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Caller identity platform Truecaller recently launched a new feature that lets one person become an admin of a family group, get alerts about fraud calls …
To learn how to behave, the current revolutionary generation of AIs must be trained on vast quantities of published images, written works, and sounds, many …
arXiv:2603.11781v1 Announce Type: new Abstract: Multi-agent LLM systems increasingly tackle complex reasoning, yet their interaction patterns remain limited to voting, unstructured debate, or pipeline orchestration. …
arXiv:2603.11399v1 Announce Type: new Abstract: Users on e-commerce platforms can be uncertain about their preferences early in their search. Queries to recommendation systems are frequently …
arXiv:2603.11442v1 Announce Type: new Abstract: Can humans detect AI-generated financial documents better than machines? We present GPT4o-Receipt, a benchmark of 1,235 receipt images pairing GPT-4o-generated …
arXiv:2603.11736v1 Announce Type: new Abstract: In recent years, generative artificial intelligence (GenAI) systems have assumed increasingly crucial roles in selection processes, personnel recruitment and analysis …
arXiv:2603.11455v1 Announce Type: new Abstract: This study examines users' behavioural intention to use OpenClaw through the Cognition--Affect--Conation (CAC) framework. The research investigates how cognitive perceptions …
arXiv:2603.11798v1 Announce Type: new Abstract: Multi-document Multi-entity Question Answering inherently demands models to track implicit logic between multiple entities across scattered documents. However, existing Large …
arXiv:2603.11266v1 Announce Type: new Abstract: Unlearning in Large Language Models (LLMs) aims to enhance safety, mitigate biases, and comply with legal mandates, such as the …
arXiv:2603.11388v1 Announce Type: new Abstract: Safety alignment aims to ensure that large language models (LLMs) refuse harmful requests by post-training on harmful queries paired with …
arXiv:2603.11816v1 Announce Type: new Abstract: Traffic forecasting is a cornerstone of intelligent transportation systems. While existing research has made significant progress in short-term prediction, long-term …
arXiv:2603.11679v1 Announce Type: new Abstract: As real-world datasets become increasingly complex and heterogeneous, supervised learning is often bottlenecked by input representation design. Modeling multimodal data …