small language model

Renewal structure and critical dimension of causal set d'Alembertians

Plain-language summary Causal set theory models spacetime as a discrete collection of events ordered by cause and effect. On such a set, the wave operator, the basic rule for how a field propagates, has to be built from counts of events in the past. These constructions are nonlocal: the value at one event depends on ev...

Renewal structure and critical dimension of causal set d'Alembertians

Plain-language summary Causal set theory models spacetime as a discrete collection of events ordered by cause and effect. On such a set, the wave operator, the basic rule for how a field propagates, has to be built from counts of events in the past. These constructions are nonlocal: the value at one event depends on ev...

Reducing Clinician Annotation Fatigue in Open-Set Federated Learning: A Client-Adaptive Vision-Language Gatekeeper.

PURPOSE Federated learning enables breast-imaging sites to jointly train mammography artificial intelligence (AI) without sharing images, but radiologists at each site must still annotate selected images during active-learning rounds. We developed and evaluated a client-adaptive vision-language gatekeeper that withhold...

Integrating online cooperative learning into the English as a foreign language writing curriculum: a modelling trial

Online learning has been reported to be increasingly used within Chinese higher education. The rapid expansion has created a problem that it’s difficult to carry out real-time learner interaction among a great number of students. The pure online instruction made the existing problems in university EFL teaching even wor...

Contamination Means Overestimation? A Fine-Grained Empirical Study in Code Intelligence

In recent years, code intelligence has gained increasing importance in the field of automated software engineering. Meanwhile, the widespread adoption of Pretrained Language Models (PLMs) and Large Language Models (LLMs) has raised concerns regarding data contamination and its potential impact on model performance eval...

Application of Retrieval-Augmented Generation Large Language Models in Stomatology: A Scoping Review

Large language models (LLMs) have been gradually applied to tasks such as specialized question answering, educational assistance, clinical decision support, and knowledge integration in stomatology. However, general-purpose LLMs still suffer from critical limitations, including outdated knowledge, hallucinatory generat...

FORTE: Adaptive Scoring and Exact Keyframe Selection for Long-Video Question Answering

This work introduces FORTE, a training-free framework that addresses the challenge of adaptive relevance scoring and global keyframe optimization through two stages: adaptive relevance scoring and global keyframe optimization.

Skeleton-and-Strategy Prompting: Training-Free Negation Understanding for Vision-Language Models

SSP first abstracts the underlying question structure into a skeleton, retrieves a small set of same-skeleton questions from a lightweight question pool, then prompts the VLM to analyze their shared negation pattern and synthesize a single-sentence answering strategy.

In silico designing of small molecules for targeting RNA: current landscape and future directions

Keyword Harnesses Fail Open: A Cheap Diagnostic Ladder for Tool-Use Claims in Small Language Models

Keyword-matching benchmarks can credit small models for tool use they never perform. We document such a false positive in a matched-architecture pair of Spanish security language models and propose a ladder of strict, cheap diagnostics. A 661.6M parameter model (approx. 65% code/technical text; no dedicated SFT) and a...

Old Ideas, Novel Problems: The Instability of LLM-Based Novelty Evaluation

Automated ideation systems are often evaluated on the novelty of the ideas they produce, and that judgment is increasingly delegated to large language models. Such judges are typically built ad hoc and validated, if at all, on human-authored papers rather than on the generated ideas they are meant to score. So, how do...

Yo-ByT5: Efficient and High-Fidelity Diacritic Restoration for Yor\`ub\'a

Yor\`ub\'a is a widely spoken tonal language that depends on diacritics to avoid lexical ambiguity. However, it is often written without these diacritics, thereby hindering downstream Natural Language Processing (NLP) tasks. In this paper, we introduce Yo-ByT5, a byte-level Automatic Diacritic Restoration (ADR) model f...