Introduction: Horizon scanning in healthcare assesses early signals of innovation, crucial for timely adoption. Current horizon scanning faces challenges in efficient information retrieval and analysis, especially in grey literature, presenting a need for innovative tools.
Methodology: This article introduces SCANAR...
Lena Schmidt, Oshin Sharma, Chris Marshall et al.· 0 citations
Toxicity detection has become core safety infrastructure for online moderation, dataset filtering, and deployed language-model systems. Yet most detectors still treat toxicity as an intrinsic property of isolated text. This position paper argues that toxicity detection should be evaluated as the contextual measurement...
Sergei Berezin, Reza Farahbakhsh, Noel Crespi· 0 citations
Traditional multi-agent reinforcement learning (MARL) systems can develop cooperative strategies through repeated interactions. However, these systems are unable to perform well on any other setting than the one they have been trained on, and struggle to successfully cooperate with unfamiliar collaborators. This is par...
Arjun V Sudhakar, Hadi Nekoei, Mathieu Reymond et al.· 0 citations
Emergent Language (EL) focuses on the emergence of communication among artificial agents. Although symbolic communication channels more closely mirror the discrete nature of human language, learning such protocols remains fundamentally difficult due to the non-differentiability of symbol sampling. Existing approaches t...
Mohammad Mahdi Samiei Paqaleh, Mehdi Jamalkhah, Mahdieh Soleymani Baghshah· 0 citations
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In recent years, a substantial body of work in visually grounded natural language processing has focused on real-life multimodal scenarios such as describing content depicted in images or videos. However, comparatively less attention has been devoted to studying the nature and degree of interaction between the differen...
Aditya K Surikuchi, Raquel Fern\'andez, Sandro Pezzelle· 0 citations
Machine learning can help sellers predict buyers' willingness to pay, but its predictions may be plausible and yet entirely unrelated to a buyer's value. We introduce a Bayesian auction model that distinguishes such hallucinations from ordinary measurement noise. We characterize revenue-maximizing auctions with publicl...
Ilan Lobel, Humberto Moreira, Omar Mouchtaki· 0 citations
A comprehensive survey and a taxonomy of state-of-the-art open LLMs and AIFMs for clinical tasks and a subjective evaluation of LLM-driven personalized prescriptions are provided, highlighting the importance of responsible and transparent deployment in healthcare contexts.
Maximum a posteriori inference in a finite Markov random field is generally NP-hard. We study an instance-wise optimizer that minimizes the exact multilinear energy under product marginals. The canonical parameterization adds a GNN output to free per-node logits. This residual bypass is a global change of coordinates,...
Yaomin Wang, Chaolong Ying, Xiaodong Luo et al.· 0 citations
Complex query answering (CQA) on knowledge graphs (KGs) is gaining momentum as a challenging reasoning task. In this paper, we show that the current benchmarks for CQA might not be as complex as we think, as the way they are built distorts our perception of progress in this field. For example, we find that in these ben...
Cosimo Gregucci, Bo Xiong, Daniel Hernandez et al.· 0 citations
This paper proposes a new clustering technique to decompose the vascular tree into various scale levels, from tiny to large vessels, and extends standard 3D UNet to multi-task learning by incorporating scale-specific auxiliary tasks and contrastive learning to encourage the discrimination between scales in the shared r...
A. Sadikine, B. Badic, J. Tasu et al.· IEEE International Symposium...· 1 citation
Rating-based human evaluation has become an essential tool to accurately evaluate the impressive performance of large language models (LLMs). However, current rating systems suffer from several important limitations: first, they fail to account for biases that significantly influence evaluation results, second, they re...
Jasper Dekoninck, Maximilian Baader, Martin Vechev· 0 citations
Due to the ongoing electrification of transportation systems, energy-based routing problems such as the Electric Vehicle Routing Problem (EVRP) are becoming increasingly important. Unlike Euclidean routing problems, the EVRP involves asymmetric energy costs caused by road topology. Existing learning-based routing appro...
Attila Lischka, Filip Rydin, Jiaming Wu et al.· 0 citations
