Search: “models”

Nearly Minimax-Optimal Regret for Linear Contextual Bandits with Arbitrary Adaptive Action Sets

arXiv:2609.15170v1 Announce Type: new Abstract: We study stochastic linear contextual bandits with arbitrary action menus that may depend on the fixed parameter and the interaction history. We establi

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Neural Modal Decomposition: Architectural Priors from Observables

DGX agent

arXiv:2609.14402v1 Announce Type: cross Abstract: Many engineering building blocks behave as multi-port linear time-invariant systems. RF cavities, photonic devices, and superconducting quantum chips,

researcharxiv-cs-lg

15 Sept 2026

Occlusal Geometry in Closed Form for Orthodontic Report Generation

arXiv:2609.13237v1 Announce Type: cross Abstract: Orthodontic report generation from intraoral data is normally cast as multimodal captioning, yet the released Bite2Text scan pairs are supplied alread

Optimal Transport for Efficient, Unsupervised Anomaly Detection on Industrial Data

arXiv:2609.13940v1 Announce Type: new Abstract: Effective anomaly detection frameworks are a central pillar of the Industry 4.0 paradigm. In this paper, we introduce an Optimal Transport (OT)-based fr

Hardware

OpWeave: Flexible Operator Disaggregation for Heterogeneous LLM Serving

arXiv:2609.14237v1 Announce Type: cross Abstract: LLM serving systems increasingly disaggregate inference into finer-grained stages, with recent approaches separating attention from FFN or MoE executi

hardwarearxiv-cs-ai

Orientation Control of Soft Robots via Adiabatic Spectral Submanifolds

arXiv:2609.14376v1 Announce Type: new Abstract: Soft robots are commonly sought for safety-critical interactions in delicate environments, where accurate position and orientation control is imperative

safetyarxiv-cs-ro

Parameter-Efficient Quantum NLP for Paraphrase Detection: Performance, Robustness, and Entanglement

arXiv:2609.14529v1 Announce Type: cross Abstract: Rigorous empirical validation of quantum machine learning on natural language tasks remains scarce. We evaluate a 10-qubit hybrid quantum-classical va

PARSE: Provenance-Aware Retrieval Sanitization for Professional Domain LLM Agents

arXiv:2606.17467v3 Announce Type: replace-cross Abstract: Prompt injection defenses evaluated on synthetic benchmarks do not generalize to real enterprise documents, which are longer, denser, and inte

Perceptual Reality Transformer: What Must an Illustration Preserve?

arXiv:2508.09852v2 Announce Type: replace-cross Abstract: How can models help people communicate unusual perceptual experiences without changing what they mean? A recognizable image is only part of th

Applications

Phorecaster365: A Human-Supervised Reference Architecture for Hybrid Pharmaceutical Sales Forecasting and Planning Decision Support

arXiv:2609.13907v1 Announce Type: cross Abstract: Pharmaceutical sales forecasts inform planning across products, regions, and distribution channels, yet their interpretation depends on inventory avai

applicationsarxiv-cs-ai

Physical Kernel: Structured Visual Latents for Dark Manipulation

arXiv:2609.13244v1 Announce Type: cross Abstract: We study dark manipulation: after a brief lit Write encodes z0 = Enc(rgb), a policy pi(z) and open-loop dynamics f(z,a) complete contact-rich skills w

safetyarxiv-cs-cv

POLARIS: Training-Free Audio Fingerprinting with Saliency-Based Landmarks and Delaunay Grouping

arXiv:2609.14820v1 Announce Type: cross Abstract: This work presents POLARIS, a training-free audio fingerprinting system that selects landmarks from a locally normalized saliency field and groups the

Primitive-Informed Sampling-Based MPC for Multi-Fingered Dexterous Manipulation

arXiv:2609.14868v1 Announce Type: new Abstract: We present a primitive-informed sampling-based model predictive control (MPC) framework for multi-fingered dexterous manipulation. Sampling-based MPC av

safetyarxiv-cs-ro

Principal-timestep Restricted Init via Sparse Matrix-decomposition in Flow-matching

arXiv:2609.15643v1 Announce Type: new Abstract: Flow-matching diffusion models have recently emerged as a strong paradigm for high-fidelity visual generation. However, their prohibitively high fine-tu

safetyarxiv-cs-lg

Applications

ProIQA: A Process-Based Framework for Fine-Grained Math Item Quality Assessment

arXiv:2609.15292v1 Announce Type: new Abstract: Automatic Item Generation (AIG) is pivotal for personalized education, yet guaranteeing the pedagogical value of generated items remains a bottleneck. E

applicationsarxiv-cs-ai

Projection-Free Multi-level Algorithms for Stochastic Constrained Compositional Optimization

arXiv:2609.15679v1 Announce Type: cross Abstract: This paper studies projection-free algorithms for stochastic constrained multi-level compositional optimization. In this context, the objective functi

