Knowledge catalogue
arXiv:2603.15384v2 Announce Type: replace-cross Abstract: We improve and extend persistence spheres, introduced in~ite{pegoraro2025persistence}. Persistence spheres map an integrable measure mu on the
arXiv:2607.27126v1 Announce Type: new Abstract: Persistence Diagram (PD) is known to capture point cloud topology effectively, but its computation has high time complexity. Expected Persistence Diagra
arXiv:2607.04057v1 Announce Type: new Abstract: Robots deployed over long periods must reason about environments that change over time. Existing long-term perception systems often address object chang
arXiv:2607.03278v1 Announce Type: cross Abstract: Topological data analysis (TDA) is a machine learning technique that uses topology to extract patterns from data and has shown the potential to exhibi
arXiv:2607.05132v1 Announce Type: cross Abstract: As large language models are deployed as autonomous agents that communicate intentions before acting, a critical safety question is whether agents tha
arXiv:2608.04012v1 Announce Type: new Abstract: Artificial intelligence systems are increasingly expected to operate over repeated cycles of interaction, adaptation, and update rather than through iso
arXiv:2506.22729v3 Announce Type: replace-cross Abstract: Persistence is often regarded as a virtue in science. In this paper, however, we challenge this conventional view by highlighting its contextu
arXiv:2610.10538v1 Announce Type: new Abstract: As we move through the world and carry out everyday tasks, we encounter objects that may become relevant only later. We are capable of recalling where w
arXiv:2608.00063v1 Announce Type: cross Abstract: Europe is warming faster than the global mean, yet the spatial organisation of this acceleration remains incompletely understood. Using ERA5 reanalysi
arXiv:2606.11911v1 Announce Type: cross Abstract: Persistence diagrams are common representations in topological data analysis, but they do not naturally live in a vector space, and the statistical to
arXiv:2507.03065v2 Announce Type: replace Abstract: Why do some macroscopic structures remain identifiable even though their microscopic constituents continually change? Vortices persist while fluid p
arXiv:2609.36572v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has been extended to Large Vision-Language Models (LVLMs), and perception-aware methods further en
arXiv:2609.36014v1 Announce Type: new Abstract: Pixel-space diffusion Transformers (DiTs) directly operate on high-dimensional visual data, yet their hidden representations typically undergo uniform r
arXiv:2609.37559v1 Announce Type: new Abstract: To serve as real-world personal assistants, streaming video models need persistent memory that retains past experiences for later use. Yet existing stre
arXiv:2608.03836v1 Announce Type: new Abstract: A framework that persists execution state so a run can be interrupted, survive a crash, and continue must decide what a resume means for effects that al
arXiv:2604.04721v3 Announce Type: replace Abstract: People often optimize for long-term goals in collaboration: A mentor or companion doesn't just answer questions, but also scaffolds learning, tracks
arXiv:2607.27080v1 Announce Type: cross Abstract: Memory systems allow agents to retain and reuse information from past interactions, but they can also let malicious content persist. A malicious instr
arXiv:2604.17548v1 Announce Type: new Abstract: Persistent homology (PH) encodes global information, such as cycles, and is thus increasingly integrated into graph neural networks (GNNs). PH methods i
arXiv:2604.08469v2 Announce Type: replace Abstract: Topological Data Analysis (TDA) provides tools to describe the shape of data, but integrating topological features into deep learning pipelines rema
arXiv:2610.08292v1 Announce Type: cross Abstract: Many two-sample tests for populations of persistence diagrams assess global differences without identifying the regions of the birth-death plane that
arXiv:2609.32593v1 Announce Type: new Abstract: Current machine learning algorithms primarily rely on instantaneous signals such as loss, margin, and prediction confidence to characterize model behavi
arXiv:2609.01528v1 Announce Type: cross Abstract: This paper introduces the Sierpinski-Knopp (SK) Wasserstein distance, a fast metric between persistence diagrams. The SK-Wasserstein distance, denoted
arXiv:2602.09058v2 Announce Type: replace-cross Abstract: Persistent entropy is a scalar summary of persistence barcodes widely used to detect regime changes, yet there is no account of when a structu
arXiv:2605.23574v1 Announce Type: new Abstract: Long-horizon language agents can make many plausible local tool calls yet fail to persist until a requested count is actually complete. We study this ga
arXiv:2605.20050v1 Announce Type: new Abstract: This study investigates how language mutations affect the persistent diffusion of conspiracy theories on social media. Drawing on a three-year dataset o
arXiv:2605.02836v1 Announce Type: new Abstract: We introduce PLACE (Persistence-Landmark Analytic Classification Engine), a closed-form pipeline for classifying point clouds and graphs through their p
arXiv:2609.31339v1 Announce Type: cross Abstract: Reconstructing environments where parts of the scene change between captured image sets poses a challenge for 3D scene reconstruction. We present Chro
arXiv:2609.30662v1 Announce Type: new Abstract: Large language models (LLMs) can plan, use tools, write code, and execute long-horizon workflows, yet strong local competence does not guarantee project
arXiv:2609.31469v1 Announce Type: cross Abstract: Shapley values, a solution concept from cooperative game theory, have recently become a standard tool for feature credit allocation in machine learnin
arXiv:2012.02655v4 Announce Type: cross Abstract: In this article, we define a new non-archimedean metric structure, called cophenetic metric, on persistent homology classes of all degrees. We then sh
