Legal artificial intelligence (AI) systems increasingly draw on retrieval-augmented generation (RAG), transformerbased embeddings, multi-stage structured reasoning, and ensemble learning to support tasks such as legal question answering,
legal judgment prediction, and multilingual outcome prediction. Hallucination, lim...
Neeraja R. A., Sherin Shaji, Devende M. R. et al.· International Journal for Re...· 0 citations
Classical singing pedagogy relies on expert judgments that integrate auditory-perceptual cues, embodied pedagogical knowledge, and specialized evaluative language. This exploratory, longitudinal study proposes a cognitive framework, centered on Polanyi’s concept of tacit knowledge, for describing how experienced bel ca...
Kyoko Ikeda, Michiko Yamaguchi, 朱実 小畑 et al.· Frontiers in Psychology· 0 citations
While some promising adaptations to Family-Based Treatment were identified, the evidence-base remains limited by a predominance of small, uncontrolled studies and a lack of standardised outcome measures.
A. Cussen, Michele Yeo, Janet Conti et al.· Journal of Eating Disorders· 0 citations
Enterprise data pipelines have grown in scale and interdependency faster than the operational practices used to maintain them. Pipeline failures are still predominantly diagnosed and remediated by human engineers reading logs, tracing lineage, and applying tacit knowledge, which produces long mean-time-to-recovery and...
A. Kolla, Ameya Kokate· International Journal of Fro...· 0 citations
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Physical education (PE) offers opportunities for psychological learning, but evidence of benefit depends on the outcome, design, and instructional context.
This systematic review and multilevel meta-analysis included 74 reports from 70 trial families of primary-school PE interventions. Four databases covered...
Le-Bin Li, Yao-Jun Huang, Di Zhang et al.· Frontiers in Psychology· 0 citations
Keystroke logging has made second language (L2) writing visible as a sequence of pauses, production, cursor movement, and editing, yet much evidence is still analyzed through fixed pause cut-offs or isolated process measures. This study examined whether a window-level hidden Markov model (HMM) could provide an interpre...
Aitor Garcés-Manzanera· Research Methods in Applied...· 0 citations
The honeymoon ends. Within days or weeks of landing, most international students hit a sharp dip in confidence—the “arrival cliff”—when novelty stops compensating for cumulative friction: a missed bureaucratic deadline, a familiar gesture suddenly read as inappropriate, a class discussion that moves three steps ahead o...
Genevive Bjorn, Clara Fangfang Ma· Routledge eBooks· 0 citations
VR-FraudNet, a five-stage framework combining a time-conditioned spectral graph encoder, LightGBM triage and threshold routing, a schema-constrained rationale language model, a fixed deterministic verifier, and an isotonic probability mixer with split-conformal calibration, does not establish universal adversarial safe...
Md Sultanul Arefin Sourav, Evha Rozario, Md Ashiqul Islam et al.· Discover Artificial Intellig...· 0 citations
A controlled counterfactual audit of 80 recent English-language arXiv manuscripts shows that metadata perturbations can displace manuscripts and alter top-K shortlist membership, identifying a concrete reliability risk for LLM-assisted scientific evaluation pipelines.
Marco Rospocher· Discover Artificial Intellig...· 0 citations
The results show that harness-managed control flow can substantially improve the effectiveness of the smallest models and suggest that small models can be useful for repository repair when responsibilities are divided across explicit stages that can be independently assigned to the component best suited to each.
Francesco Dente, Dario Satriani, Donatello Santoro et al.· Proceedings of the 1st Inter...· 0 citations
Deploying Large Language Models (LLMs) on memory-constrained edge servers to serve requests from mobile devices is challenging due to their substantial resource demands. The Key-Value (KV) cache and Feed-Forward Network (FFN) parameters consume the majority of available memory. However, existing methods typically rely...
Zhong-Xiang Wei, Yi-Peng Zhou, Jin Zhao et al.· IEEE Transactions on Mobile...· 0 citations
OrthoPurify is proposed, a more efficient method to purify backdoored model weights via one-step orthogonal projection, which reduces the attack success rate to near zero while preserving the original performance across diverse benchmarks, without retraining the backdoored model or introducing inference-time overhead.
Bo Yang, Hao-Chen Zhou, Zhi-Fang Zhang et al.· 0 citations
