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small language model

3,629 papers

#small language model Book Open access Aug 2026

Towards Fully Automated Medical Imaging Code Generation via Validation-Based Context Engineering

This work proposes AutoMedImg, a multi-agent framework for fully automated medical image processing code generation that achieves zero human intervention, with Dice scores of up to 0.90 for segmentation tasks and 99% accuracy for classification.

Zi-Xiao Zhao, Jing Sun, Zhe Hou et al. · 0 citations
#small language model Open access Aug 2026

Automated scoring of adult ego development from sentence completions: interpretable maturity indicators derived by evolutionary prompt optimization

An automated scoring approach in which an evolutionary algorithm derives a small set of interpretable maturity indicators, each scored from sentence-completion responses by a domain-fine-tuned language model, supports automated ego-development scoring at agreement levels comparable to trained raters, and the indicators...

Tamas Madl, S. Cook-Greuter · 0 citations
#small language model Book Open access Oct 2026

Defensive Capability Analysis for JavaScript Libraries

A defensive capability analysis for JavaScript libraries that soundly reports every exercised capability for code executed under a lightweight protected runtime, complementing the static analysis with a lightweight runtime enforcement mechanism that blocks those patterns.

Wen-Yu Xu, Anders Møller · 0 citations
#natural language process... Preprint Sep 2026

Knowledge Distillation During Mid-Training Favors Reasoning over Factual Recall

Switch Distillation is proposed, a simple mid-training objective that distills on tokens where the teacher is confident, using teacher predictive entropy as a lightweight routing signal, and otherwise falls back to cross-entropy, which consistently outperforms existing distillation objectives across teacher sizes.

Jacqueline He, Howard Yen, S. Li et al. · 0 citations
#natural language process... Preprint Sep 2026

VerTox: Verifiable Reward-Guided Corpus Poisoning Against Neural Ranking Models

This work proposes VerTox, the first framework to formulate corpus poisoning as a verifiable reward-guided reinforcement learning (RLVR) problem, and produces adversarial documents that frequently rank higher than target documents across major neural ranking architectures, as well as a proprietary commercial embedding...

Zhi-Qi Huang, Vivek Datla, Zhichao Xu et al. · 0 citations
#natural language process... Preprint Sep 2026

Subword Segmental BabyLMs: Learning to Tokenise for Sample-Efficient Pretraining

The results show that learnable subword tokenisation can improve sample-efficiency for BabyLM pretraining and analyse the subword learning dynamics of the models and find that tokenisation gradually converges on subword units that balance morphological alignment and fine-grained segmentation.

Francois Meyer · 0 citations
#natural language process... Preprint Sep 2026

A Certificate-Producing Cascade for Equational Implication: The SAIR EQT2 Stage 2 Solver

A single-file solver organized as a cheapest-first cascade is presented, which combines coefficient tests over structured algebra families, bounded finite-model search, an explicit central-groupoid witness, and several infinite-carrier witnesses and makes no completeness or comparative-superiority claim.

Hao Ma, Wen-Lin Zhang, Manuel Israel Cazares · 0 citations
#machine learning Preprint Sep 2026

The Structure of Quantization Damage in LLMs: Why the Next Bit Should Be Spent Globally

Post-training quantization (PTQ) is widely used to reduce the cost of serving large language models (LLMs), but its accuracy cost is uneven and is often tuned per model. We study where quantization damage occurs and how to allocate a small additional precision budget. Using causal mixed-precision intervention as ground...

Jun-Hao Hu, S. Ramachandran · 1 citation
#machine learning Preprint Sep 2026

CRAFT: Fine-Tuning Pre-hoc Explainability in AI-native 6G RAN

CRAFT, which stands for Cold-start Reasoning Alignment Alignment via Fine-Tuning, is proposed, a data-centric method to autonomously generate a verified dataset of (input, trace, label) triplets, requiring substantially less compute and wall-clock time than GRPO-based methods.

Pranshav Gajjar, V. K. Shah · 0 citations
#artificial intelligence Preprint Sep 2026

CordisBench: Can Language Models Reason About Component Lifecycles in Dynamic Agent Harnesses?

CrisBench, a 1,200-question benchmark of lifecycle reasoning that combines a controlled formal setting with programs executed against Cordis, a runtime that manages component dependencies and cleanup, and asks models to identify affected components, predict state after a specified teardown order, and determine which co...

Damien Sileo, Dimitri Kachler · 1 citation

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