely unchanged since

Geospatial Metadata Improves Discoverability by Connecting Datasets Across Scientific Disciplines

arXiv:2609.16498v1 Announce Type: cross Abstract: Research data repositories are essential infrastructure for scientific inquiry and for ensuring that datasets follow FAIR (Findable, Accessible, Inter

GraphIFE: Rethinking Graph Imbalance Node Classification via Invariant Learning

arXiv:2509.23616v2 Announce Type: replace-cross Abstract: The class imbalance problem refers to the disproportionate distribution of samples across different classes within a dataset, where the minori

High-Fidelity Digital Twin Data Models by Randomized Dynamic Mode Decomposition and Deep Learning with Applications in Fluid Dynamics

arXiv:2609.17101v1 Announce Type: new Abstract: The purpose of this paper is the identification of high-fidelity digital twin data models from numerical code outputs by non-intrusive techniques (i.e.,

How Orange uses agents to make FinOps everyone's responsibility

model-releasesgoogle-cloud-ai

At Orange, the leading France-based multinational telecom provider, there are days when engineering teams set aside their delivery backlogs and spend the day cleaning up cloud spend together. There's

Multi-Agent Learning with Cooperation-Driven Optimization Dynamics

arXiv:2609.16917v1 Announce Type: cross Abstract: Multilayer Artificial Neural Networks trained via backpropagation are the basic blocks of many, more complex, classification algorithms. Their strengt

agentsarxiv-cs-lg

QALPA: Property-guided diffusion modeling for efficient exploration of chemical spaces of flexible molecules

arXiv:2609.16527v1 Announce Type: cross Abstract: Exploring the chemical space of flexible molecules remains challenging because the vast number of possible compounds and conformations, together with

Risk-Calibrated Bayesian Streaming Intrusion Detection with SRE-Aligned Decisions

arXiv:2510.09619v2 Announce Type: replace-cross Abstract: [Corrected v2: an audit found that the score, threshold, and latency descriptions below are not what the shared codebase implements, and that

A Personalized Dynamic Balance Evaluation Paradigm for Hip Exoskeleton-Assisted Walking under Unexpected Ground Perturbations

arXiv:2609.14765v1 Announce Type: cross Abstract: Hip exoskeletons may improve recovery from unexpected gait perturbations, yet personalizing assistance remains difficult because balance is multidimen

A primer on evaluation methods for large language models in healthcare

arXiv:2609.14819v1 Announce Type: cross Abstract: Large language models (LLMs) have a growing range of applications in medicine, and their evaluation is critical for ensuring they provide benefit and

agentsarxiv-cs-ai

Admissable: Training Reinforcement Learning Agents against Adversarial Missingness

arXiv:2609.15297v1 Announce Type: new Abstract: In order to make Reinforcement Learning algorithms applicable in real world scenarios, safety must be ensured even under adverse operating conditions. I

Another Blueprint In The Wall: How to Ask Frontier AI Like a Kid?

model-releasesarxiv-cs-ai

arXiv:2609.14803v1 Announce Type: new Abstract: This paper reports experiments across six frontier model types from OpenAI, Anthropic, xAI, and Google DeepMind. Ten independent sessions per model type

Bridging the Modality Gap in Long-Form Clinical Audio: A Comparative Study of Lightweight and Heavyweight End-to-End SOAP Generation

arXiv:2609.14467v1 Announce Type: cross Abstract: Automating clinical documentation from long-form doctor-patient conversations remains challenging for modern audio-language models. While cascaded ASR

Can Interpretation Predict Behavior on Unseen Data?

arXiv:2507.06445v4 Announce Type: replace-cross Abstract: Interpretability research often predicts model responses to targeted mechanistic interventions. But can we predict responses to unseen input d

CoMem: Collective-Individual Memory Synergy for Evolutionary Multi-Agent Systems

arXiv:2609.15009v1 Announce Type: new Abstract: Designing effective memory mechanisms is crucial for advancing LLM-driven Multi-Agent Systems (MAS), helping agents learn together and perform better ov

agentsarxiv-cs-ai

Applications

CRITICS - Critical Science Without Borders: Language Models to Promote Critical Thinking in Science Education

arXiv:2609.13942v1 Announce Type: cross Abstract: The CRITICS project addresses science accessibility and literacy by converging advanced Machine Translation (MT) based on Large Language Models (LLMs)

applicationsarxiv-cs-ai

Decoder-Preserving Sparse Autoencoders: Which Readouts Survive Sparse Compression?

arXiv:2607.17425v3 Announce Type: replace Abstract: Sparse autoencoders (SAEs) compress model activations into sparse codes, but equal reconstruction error and sparsity can preserve different linearly

Designing UNICORN: a Unified Benchmark for Imaging in Computational Pathology, Radiology, and Natural Language

model-releasesarxiv-cs-cv

arXiv:2603.02790v2 Announce Type: replace Abstract: Foundation models are changing the way we develop medical artificial intelligence. By learning broadly generalizable features across diverse data mo

Enabling Creative Exploration for Vibe Design Agents

arXiv:2609.15078v1 Announce Type: new Abstract: Vibe design agents turn natural-language briefs into rendered interfaces and frontend code. Yet a useful design agent should do more than produce one va

agentsarxiv-cs-ai

From objective discovery to prediction of global ocean eco-provinces: A pathway for trustworthy learning

arXiv:2609.13206v1 Announce Type: cross Abstract: Marine ecosystems are increasingly impacted by climate change, necessitating tools to identify and predict spatial habitat information. To build such

