Tootfinder

Threads launches a fediverse feed and a way to search for fediverse users, with support for Mastodon and others, for users who turned on fediverse sharing (David Pierce/The Verge)
https://www.theverge.com/news/688267/threads-fediverse-feed-search

Threads is adding fediverse content to your social feeds
A new ‘Fediverse feed’ in your Following section will show posts from Mastodon, Flipboard, and elsewhere.

Threads launches a fediverse feed and a way to search for fediverse users, with support for Mastodon and others, for users who turned on fediverse sharing (David Pierce/The Verge)
https://www.theverge.com/news/688267/threads-fediverse-feed-search

Threads is adding fediverse content to your social feeds
A new ‘Fediverse feed’ in your Following section will show posts from Mastodon, Flipboard, and elsewhere.

Towards Operation Proof Obligation Generation for VDM
Nick Battle, Peter Gorm Larsen
https://arxiv.org/abs/2506.12858 https://arxiv.o…

Towards Operation Proof Obligation Generation for VDM
All formalisms have the ability to ensure that their models are internally consistent. Potential inconsistencies are generally highlighted by assertions called proof obligations, and the generation of these obligations is an important role of the tools that support the method. This capability has been available for VDM tools for many years. However, support for obligation generation for explicit operation bodies has always been limited. This work describes the current state of work to address t…

From Points to Places: Towards Human Mobility-Driven Spatiotemporal Foundation Models via Understanding Places
Mohammad Hashemi, Andreas Zufle
https://arxiv.org/abs/2506.14570

From Points to Places: Towards Human Mobility-Driven Spatiotemporal Foundation Models via Understanding Places
Capturing human mobility is essential for modeling how people interact with and move through physical spaces, reflecting social behavior, access to resources, and dynamic spatial patterns. To support scalable and transferable analysis across diverse geographies and contexts, there is a need for a generalizable foundation model for spatiotemporal data. While foundation models have transformed language and vision, they remain limited in handling the unique challenges posed by the spatial, tempora…

Domain Generalization for Person Re-identification: A Survey Towards Domain-Agnostic Person Matching
Hyeonseo Lee, Juhyun Park, Jihyong Oh, Chanho Eom
https://arxiv.org/abs/2506.12413

Domain Generalization for Person Re-identification: A Survey Towards Domain-Agnostic Person Matching
Person Re-identification (ReID) aims to retrieve images of the same individual captured across non-overlapping camera views, making it a critical component of intelligent surveillance systems. Traditional ReID methods assume that the training and test domains share similar characteristics and primarily focus on learning discriminative features within a given domain. However, they often fail to generalize to unseen domains due to domain shifts caused by variations in viewpoint, background, and l…

On Immutable Memory Systems for Artificial Agents: A Blockchain-Indexed Automata-Theoretic Framework Using ECDH-Keyed Merkle Chains
Craig Steven Wright
https://arxiv.org/abs/2506.13246

On Immutable Memory Systems for Artificial Agents: A Blockchain-Indexed Automata-Theoretic Framework Using ECDH-Keyed Merkle Chains
This paper presents a formalised architecture for synthetic agents designed to retain immutable memory, verifiable reasoning, and constrained epistemic growth. Traditional AI systems rely on mutable, opaque statistical models prone to epistemic drift and historical revisionism. In contrast, we introduce the concept of the Merkle Automaton, a cryptographically anchored, deterministic computational framework that integrates formal automata theory with blockchain-based commitments. Each agent tran…

Coordinate recognition: General theory, Groups, and other surprises
I. Farah, K. Gannon, P. Touchard
https://arxiv.org/abs/2506.13673 https://

Coordinate recognition: General theory, Groups, and other surprises
A class of structures recognizes coordinates if any reduced product of structures from said class witnesses a certain kind of rigidity phenomena. We provide several equivalent characterizations of this property. This property has (at least) two remarkable consequences, one set-theoretic and one model-theoretic, for reduced products of structures of the said class. First, under appropriate set-theoretic assumptions every isomorphism between such reduced products associated with the Fr\' echet id…

Towards an Approach for Evaluating the Impact of AI Standards
Julia Lane
https://arxiv.org/abs/2506.13839 https://arxiv.org/pdf/2506.…

Towards an Approach for Evaluating the Impact of AI Standards
There have been multiple calls for investments in the development of AI standards that both preserve the transformative potential and minimize the risks of AI. The goals of AI standards, particularly with respect to AI data, performance, and governance, are to promote innovation and public trust in systems that use AI. However, there is a lack of a formal or shared method to measure the impact of these standardization activities on the goals of innovation and trust. This concept paper proposes …

On Immutable Memory Systems for Artificial Agents: A Blockchain-Indexed Automata-Theoretic Framework Using ECDH-Keyed Merkle Chains
Craig Steven Wright
https://arxiv.org/abs/2506.13246

On Immutable Memory Systems for Artificial Agents: A Blockchain-Indexed Automata-Theoretic Framework Using ECDH-Keyed Merkle Chains
This paper presents a formalised architecture for synthetic agents designed to retain immutable memory, verifiable reasoning, and constrained epistemic growth. Traditional AI systems rely on mutable, opaque statistical models prone to epistemic drift and historical revisionism. In contrast, we introduce the concept of the Merkle Automaton, a cryptographically anchored, deterministic computational framework that integrates formal automata theory with blockchain-based commitments. Each agent tran…

UniDet-D: A Unified Dynamic Spectral Attention Model for Object Detection under Adverse Weathers
Yuantao Wang, Haowei Yang, Wei Zhang, Shijian Lu
https://arxiv.org/abs/2506.12324 …

UniDet-D: A Unified Dynamic Spectral Attention Model for Object Detection under Adverse Weathers
Real-world object detection is a challenging task where the captured images/videos often suffer from complex degradations due to various adverse weather conditions such as rain, fog, snow, low-light, etc. Despite extensive prior efforts, most existing methods are designed for one specific type of adverse weather with constraints of poor generalization, under-utilization of visual features while handling various image degradations. Leveraging a theoretical analysis on how critical visual details…