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artificial intelligence

10,538 papers

#artificial intelligence Preprint Open access Sep 2026

Label-Guided Knowledge Distillation for 3D-CNNs in Action Recognition

As a key model compression technique, knowledge distillation aims to transfer knowledge from a high-capacity teacher model to a lightweight student model for enhancing the latter's performance. In this work, we reviewed the feature knowledge distillation for 3D-CNNs and observed that most feature distillation methods i...

Yanjiang Shi, Peng Zhao, Nan Qi et al. · 0 citations
#artificial intelligence Preprint Open access Sep 2026

TileNet: Tile-Based CNN-SVM Architecture for Autonomous Unmanned Aerial Systems Inspection of Flat Roofs

Flat roofs are among the most influential components of the building envelope, governing both structural performance and thermal efficiency, and thereby contributing directly to household energy consumption, carbon emissions, and long-term environmental sustainability. Timely detection of roof defects is essential for...

Samuel Dunthorne, Hashim A. Hashim · 0 citations
#artificial intelligence Preprint Open access Sep 2026

Comfort by Construction: Adaptive, Comfort-Bounded Action Spaces for Learned Driving Policies

Data-driven driving simulators command accelerations and steering rates from a fixed grid without constraining the realized accelerations and jerks. As a result, reinforcement-learning policies inflate safety metrics through abrupt, last-second maneuvers that lie far outside the range of human driving and would be unac...

Anna Rothenh\"ausler, Daniel Jost, Raghu Rajan et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Tasks over Application Manuals: Revealing Gaps in Long-Horizon Procedural Reasoning for Language Models

Large language models (LLMs) have achieved strong performance on a wide range of natural language tasks, and recent benchmarks suggest that they are increasingly adept at multi-hop reasoning. However, these benchmarks are typically short-horizon, requiring only a small number of retrieval or inference steps, and provid...

Utkarsh Soni, S. Murtaza, Yi-Fan Nie et al. · 0 citations
#artificial intelligence Preprint Sep 2026

SeqMoE: Toward Full-Load Performance via Predictive and Graph-Compatible MoE Offloading

Mixture-of-Experts (MoE) creates a structural advantage for offloading: only a small fraction of activated experts need to reside in device memory, and if they can be loaded in time for computation, offloading can in principle approach full-load performance, where all model weights reside in device memory. Yet translat...

Zi-Han Wang, Yu-Qi Wang, Lei Gong et al. · 0 citations
#artificial intelligence Open access Jul 2026

Generative Retrieval for Unsupervised Text-Based Person Search.

Text-based person search (TBPS) aims to retrieve images of a target person from a large image gallery based on a given natural language description. Most existing methods rely on supervised learning with manually annotated image-text pairs. In this paper, we explore unsupervised TBPS, with only unlabeled images. We pro...

Mang Ye, Yucheng Ji, Yang Bai et al. · 0 citations
#artificial intelligence Preprint Open access Sep 2026

ARC: Autonomous Robotics Compliance A Three-Layer Governance Architecture for Deployed Autonomous Systems

Proposed governance framework for autonomous robotic systems, introducing a three-layer compliance architecture (ARC) instantiated through model safety validation, cognitive certification benchmarks, and operational authorization standards.

Tord Eide, Einar Holt · 0 citations
#artificial intelligence Preprint Sep 2026

LLM-Enhanced Dual-Branch Learning for Large-Scale Multi-Label Text Classification

Large-scale multi-label text classification assigns a small subset of relevant labels to each document from a vocabulary containing thousands or tens of thousands of candidate labels. Although pretrained language models have improved semantic text representations, most representation-based approaches center their predi...

Hui Ye, Jing Zhang, Xiu-Long Yang et al. · 0 citations
#artificial intelligence Preprint Open access Sep 2026

UniPart: Towards Zero-shot Language-Grounded 3D Part Segmentation for Embodied Interaction

Fine-grained robotic manipulation depends on understanding parts, not only whole objects. Existing 3D foundation models tend to be either generalized but object-aware, or part-aware but limited to closed-set taxonomies, which weakens zero-shot transfer. We study text-conditioned 3D part segmentation, where a free-form...

Xinqiang Yu, Zekun qi, Jiawei He et al. · 0 citations
#artificial intelligence Preprint Open access Sep 2026

Behavior Quotient Learning for Low-Rank Adaptation of LLM Agents

LLM-based agents rely on heterogeneous interaction capabilities to accomplish complex tasks. Existing approaches often distribute these capabilities across multiple LoRA adapters, which increases adapter storage requirements and introduces routing overhead during inference. A single LoRA avoids this overhead, but learn...

Pengyang Zhou, Xiaobin Tu, Zhengxi Liu et al. · 0 citations
#artificial intelligence Preprint Open access Sep 2026

Large Distant Gradients Need Not Be Reliable: reliability-weighted credit assignment for long-horizon autoregressive forecasting

In autoregressive forecasting, long prediction rollouts provide distant supervision, but backpropagation through time (BPTT) carries gradients from those losses through many autoregressive steps. Repeated Jacobian products can make distant gradients dominate the update while amplifying predictable signal and unpredicta...

Junhao Zhao, David Michael Simberg, Jacob Kang et al. · 0 citations
#artificial intelligence Preprint Open access Sep 2026

A Multi-Vehicle Dataset with Camera, LiDAR, and Radar Sensors and Scanned 3D Models for Custom Auto-Annotation using RTK-GNSS

Datasets are a crucial element in the development of perception algorithms. They relate sensor measurement data to annotated reference information and allow for the deduction of sensor and object characteristics. In autonomous driving, the reference data commonly consist of semantic image segmentation, point-wise assoc...

Philipp Berthold, Bianca Forkel, Mirko Maehlisch · 0 citations

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MIT News · Artificial Intelligence Sep 29, 2026

Who we become when we talk to machines

Professor Sherry Turkle’s new book, “Artificial Intimacy,” offers a withering critique of chatbots and the antisocial dynamics she believes they encourage.

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