arXiv:2509.16399v1 Announce Type: new Abstract: In social impact optimization, AI decision systems often rely on solvers that optimize well-calibrated mathematical objectives. However, these solvers cannot directly accommodate evolving human preferences, typically expressed in natural language rather than formal constraints. Recent…
arXiv:2509.16431v1 Announce Type: new Abstract: In the manufacturing industry, it is very important to keep machines and processes running smoothly and without unexpected problems. One of the most common tools used to check if everything is working properly is called…
arXiv:2509.16348v1 Announce Type: new Abstract: We present UNIPHY+, a unified physiological foundation model (physioFM) framework designed to enable continuous human health and diseases monitoring across care settings using ubiquitously obtainable physiological data. We propose novel strategies for incorporating contextual information…
arXiv:2509.16372v1 Announce Type: new Abstract: This study evaluates causal reasoning in large language models (LLMs) using 99 clinically grounded laboratory test scenarios aligned with Pearl’s Ladder of Causation: association, intervention, and counterfactual reasoning. We examined common laboratory tests such as…
arXiv:2509.16332v1 Announce Type: new Abstract: Large Language Models increasingly mediate high-stakes interactions, intensifying research on their capabilities and safety. While recent work has shown that LLMs exhibit consistent and measurable synthetic personality traits, little is known about how modulating these…
arXiv:2509.16330v1 Announce Type: new Abstract: Large Language Model (LLM)-based agents have emerged as a new paradigm that extends LLMs’ capabilities beyond text generation to dynamic interaction with external environments. By integrating reasoning with perception, memory, and tool use, agents are…
arXiv:2509.16299v1 Announce Type: new Abstract: Fuzzy implication functions constitute fundamental operators in fuzzy logic systems, extending classical conditionals to manage uncertainty in logical inference. Among the extensive families of these operators, generalizations of the classical material implication have received considerable…
arXiv:2509.17991v1 Announce Type: cross Abstract: Almost 50% depression patients face the risk of going into relapse. The risk increases to 80% after the second episode of depression. Although, depression detection from social media has attained considerable attention, depression relapse detection…
arXiv:2509.16444v1 Announce Type: new Abstract: Mental health applications have emerged as a critical area in computational health, driven by rising global rates of mental illness, the integration of AI in psychological care, and the need for scalable solutions in underserved…
arXiv:2509.18091v1 Announce Type: cross Abstract: Despite the growing interest in replicating the scaled success of large language models (LLMs) in industrial search and recommender systems, most existing industrial efforts remain limited to transplanting Transformer architectures, which bring only incremental improvements…
