Tootfinder

"AI bots that scrape the internet for training data are hammering the servers of libraries, archives, museums, and galleries, and are in some cases knocking their collections offline"
#AI is ruining our digital world
(Original title: AI Scraping Bots Are Breaking Open Libraries, Archives, and Museums)

AI Scraping Bots Are Breaking Open Libraries, Archives, and Museums
"This is a moment where that community feels collectively under threat and isn't sure what the process is for solving the problem.”

arxiv_collab: Scientific collaborations in physics (1995-2005)
Collaboration graphs for scientists, extracted from the Los Alamos e-Print arXiv (physics), for 1995-1999 for three categories, and additionally for 1995-2003 and 1995-2005 for one category. For copyright reasons, the MEDLINE (biomedical research) and NCSTRL (computer science) collaboration graphs from this paper are not publicly available.
This network has 16706 nodes and 121251 edges.
Tags: Social, Collaborati…

Heat Kernel Goes Topological
Maximilian Krahn, Vikas Garg
https://arxiv.org/abs/2507.12380 https://arxiv.org/pdf/2507.12380

Heat Kernel Goes Topological
Topological neural networks have emerged as powerful successors of graph neural networks. However, they typically involve higher-order message passing, which incurs significant computational expense. We circumvent this issue with a novel topological framework that introduces a Laplacian operator on combinatorial complexes (CCs), enabling efficient computation of heat kernels that serve as node descriptors. Our approach captures multiscale information and enables permutation-equivariant represen…

Traffic-Aware Pedestrian Intention Prediction
Fahimeh Orvati Nia, Hai Lin
https://arxiv.org/abs/2507.12433 https://arxiv.org/pdf/2507…

Traffic-Aware Pedestrian Intention Prediction
Accurate pedestrian intention estimation is crucial for the safe navigation of autonomous vehicles (AVs) and hence attracts a lot of research attention. However, current models often fail to adequately consider dynamic traffic signals and contextual scene information, which are critical for real-world applications. This paper presents a Traffic-Aware Spatio-Temporal Graph Convolutional Network (TA-STGCN) that integrates traffic signs and their states (Red, Yellow, Green) into pedestrian intenti…

Defining neurosymbolic AI
Lennert De Smet, Luc De Raedt
https://arxiv.org/abs/2507.11127 https://arxiv.org/pdf/2507.11127

Defining neurosymbolic AI
Neurosymbolic AI focuses on integrating learning and reasoning, in particular, on unifying logical and neural representations. Despite the existence of an alphabet soup of neurosymbolic AI systems, the field is lacking a generally accepted formal definition of what neurosymbolic models and inference really are. We introduce a formal definition for neurosymbolic AI that makes abstraction of its key ingredients. More specifically, we define neurosymbolic inference as the computation of an integra…

Trigonal Curve with Trigonal Deformation of Maximal Rank
Jiacheng Zhang
https://arxiv.org/abs/2506.11450 https://arxiv.org/pdf/2506.1…

Trigonal Curve with Trigonal Deformation of Maximal Rank
By extending methods of Favale-Pirola arXiv:2108.02157 and González-Alonso-Torelli arXiv:2402.15158 to toric surfaces via toric Jacobian ring, we are able to show there exists trigonal curve with trigonal deformation of rank $g$ for $g=5,7,9,11,13,15$ by giving an explicit example. Also, we give a computable criterion to determine whether a nondegenerate ample section of toric surface has first order deformation of rank $g$ within the linear system.

arxiv_collab: Scientific collaborations in physics (1995-2005)
Collaboration graphs for scientists, extracted from the Los Alamos e-Print arXiv (physics), for 1995-1999 for three categories, and additionally for 1995-2003 and 1995-2005 for one category. For copyright reasons, the MEDLINE (biomedical research) and NCSTRL (computer science) collaboration graphs from this paper are not publicly available.
This network has 31163 nodes and 120029 edges.
Tags: Social, Collaborati…

Emergence of Quantised Representations Isolated to Anisotropic Functions
George Bird
https://arxiv.org/abs/2507.12070 https://arxiv.o…

Emergence of Quantised Representations Isolated to Anisotropic Functions
This paper describes a novel methodology for determining representational alignment, developed upon the existing Spotlight Resonance method. Using this, it is found that algebraic symmetries of network primitives are a strong predictor for task-agnostic structure in representations. Particularly, this new tool is used to gain insight into how discrete representations can form and arrange in autoencoder models, through an ablation study where only the activation function is altered. Representati…

Selective Quantization Tuning for ONNX Models
Nikolaos Louloudakis, Ajitha Rajan
https://arxiv.org/abs/2507.12196 https://arxiv.org/p…

Selective Quantization Tuning for ONNX Models
Quantization is a process that reduces the precision of deep neural network models to lower model size and computational demands, often at the cost of accuracy. However, fully quantized models may exhibit sub-optimal performance below acceptable levels and face deployment challenges on low-end hardware accelerators due to practical constraints. To address these issues, quantization can be selectively applied to only a subset of layers, but selecting which layers to exclude is non-trivial. To th…

Measuring Informativeness Gap of (Mis)Calibrated Predictors
Yiding Feng, Wei Tang
https://arxiv.org/abs/2507.12094 https://arxiv.org/…

Measuring Informativeness Gap of (Mis)Calibrated Predictors
In many applications, decision-makers must choose between multiple predictive models that may all be miscalibrated. Which model (i.e., predictor) is more "useful" in downstream decision tasks? To answer this, our first contribution introduces the notion of the informativeness gap between any two predictors, defined as the maximum normalized payoff advantage one predictor offers over the other across all decision-making tasks. Our framework strictly generalizes several existing notions: it subsu…