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small language model

3,524 papers

#large language models Open access Sep 2026

MergeRepair: An Exploratory Study on Merging Task-Specific Adapters in Code LLMs for Automated Program Repair

Abstract Large Language Models (LLMs) have shown high capabilities in several software development-related tasks such as program repair, documentation, code refactoring, debugging, and testing. However, training these models requires massive amount of data and significant computational resources. Adapters are specializ...

Meghdad Dehghan, Jie JW Wu, Fatemeh H. Fard et al. · 1 citation
#small language model Preprint Sep 2026

ARIS: Low-Resource Glass-Box Neural Source-Filter Synthesis for Phonetic Stimulus Manipulation

ARS (Analytic Resonant Interpretable Synthesis), a neural source-filter model that pairs neural parameter estimation with deterministic DSP synthesis, and every control is a coefficient of the synthesizer, so F0, formants and the glottal source can be edited directly.

Yi-Ran Ding, Wen-Wei Xu · 0 citations
#small language model Book Open access Sep 2026

BookForYou: Leveraging BART-Generated Narrative Tropes for Content-Based Book Recommendations

This paper presents BookForYou, a content-based book recommendation system where a fine-tuned BART model (139M parameters) generates structured narrative trope tags from book descriptions while Sentence-BERT retrieves candidates from a 42,350-book catalog. Candidates are re-ranked via late fusion of semantic similarity...

Ritu Rajesh Kanchi, Ruhul Amin Hazarika, Gopalakrishnan Thirumoorthy · 0 citations
#small language model Book Open access Sep 2026

PROMISE: Process Reward Models for Unlocking Test-Time Scaling Laws in Generative Recommendations

This work proposes Promise, a novel framework that integrates dense, step-by-step verification into generative models, and unlocks Test-Time Scaling Laws in recommender systems, demonstrating that by increasing inference compute, smaller models can match or surpass larger models.

Cheng-Cheng Guo, Kuo Cai, Yu Zhou et al. · 0 citations
#small language model Open access Sep 2026

The machine's PILOT: cooperation and authority in AI-driven open science

The machine's PILOT argues that cooperation between open science platforms, among them the Global Open Science Cloud, the African Open Science Platform, and the European Open Science Cloud, is secured not in the description of content, which inference increasingly supplies, but in the act by which one holder offers goo...

Francis P. Crawley · 2 citations
#small language model Open access Sep 2026

Adding a Thai N-gram Engram to Qwen3-ASR-0.6B: effects on transcription error, memory, and latency

Technical report, version 1.0.1, in English and Thai, deposited as a preprint. Both editions are included as PDF, in full, one file per language. This version expands the background and introduction, revises the academic prose in both languages, and corrects the parameter count and evaluation-protocol details. The repo...

Thanabodee Nammungkun · 0 citations

Can Small Language Models Learn Materials Synthesis From Limited Experiments? A ZnO‐to‐ZIF‐8 Case Study

We investigate whether small language models can learn synthesis–outcome relationships from a limited experimental dataset using ZnO‐to‐ZIF‐8 conversion as a case study. Several small language models are benchmarked against conventional machine‐learning methods under the same cross‐validation protocol. The best‐perform...

Ngo T. Que, Nguyen T. T. Duyen, Nguyen A. Duc et al. · 0 citations
#small language model Open access Sep 2026

Should Ads Be Assertive? A Meta-Analytic Review of the Effects of Assertive Language on Perceived Freedom Threat, State Reactance, and Persuasion Outcomes

Advertising messages often use assertive language to capture consumer attention and drive behavioral compliance, yet empirical evidence for its effectiveness remains inconclusive and contradictory across studies and contexts. This meta-analytic review synthesized 142 samples examining the effects of assertive language...

Tsz Hang Chu, Dandan Liu, Hongyuan Gan · 0 citations
#small language model Open access Sep 2026

Can Meaningful Plaintext Be Transformed into Voynich-Like Text That Cannot Be Uniquely Recovered? A Generative Experiment Using Multi-Stage Information-Loss Transformations

This study investigates a constructive question concerning Voynich-like text generation: can meaningful natural-language plaintext be used as source material, subjected to non-injective and deliberately information-losing transformations, and still produce localized word-form regularities resembling those observed in t...

Mamizu Hinata · 0 citations
#small language model Open access Sep 2026

NP-SEE: Structural Analysis of Historical and Undeciphered Writing Systems — A Non-Parametric Information-Theoretic Approach

Version 3.0 We applied the NP-SEE (Non-Parametric Structural Entropy Engine) v6.1 framework to eleven corpora of historical and literary symbolic representations: Voynich Manuscript (ZL3b + GC2a), Linear A, Linear B, Inca Quipu (Open Khipu Repository, 619 khipu, 54,403 cords), Proto-Elamite, Etruscan, Meroitic, Indus V...

Luca Lupinacci · 0 citations
#small language model Review Open access Sep 2026

Beyond technical capability: how institutional resistance shapes generative AI exposure in civil and environmental engineering occupations

This article introduces the Integrated Sociotechnical Exposure Framework (ISEF) to assess generative AI exposure in civil and environmental engineering by separating technical AI suitability (TA) from institutional resistance (IR). The contribution is an operational measurement framework, not a claim that instituti...

Yuxuan Chai · 0 citations
#small language model Open access Sep 2026

How Does a Generative AI and Agentic AI Course in Indore Support Career-Oriented AI Learning?

Artificial intelligence is becoming increasingly relevant across modern industries. Businesses are exploring AI for content creation, software development, data processing, customer support, research, marketing, and workflow automation. As AI applications continue to expand, learners need more than theoretical knowledg...

Upgrad (India) · 0 citations

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