arXiv:2507.06337v3 Announce Type: replace Abstract: Background – Pulmonary insufficiency is a consequence of transannular patch repair in Tetralogy of Fallot (ToF), leading to late morbidity and mortality. Transcatheter native outflow tract pulmonary valve replacement (TPVR) has become common, but assessment of patient candidacy and selection of the optimal device remains challenging. We demonstrate an integrated […]
RASTP: Representation-Aware Semantic Token Pruning for Generative Recommendation with Semantic Identifiers
arXiv:2511.16943v1 Announce Type: cross Abstract: Generative recommendation systems typically leverage Semantic Identifiers (SIDs), which represent each item as a sequence of tokens that encode semantic information. However, representing item ID with multiple SIDs significantly increases input sequence length, which is a major determinant of computational complexity and memory consumption. While existing efforts primarily focus on […]
AutoGraphAD: A novel approach using Variational Graph Autoencoders for anomalous network flow detection
arXiv:2511.17113v1 Announce Type: cross Abstract: Network Intrusion Detection Systems (NIDS) are essential tools for detecting network attacks and intrusions. While extensive research has explored the use of supervised Machine Learning for attack detection and characterisation, these methods require accurately labelled datasets, which are very costly to obtain. Moreover, existing public datasets have limited and/or outdated […]
Device-Guided Music Transfer
arXiv:2511.17136v1 Announce Type: cross Abstract: Device-guided music transfer adapts playback across unseen devices for users who lack them. Existing methods mainly focus on modifying the timbre, rhythm, harmony, or instrumentation to mimic genres or artists, overlooking the diverse hardware properties of the playback device (i.e., speaker). Therefore, we propose DeMT, which processes a speaker’s frequency […]
The PLLuM Instruction Corpus
arXiv:2511.17161v1 Announce Type: cross Abstract: This paper describes the instruction dataset used to fine-tune a set of transformer-based large language models (LLMs) developed in the PLLuM (Polish Large Language Model) project. We present a functional typology of the organic, converted, and synthetic instructions used in PLLuM and share some observations about the implications of using […]
Attention-Guided Feature Fusion (AGFF) Model for Integrating Statistical and Semantic Features in News Text Classification
arXiv:2511.17184v1 Announce Type: cross Abstract: News text classification is a crucial task in natural language processing, essential for organizing and filtering the massive volume of digital content. Traditional methods typically rely on statistical features like term frequencies or TF-IDF values, which are effective at capturing word-level importance but often fail to reflect contextual meaning. In […]
TP-MDDN: Task-Preferenced Multi-Demand-Driven Navigation with Autonomous Decision-Making
arXiv:2511.17225v1 Announce Type: cross Abstract: In daily life, people often move through spaces to find objects that meet their needs, posing a key challenge in embodied AI. Traditional Demand-Driven Navigation (DDN) handles one need at a time but does not reflect the complexity of real-world tasks involving multiple needs and personal choices. To bridge this […]
Reassessing prediction in the brain: Pre-onset neural encoding during natural listening does not reflect pre-activation
arXiv:2412.19622v2 Announce Type: replace Abstract: Predictive processing theories propose that the brain continuously anticipates upcoming input. However, direct neural evidence for predictive pre-activation during natural language comprehension remains limited and debated. Previous studies using large language model (LLM)-based encoding models with fMRI and ECoG have reported pre-onset signals that appear to encode upcoming words, but […]
CharCom: Composable Identity Control for Multi-Character Story Illustration
arXiv:2510.10135v2 Announce Type: replace Abstract: Ensuring character identity consistency across varying prompts remains a fundamental limitation in diffusion-based text-to-image generation. We propose CharCom, a modular and parameter-efficient framework that achieves character-consistent story illustration through composable LoRA adapters, enabling efficient per-character customization without retraining the base model. Built on a frozen diffusion backbone, CharCom dynamically composes […]
ConCISE: A Reference-Free Conciseness Evaluation Metric for LLM-Generated Answers
arXiv:2511.16846v1 Announce Type: cross Abstract: Large language models (LLMs) frequently generate responses that are lengthy and verbose, filled with redundant or unnecessary details. This diminishes clarity and user satisfaction, and it increases costs for model developers, especially with well-known proprietary models that charge based on the number of output tokens. In this paper, we introduce […]
Reinforced Generation of Combinatorial Structures: Applications to Complexity Theory
arXiv:2509.18057v5 Announce Type: replace-cross Abstract: Can AI based methods help us make advances in complexity theory? We provide evidence towards answering this in the affirmative, using AlphaEvolve (an LLM code mutation agent) to obtain new results in three settings: a) We improve a recent result of Kunisky and Yu to obtain near-optimal upper and (conditional) […]
The Cooperative Network Architecture: Learning Structured Networks as Representation of Sensory Patterns
arXiv:2407.05650v5 Announce Type: replace-cross Abstract: We introduce the Cooperative Network Architecture (CNA), a model that represents sensory signals using structured, recurrently connected networks of neurons, termed “nets.” Nets are dynamically assembled from overlapping net fragments, which are learned based on statistical regularities in sensory input. This architecture offers robustness to noise, deformation, and generalization to […]