QSTAR: Quantum Selective Transfer with Adaptive Routing

arXiv:2607.21411v1 Announce Type: cross Abstract: Quantum transfer learning (QTL) is often evaluated by replacing a classical classifier with a fixed variational quantum head, but this hides a key que

Query-Conditioned Spherical Centroid Aggregation for Multimodal Retrieval

arXiv:2609.15335v1 Announce Type: new Abstract: Multimodal retrieval integrates video, audio, subtitles, and text; however, recent geometric aggregators, such as Gramian volumes, hyperbolic volumes, a

Question's Gambit: The First Move Matters in Agentic Deep Search

model-releasesarxiv-cs-ai

arXiv:2609.14412v1 Announce Type: new Abstract: Deep research agents answer complex questions through iterative loops of searching, reading, and reasoning. Recent work on reasoning-intensive benchmark

ReCAST: Reward Credit Assignment across Timesteps for Online Diffusion Reinforcement

arXiv:2609.13425v1 Announce Type: cross Abstract: Training diffusion models with multiple rewards requires distinguishing user preference from reward informativeness. User preference determines how mu

safetyarxiv-cs-ai

Resolution-Independent Analysis of Encoder--Decoder Operator Learning via Limiting Kernels

arXiv:2609.13798v1 Announce Type: cross Abstract: Operator learning is formulated on function spaces, but training data are typically available only through finite-dimensional representations. In enco

Rethinking Camouflage Image Generation towards a Training-Free Paradigm

arXiv:2609.14377v1 Announce Type: new Abstract: Camouflage image generation (CIG) aims to synthesize realistic camouflaged images by blending foreground objects into concealment-compatible background

ROVER: Robust Loop Closure Verification with Trajectory Prior in Repetitive Environments

arXiv:2508.13488v2 Announce Type: replace-cross Abstract: Loop closure detection is important for simultaneous localization and mapping (SLAM), which associates current observations with historical ke

Agents

Selective Tool Use for Agentic Change Visual Question Answering in Remote Sensing

arXiv:2609.14523v1 Announce Type: new Abstract: Change visual question answering (Change VQA) requires understanding semantic changes across bi-temporal remote sensing images. Although vision language

agentsarxiv-cs-cv

Semantic Fibers and Cross-Gram Interference: A Calculus of Safety Drift in Overcomplete Representations

arXiv:2609.14861v1 Announce Type: cross Abstract: A deployed language model may refuse a harmful request in English yet comply with its faithful translation, revealing a cross-lingual safety failure t

safetyarxiv-cs-ai

Semantic Privacy Protection with Utility Preservation for 3D Point Clouds

arXiv:2609.13823v1 Announce Type: new Abstract: Point cloud data face serious semantic privacy risks during acquisition, transmission, and cross-institutional sharing. Existing methods mostly rely on

ShopEase: A Generative AI-Based Multi-Agent Framework for Intelligent Enterprise Customer Support Using Hybrid Retrieval-Augmented Generation

arXiv:2609.13856v1 Announce Type: new Abstract: Enterprise customer support systems must answer customer questions correctly, retrieve the right policy information, use customer context, and pass diff

Should All Noises Be Treated Equally: Impact of Input Noise Variability on Neural Network Robustness

arXiv:2609.14504v1 Announce Type: new Abstract: Geophysical data collected from active field sites are often contaminated by complex and heterogeneous noise, obscuring weak seismic events, and complic

safetyarxiv-cs-lg

SlopShape: Identifying AI-Generated Commercial Web Content

arXiv:2609.15369v1 Announce Type: new Abstract: Word-level detectors identify unedited AI-generated text almost perfectly, but the literature documents their brittleness under rewording, and a word-le

researcharxiv-cs-cl

Specification Oracles

arXiv:2609.13415v1 Announce Type: new Abstract: Specifications face a basic tradeoff: leave details out, and important questions go unanswered; record every detail separately, and the specification be

researcharxiv-cs-lg

Symmetry- and Property-Aware Crystal Generation with Reinforcement Learning for Inverse Materials Design

arXiv:2609.13468v1 Announce Type: cross Abstract: The inverse design of crystalline materials ultimately seeks structures with desired physical properties. However, for many functional responses, a fa

