Cryptographically verifiable C2PA-based Content Credentials (CCs) can be attached to freshly acquired or generated digital images but also to already existing ones with no previous provenance information, for instance after processing through trusted C2PA-enabled software tools. The latter case leads to images with so-...
Riccardo Ziglio, Eleonora Marchesini, Andrea Montibeller et al.· 0 citations
This paper proposes Teacher-Evolution Self-Distillation (TESD), which enables the self-teacher to generate rollouts and receive environmental feedback based on task correctness and context independence and performs teacher-oriented optimization to continuously enhance the model's self-teaching capability during distill...
Shu-Fan Shen, Zhong-Ni Hou, Chao Bi et al.· 0 citations
We ask what AI coding agents and AI security harnesses find that deterministic static application security testing (SAST) does not, and what they miss that SAST catches. VulnBench 2.0 is a benchmark of 108 hand-curated, attacker-reachable vulnerabilities in 20 open-source web applications in Go, JavaScript/TypeScript,...
Liran Tal, Chris Liu, Charlotte Fereday et al.· 0 citations
This paper refines and empirically evaluates the Artificial Personality Model (APM), a hybrid framework integrating human-centred and machine-specific personality dimensions, and contributes an empirically refined framework and a novel instrument for measuring perceived artificial personality, offering practical guidan...
Alexander Dregger, Barbarella Petz, Erik Kuhn et al.· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
There is a fundamental contradiction between the desire for models that can generalize, and models that can continuously adapt to recent input with changing statistics. These conditions, captured in few-shot and continual learning settings, can bias or disrupt learned representations. This harms generalization to a bro...
Large audio language models (LALMs) can process speech directly, but it remains unclear how well they use the non-lexical acoustic information that speech carries. We study this question through pain, using TAME-Pain, which contains pain-neutral Harvard sentences and spoken pain ratings recorded at different self-repor...
Personalizing AI assistants requires adapting their behavior to users' preferences and task contexts. Existing work elicits assistant personas through persona prompting or finetuning on persona-conditioned generations. However, persona descriptions alone do not identify what to change or preserve in a particular respon...
Diffusion and flow matching models offer scalable approaches to generating crystalline materials, molecular conformers, and protein-ligand complexes. However, satisfying crystallographic symmetry, structural geometry, and accurate stereochemistry remains challenging. Satisfying these requirements calls for corrections...
Pengfei Cai, Katharina S. C. J\"ager, Utkarsh Utkarsh et al.· 0 citations
Joint-embedding predictive architectures (JEPAs) learn to predict representations rather than pixels, offering a compact way to model how visual scenes evolve. We ask whether this predictive objective improves closed-loop control when a vision-language-action (VLA) policy already uses V-JEPA features. We call our JEPA-...
Rufeng Xiao (VLA Research Team, Synthoid.ai), Ruihao Xiao (VLA Research Team et al.· 0 citations
AI agents now install packages, call model APIs with their operators' keys and change code in repositories that deploy to production. The network, credentials and write access they need are also how they can leak data, steal a key or change a system nobody approved. Sandboxes contain an agent but leave little evidence...
Decision models offered resource advantages alongside lower peak accuracy; generative large language model configurations offered resource advantages alongside lower peak accuracy; selecting models for medical workflows requires considering probability quality and repeatability together with accuracy and the resources...
O. Freyer, D. Glauert, M. Hofmann et al.· 0 citations
This work proposes user behaviour fuzzing, a guided search over plausible user behaviours that can lead a model to violate its role specification, and introduces RoleFUZZER, a framework that adapts coverage-guided fuzzing from software testing to operationalise the search.
Kshitish Ghate, Michael Stephen Saxon, Tadayoshi Kohno et al.· 0 citations