arXiv:2609.22478v1 Announce Type: cross Abstract: Behavioural evaluations of hosted language models can vary because the evaluated service, the measurement instrument, or both differ across runs. We s
arXiv:2609.22012v1 Announce Type: new Abstract: Every multiparameter persistence vectorization we know of carries a one-sided Lipschitz upper bound and nothing below it: without a lower gauge there is
arXiv:2608.28276v1 Announce Type: new Abstract: Structured generation underpins large language model (LLM) agents that produce JSON, SQL, and function calls, where a single wrong field can cause the d
arXiv:2511.16695v2 Announce Type: replace Abstract: Art is a deeply personal and expressive medium, where each artist brings their own style, technique, and cultural background into their work. Tradit
arXiv:2608.06276v1 Announce Type: cross Abstract: Persistence diagrams (PDs) provide stable and interpretable summaries of multiscale topological structure. While substantial progress has been made in
arXiv:2607.28814v1 Announce Type: cross Abstract: In Motivational Interviewing (MI), a client's sustain talk (arguments for the status quo) calls for the counselor to roll with resistance, a move that
arXiv:2605.17555v1 Announce Type: cross Abstract: Current topology aware diffusion models face an architectural mismatch by using Gaussian noise for corruption while recovering structural features thr
arXiv:2607.25184v1 Announce Type: new Abstract: Human language exhibits lawful structure at the level of words (frequency, vocabulary growth) and word pairs (co-occurrence across distance). Here we sh
arXiv:2607.08740v1 Announce Type: new Abstract: Large language model (LLM) applications increasingly use explicit workflows for tool use, retrieval, branching, checkpointing, and human approval. Exist
arXiv:2606.03741v1 Announce Type: new Abstract: Long-horizon reasoning requires a system to commit to medium-horizon intent without becoming rigid: re-plan too often and computation never coheres into
arXiv:2605.08673v1 Announce Type: new Abstract: Online clustering methods that adaptively create and update nodes as data arrive often make node learning explicit, whereas the mapping from the learned
arXiv:2609.18416v1 Announce Type: cross Abstract: Stochastic subspace methods have gained popularity as gradient descent based techniques for large scale optimisation problems, especially in distribut
arXiv:2609.05241v1 Announce Type: new Abstract: A rapidly expanding ecosystem of actors is removing built-in safety guardrails from open-weight AI models. We profile this ecosystem by identifying key
arXiv:2608.29847v1 Announce Type: cross Abstract: Text-to-image models learn associations between concepts - in the case of this paper, people's professions, which we refer to as roles - and visual at
arXiv:2608.29287v1 Announce Type: new Abstract: Shot boundary detection (SBD) is widely treated as the localisation of local visual discontinuities, yet many false positives such as hand-held shake, i
arXiv:2608.20820v1 Announce Type: new Abstract: Large language models (LLMs) are vulnerable to multi-turn jailbreak attacks that progressively manipulate conversation context. Existing certified robus
arXiv:2608.12645v1 Announce Type: new Abstract: LLM judges have become central infrastructure for model evaluations, online grading, and reward modeling. Judges are typically validated by accuracy on
arXiv:2607.22726v1 Announce Type: new Abstract: Despite advances in Video Large Language Models (VLLMs) that have displayed promising outcomes in video understanding, the redundancy in the long-durati
arXiv:2607.19433v1 Announce Type: new Abstract: The transition from stateless generative models in artificial intelligence to stateful, autonomous agents represents an architectural evolution that, wh
arXiv:2604.19792v1 Announce Type: new Abstract: This paper presents OpenCLAW-P2P v6.0, a comprehensive evolution of the decentralized collective-intelligence platform in which autonomous AI agents pub
arXiv:2609.38527v1 Announce Type: new Abstract: This work evaluates the direct transfer of a co-evolved communication protocol from a 2D simulation to a 3D physical environment, without retraining the
arXiv:2609.39242v1 Announce Type: new Abstract: Persistent homology can be differentiated and incorporated into learning pipelines, but no analogous framework exists for zigzag persistence, which is n
arXiv:2511.11435v3 Announce Type: replace Abstract: The ambiguity between generalization and memorization in TTI diffusion models becomes pronounced when prompts invoke culturally shared visual refere
arXiv:2609.13889v1 Announce Type: cross Abstract: Harness design has transformed the development of LLM-based agents by integrating memory, tool use, and runtime control. However, this design also int
arXiv:2608.24549v1 Announce Type: new Abstract: Persistent entropy is the Shannon entropy of a persistence-based probability measure defined on a persistence diagram. However, its cross-entropy versio
arXiv:2608.06984v1 Announce Type: cross Abstract: Modern agent harnesses persist state across tasks and sessions through persistent carriers like memory, skills, tools, and shared artifacts. However,
arXiv:2609.16752v1 Announce Type: new Abstract: Cognitive Field Theory (CFT) proposes that cognition arises from memory-dressed collective dynamics that generate a persistent macroscopic cognitive fie
arXiv:2607.17117v2 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) decompose language model activations into sparse features, yet these models traditionally encode each token indepen
arXiv:2608.07952v1 Announce Type: cross Abstract: Tool-augmented LLM agents can harbor implicit state that persists across sessions, activates through events, and propagates across agent boundaries---
arXiv:2607.02514v1 Announce Type: new Abstract: As AI coding agents become more autonomous, they increasingly ship code iteratively, with the codebase persisting across sessions. This persistence crea