Tutorials

Synthetic Data in Marketing Research: How to Evaluate and When to Trust

arXiv:2609.13995v1 Announce Type: new Abstract: Debate over synthetic data in marketing research has polarized between claims that large language models (LLMs) make human respondents obsolete and call

tutorialsarxiv-cs-ai

T-SMART: Mechanism-Level Attribution for Tool-Augmented Time-Series Question Answering

arXiv:2609.14142v1 Announce Type: new Abstract: Large language models (LLMs) can struggle with time-series question answering (TS-QA), especially when numerical signals are serialized as text and requ

researcharxiv-cs-lg

TATK: Triple-Aware Top-K Learning with Knowledge-Grounded Verification for LLM-based Sequential Recommendation

arXiv:2609.14565v1 Announce Type: new Abstract: LLM-based sequential recommenders usually cast next-item prediction as text generation, but this interface is poorly matched to full-catalog top-K ranki

The Attribution-Compression Frontier in Retrieval-Augmented Generation

arXiv:2609.14245v1 Announce Type: cross Abstract: Context compression reduces generator input in retrieval-augmented generation, but answer quality alone does not characterize citation attribution. We

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

To Blend In, First Decouple: Rethinking Camouflage Image Generation via Context-Decoupled Representations

arXiv:2607.17768v2 Announce Type: replace Abstract: Camouflage image generation (CIG) focuses on generating visually concealed objects that seamlessly blend into their backgrounds. Existing methods ty

researcharxiv-cs-cv

Toward a Layer-2 Trigger for AI/ML Lifecycle Management in 6G

arXiv:2609.14517v1 Announce Type: cross Abstract: 3GPP has progressively expanded AI/ML lifecycle management in the radio access network, from one-sided model control to Release 20 support for two-sid

researcharxiv-cs-lg

Toward Complete Hospital Discharge Summarization with Abstract Meaning Representation

arXiv:2609.13581v1 Announce Type: new Abstract: Discharge summaries are lengthy medical documents that summarize a hospital in-patient visit. Automatically generating them can reduce documentation bur

safetyarxiv-cs-cl

Tracking Through Decoupling Singularities: A Singularity-Robust Homotopy-Continuation Extension of Feedback Linearization

model-releasesarxiv-cs-ro

arXiv:2607.10436v3 Announce Type: replace-cross Abstract: Input--output feedback linearization fails at decoupling singularities, where the decoupling matrix loses rank, the relative degree is lost, a

TRACTA: Benchmarking Temporal Reasoning over Semantic Trajectories

model-releasesarxiv-cs-ai

arXiv:2607.22365v2 Announce Type: replace Abstract: High-complexity operational environments require methods that characterize temporally distributed patterns rather than classify isolated events. Thi

Transfer Learning for Socioeconomic Estimation in Forced-Displacement Settings

arXiv:2609.15773v1 Announce Type: cross Abstract: Progress in inclusive household surveys has strengthened socioeconomic evidence for forcibly displaced populations, providing indispensable benchmarks

Agents

Turkish MMLU Pro: Traceable Option Augmentation and Its Validity Limits in Turkish Multiple-Choice Evaluation

arXiv:2609.15467v1 Announce Type: cross Abstract: Adding answer options can lower multiple-choice scores without improving assessment validity. Turkish MMLU Pro examines this distinction using 12,000

agentsarxiv-cs-ai

Two-Stage Personalized Gait Phase Estimation in Stroke Survivors During Exoskeleton-Assisted Walking: An Offline Feasibility Study

arXiv:2609.14984v1 Announce Type: new Abstract: This study evaluated personalized gait phase estimation for stroke survivors using functional inertial measurement unit (IMU) alignment and two-stage se

safetyarxiv-cs-ro

Uncertainty-Guided Sparse Refinement for Action Chunking Transformer Policies

model-releasesarxiv-cs-ro

arXiv:2609.15840v1 Announce Type: new Abstract: Learning chunk-based visuomotor policies for long-horizon robot manipulation remains challenging. Recent action-chunking methods have shown promising pe

Utility-Guided Agent Orchestration for Efficient LLM Tool Use

arXiv:2603.19896v2 Announce Type: replace Abstract: Tool-using large language model (LLM) agents often face a fundamental tension between answer quality and execution cost. Fixed workflows are stable

safetyarxiv-cs-ai

ViCo-SAM3: Vision-Conditioned Alignment for Open-Vocabulary Camouflaged Object Segmentation

arXiv:2609.15418v1 Announce Type: new Abstract: Open-vocabulary camouflaged object segmentation (OVCOS) aims to segment unseen camouflaged objects under text guidance. We observe that SAM3 still suffe

Agents

When Agents Slow Down: Understanding LLM Agents' Test-Time Strategies via Elo-per-token Analysis

arXiv:2609.15309v1 Announce Type: new Abstract: Large language model (LLM) agents allocate test-time compute adaptively as they revise solutions, use tools, explore alternatives, and decide when to st

agentsarxiv-cs-cl