small language model

Cell line screening of AI-generated drug repurposing predictions for NF2-related schwannomas

Non-NF2 schwannomatosis (SWN) is a rare syndrome that causes nerve sheath tumors with complex genetic variations and poorly understood modifiers. With no approved pharmacologic interventions, there is an urgent need for treatments that prevent or reduce tumor growth, or that ameliorate schwannoma-associated pain. Many...

The Truthometer: A Structured Cited Verdict, a Rulebook for the Claims No Register Settles, and a Distilled Judge

Paper 5 shows that for the commercial web, truth is a register join rather than a judgement, and that grounding in retrieved evidence is what makes verification work. This paper is the system that follows, and its contribution is threefold: the score, the rulebook, and the distillation boundary. **The Veracity Score.**...

The Truthometer: A Structured Cited Verdict, a Rulebook for the Claims No Register Settles, and a Distilled Judge

Paper 5 shows that for the commercial web, truth is a register join rather than a judgement, and that grounding in retrieved evidence is what makes verification work. This paper is the system that follows, and its contribution is threefold: the score, the rulebook, and the distillation boundary. **The Veracity Score.**...

Full-Layer Memory Injection via Compile-Time Key-Value Caches: An External-Knowledge Mechanism for Small-Parameter Language Models

Knowledge of large language models (LLMs) is frozen in parameters after pretraining and hard to update at low cost. This paper proposes a full-layer memory injection method based on compile-time key-value (KV) caches. Experiments on Qwen3-0.6B show full-layer token-level KV injection raises private-specification QA sco...

Evaluation of Vanilla and RAG-Supported LLM Comprehension of the EU AI Act

A comparative benchmarking study evaluating the regulatory comprehension of four open-source large language models, TinyLlama-1.1B-Chat, Gemma-2B-Instruct, Llama-3.1-8B-Instruct, and Mistral-7B-Instruct-v0.3, contributes an empirical characterization of small and medium language model regulatory comprehension and a reu...

Interpretable Subgroup Discovery with Abstention in Small, Heterogeneous Clinical Trials: A Retrospective Multi-Dataset Study

Small, heterogeneous clinical datasets pose a challenge for whole-cohort prediction because clinically meaningful treatment or response patterns may be diluted across biologically diverse patients. We describe and evaluate NetraAI, an interpretable dynamical-systems framework for selective subgroup discovery that uses...

Large language models in healthcare semantics

AI for Recruitment Administration

Measuring the waits a hiring process creates, and keeping the record it owes Four working days of internal approval are three weeks of silence on the other side, and almost every complaint about hiring is a complaint about that gap rather than about the decision at the end of it. Recruitment administration is a queue w...

Operation Waffles: AI-Mediated Lexical Drift and Distributed Framing Effects

Operation Waffles proposes a harmless proof-of-concept for studying whether large language models can introduce measurable lexical drift into human language. The paper suggests using an innocuous tracer term—“waffles”—to test whether small model-level preferences for particular words, metaphors, or phrasings survive in...

A voice-biomarker foundation model for ALS monitoring and Parkinson’s screening

Speech production integrates respiratory, laryngeal, articulatory, prosodic, linguistic and executive control, so neurodegeneration can leave measurable acoustic traces before conventional clinical scales change. Two decades of work have identified credible candidate speech and voice biomarkers for amyotrophic lateral...

The Person to Content Coupling: A Low Dimensional, State Dependent Field Between Disposition and Character

Personality science compresses a person into a small readable coordinate system, and the content science of the companion papers does the analogous thing for writing, eight character axes that collapse to two interpretable dimensions, matter against manner and originality. This paper reports the coupling between those...

Reconstructing wireless signals for low altitude networks using small language models

In-Context Signal Completion (ICSC) is presented, demonstrating that small language models fine-tuned with Group Relative Policy Optimization and physics-informed rewards can reconstruct RSSI across sequential extrapolation and spatial interpolation tasks.