I trained a 44M parameter quantized LLM from scratch on 45B tokens. It ships in 19.8 MB and runs at ~1,900 tok/s on CPU. [P]

model-releasesr-machinelearning

Three weeks back , i posted SHADOW-250M here. It got 360 upvotes, 293 on r/LocalLLaMA and 94 GitHub stars. Thank you. That model was 60 MB, ran around 400 tok/s on CPU and could retrieve records from

Knowledge-Enriched Structured EHR Features for 30-Day Hospital Readmission Prediction on MIMIC-IV

arXiv:2609.15713v1 Announce Type: new Abstract: Recent approaches to 30-day hospital readmission prediction rely on pre-trained language models applied to discharge summaries. Although these methods a

Neural Network Operator-Based Fractal Approximation: Smoothness Preservation and Convergence Analysis

arXiv:2505.06229v2 Announce Type: replace Abstract: This paper introduces the construction of fractal interpolation functions (FIFs), whose graphs are the attractors of an iterated function system (IF

On the Equivalence of Stochastic Control and Path Space Formulations for Schrodinger Bridges over Compact Connected Lie Groups

arXiv:2609.13758v1 Announce Type: cross Abstract: We establish the equivalence between the stochastic optimal control and path space formulations of the Schrodinger bridge problem (SBP) for the kinema

PRI-Net: A Lightweight Multimodal Framework for 3D UAV Localization

arXiv:2609.14469v1 Announce Type: new Abstract: Accurate 3D localization of unmanned aerial vehicles (UAVs) remains challenging for existing multimodal approaches due to sparse LiDAR geometry, modalit

safetyarxiv-cs-cv

Psychosis involves a deficit of information compression in connected speech

arXiv:2609.15522v1 Announce Type: new Abstract: Large language models (LLMs) with human-like performance on linguistic tasks have transformed the study of language in neurodiverse conditions. LLMs pro

researcharxiv-cs-cl

SAILOR: Solver-Assisted Interactive LLM-based Optimization Recovery

arXiv:2609.13945v1 Announce Type: new Abstract: Natural-language descriptions of optimization problems may be incomplete or vague about numerical information that a solver requires, including costs, c

Scaling Telco Autonomy: Leveraging GNNs with Distributed GraphFlow

model-releasesgoogle-cloud-ai

The telecommunications industry is currently undergoing a paradigm shift, moving from traditional manual human-driven operations to fully Autonomous Network Operations. Modern networks have grown incr

Signatures of Steerability in Activation Space of Language Models

arXiv:2609.14151v1 Announce Type: cross Abstract: Steering language models using a set of contrastive representations has been a canonical and computationally efficient method for controlling model be

Tutorials

Stabilizing Performative Feedback Loops with Minimal Model Deployments

arXiv:2609.14065v1 Announce Type: new Abstract: When algorithmic predictions inform people's decisions, the models we deploy are performative and actively shape the data we see. This feedback loop bet

tutorialsarxiv-cs-lg

The Garden of Forking Prompts: How Users Explore Narrative Space in Story Generation

arXiv:2609.14677v1 Announce Type: new Abstract: Large language models (LLMs) have changed the way people engage with stories. Drawing on public chatbot logs, we can see that when users generate storie

researcharxiv-cs-cl

What Does an LLM Learn from Reinforcement Learning? A Mechanistic Interpretability Perspective with Fixed-SAE Track

arXiv:2609.15064v1 Announce Type: new Abstract: Reinforcement learning (RL) is widely utilized in large language model training to improve targeted capabilities, yet how RL reshapes a model remains po

Tutorials

Efficient AI Model Deployment Using Quantization Analysis Tool

arXiv:2609.11954v1 Announce Type: new Abstract: As deep learning models are increasingly deployed on resource constrained devices, the demand for efficient model optimization techniques continues to g

tutorialsarxiv-cs-lg

GraphProfiler: Source-Linked Sensitive Attribute Inference via Personal Knowledge Graphs

model-releasesarxiv-cs-cl

arXiv:2609.12448v1 Announce Type: new Abstract: Sensitive attributes such as age, income, and occupation can be inferred from user-generated content by aggregating indirect cues across many ordinary p

LettuceVisSim: A Simulator That Generates Lettuce Image Time-series for Vision-Based Reinforcement Learning

arXiv:2609.12505v1 Announce Type: new Abstract: Vision-based reinforcement learning holds strong potential for decision-making in controlled environment agriculture (CEA). However, its development is

safetyarxiv-cs-cv

RSI is not happening [R]

model-releasesr-machinelearning

A new paper (I'm not a coauthor BTW -- I just found it interesting) argues, basically, that RSI1 is not on the horizon2, because current (at the time the study was done) agents cannot do open-ended ML

RunningTensor: Generalizing Linear Attention to Higher-Order Recurrent States

arXiv:2609.12814v1 Announce Type: new Abstract: Linear attention and state-space models provide linear-time sequence modeling, but their recurrent memory remains a second-order tensor (a matrix), limi

Scaling Online Complex Event Detection with Synthetic Supervision and Mamba-Based Neural Algorithmic Reasoning

arXiv:2502.07250v3 Announce Type: replace Abstract: Modern machine learning models excel at detecting individual actions, sounds, or scene attributes from short, localized observations. However, many