small language model

PREreview of "Comparative Analysis of Explainable AI for Depression Risk Assessment Based on Digital Behavior of University Students"

This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/23110671. 1. Introduction and research objectives We find the research question relevant, particularly the attempt to make predictions about students' mental health more interpretab...

Automatic Spoken Word Recognition for Very Low-Resource Languages: A Comparison Between Zero-Shot and Siamese Approaches in Two Indigenous Languages

Beyond Constrained Decoding: Grammar-Aware Fine-Tuning for Small Language Models

PREreview of "Design and Implementation of a Self-Service Kiosk with Embedded Analytics and Demand Forecasting for Small Retail Decision Support"

This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/23108434. Major issues Reliance on simulated rather than real-world retail data limits the generalization of the study. Limited validation with actual small retail users or operatio...

PREreview of "Comparative Analysis of Explainable AI for Depression Risk Assessment Based on Digital Behavior of University Students"

This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/23110671. 1. Introduction and research objectives We find the research question relevant, particularly the attempt to make predictions about students' mental health more interpretab...

Harness-Driven Progressive Detail: Making Stateless and Small Language Models Do Bounded Agentic Work — An Implementation Report under PSOS and LMCP

Agentic coding and operations work is usually delegated to a model running an open tool loop: the model decides each next step, re-reads its growing transcript every turn, and stops when it believes it has finished. That arrangement is affordable on a provider with prompt caching, where each turn pays only for new toke...

Harness-Driven Progressive Detail: Making Stateless and Small Language Models Do Bounded Agentic Work — An Implementation Report under PSOS and LMCP

Agentic coding and operations work is usually delegated to a model running an open tool loop: the model decides each next step, re-reads its growing transcript every turn, and stops when it believes it has finished. That arrangement is affordable on a provider with prompt caching, where each turn pays only for new toke...

Building AI Systems That Work Offline: An Offline-First Architecture and Feasibility Assessment for Low-Connectivity Environments

Artificial intelligence applications increasingly rely on continuous cloud connectivity for inference, data synchronization, and model updates. This dependency limits their applicability in regions where Internet access is intermittent, costly, or unavailable, such as rural schools and other resource-constrained settin...

Building AI Systems That Work Offline: An Offline-First Architecture and Feasibility Assessment for Low-Connectivity Environments

Artificial intelligence applications increasingly rely on continuous cloud connectivity for inference, data synchronization, and model updates. This dependency limits their applicability in regions where Internet access is intermittent, costly, or unavailable, such as rural schools and other resource-constrained settin...

AEGIS: Real-Time Latent-Space Backdoor Detection for Dependable and Secure Small Language Model Inference

Backdoor attacks pose a serious threat to small language models (SLMs) because compromised models can behave normally on benign inputs while producing attacker-specified outputs when a hidden trigger is activated. Existing defenses commonly require model retraining, operate only before deployment, rely on input-level s...

AiDER: Auditing and Document Evaluation via Rule Compilation and Small Language Models – An Education Case Study

Reviewing documents against natural-language requirements is hard when those requirements demand interpretation, contextual evidence, and non-trivial judgment. It is even harder when the review is to be automated reliably and made auditable. In domains like education, where teaching materials must align with pedagogica...

Structuring Intelligence: Agent-Based Decomposition for Tabular Reasoning with Small Language Models