Diet is a major determinant of health, yet accurate dietary assessment from free-living meal images remains challenging. Existing retrieval-based Vision-Language Model (VLM) approaches to nutrient estimation typically rely on textual food representations, while, to our knowledge, direct grounding on visually similar an...
Lubnaa Abdur Rahman, Ioannis Papathanail, Maria Panagiotou et al.· 0 citations
Language-generating AI systems are no longer only objects of linguistic interaction: their outputs increasingly re-enter the communicative and institutional practices from which their training material was drawn. Drawing on social theory, social epistemology, and the philosophy of language, this article develops a soci...
Charalampos M. Liapis, Epameinondas Panagopoulos· 0 citations
tok is a plain-text notation for Business Process Model and Notation (BPMN) 2.0.2 process models and Decision Model and Notation (DMN) 1.5 decisions. One engine checks a tok document against both standards, compiles the document to XML with an automatic diagram, and serves language-model applications through the Model...
Background: Cardiovascular care generates large volumes of clinical free-text documentation in local languages. However, clinical natural language processing (NLP) resources remain concentrated in English, and no existing benchmark is cardiology-specific, multilingual, and broad in entity coverage.
Methods: We presen...
Manuela-Daniela Danu, Miguel Rodr\'iguez-Ortega, Alberto Becerra-Tome et al.· 0 citations
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The growing adoption of digital pathology has rapidly expanded collections of hematoxylin-and-eosin whole-slide images, yet efficient navigation through these archives remains challenging, as metadata is often inconsistent or unavailable. Content-based image retrieval addresses this challenge by identifying similar cas...
Jingsong Liu, Youssef Wally Han Li, Weiwei Zhou et al.· 0 citations
Long-horizon LLM agents make multi-step decisions, yet outcome-reward-only reinforcement learning provides little direct supervision for individual steps. We introduce AttnSR, a step-level reward augmentation method that derives reward allocations from policy attention extracted during training replay, without a separa...
Mengsong Wu, Tianchen Zhou, Zhaochen Su et al.· 0 citations
ZeroRAG is presented, a decentralized routing layer for document retrieval in RAG that performs semantic query routing across an overlay of peers that performs semantic query routing across an overlay of peers with- out global data structures or centralized orchestration.
Petru Neague, Q. Stokkink, Martijn de Vos et al.· 0 citations
Knowledge of the hidden interior structure of an object, including the presence and location of cavities, is essential for predictive simulation, robotic manipulation, and nondestructive inspection. However, such cavities leave no direct signature on the static visible surface, making collision-induced deformation one...
Machine unlearning aims to remove the influence of specific training data from a trained model without retraining from scratch. In real deployments, however, deletion requests arrive over time, calling for incremental class unlearning (ICU): classes are removed sequentially, previously forgotten knowledge must remain f...
Nicol\'as Segura-Kunsagi, Juan Luis Su\'arez-D\'iaz, Iv\'an Sevillano-Garc\'ia et al.· 0 citations
Tabular Foundation Models (TFMs) adapt to a new task only through the labeled rows in their context. However, labels are expensive to acquire in real-world scenarios due to the need for highly specific domain knowledge to ensure high-quality data. Active in-context learning transfers classical acquisition rules to this...
Vision foundation models are the backbone of modern surgical image analysis, yet most surgical systems still rely on encoders pretrained on natural images or on specialist models trained from scratch on comparatively small datasets. Pretraining encoders on large amounts of surgery-specific data has the potential to gen...
Kun Yuan, Hao Ding, Yi-Qing Shen et al.· 0 citations
Estimating causal effects from observational network data requires accounting for both individual treatment and neighborhood exposure. Existing outcome models commonly incorporate these intervention variables into a joint predictor and estimate causal effects through prediction contrasts, leaving the corresponding resp...
Zhirong Huang, Wenzhen Zhang, Guangquan Lu et al.· 0 citations
