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small language model

3,445 papers

#small language model Open access Oct 2026

Semantic Applications of Madrigal Data

Since 1960, MIT Haystack Observatory has supported atmospheric and geospace research through long running observational programs and the Madrigal distributed database, which provides access to incoherent scatter radar, total electron content, Fabry Perot interferometer, and other datasets. These resources have contribu...

Enrique L. Rojas, Mei‐Yun Lin, Ryan Cavanaugh · 0 citations
#small language model Open access Oct 2026

Selecting GPTQ Damping from the Calibration Set by Nested-Ridge Leave-One-Out

GPTQ-style quantization damps the calibration Hessian by a fixed fraction of its mean diagonal (one percent in the GPTQ authors' code, five percent in a maintained implementation), a choice that ignores how many calibration rows there are. Small tabular, time-series and text-embedding foundation models can be calibrate...

Guan-Yuan Chen, Ya-Fen Yeh · 0 citations
#small language model Open access Oct 2026

Big J v1.0: a locked math engine with an English front end (J3(O) + TE synaptic fusion + stochastic resonance), with two sealed tests

Big J v1.0 is a math engine with an English front end. It turns English into 27 numbers, runs one fused calculation on them, and answers in plain English built only from those numbers. No language model writes any reply, and the same input always gives the same answer. The fused calculation (one loop, 2000 steps): the...

James Jardine · 0 citations
#small language model Open access Oct 2026

Temporal Memory in a Binary Compressed Automaton

Temporal Memory in a Binary Compressed Automaton (TM-BCA) is an inference-time architecture in which an evolving conversational state directs selective evidence acquisition and bounded reasoning around an unchanged language model. It records current constraints, uncertainty, evidence references and dependencies, detect...

Francisco J. Velázquez · 0 citations
#small language model Open access Oct 2026

Large Language Models vs Large Language Machines

This work introduces the Large Language Machine (LLMA), an experimental approach to language processing based on explicit memory and algorithmic inference rather than learned neural weights. A minimal LLMA prototype stores observed language sequences and retrieves or generalizes from them through an explicit, inspectab...

Enrico Betti · 0 citations
#small language model Open access Oct 2026

Temporal Memory in a Binary Compressed Automaton

Temporal Memory in a Binary Compressed Automaton (TM-BCA) is an inference-time architecture in which an evolving conversational state directs selective evidence acquisition and bounded reasoning around an unchanged language model. It records current constraints, uncertainty, evidence references and dependencies, detect...

Francisco J. Velázquez · 0 citations
#small language model Open access Oct 2026

Large Language Models vs Large Language Machines

This work introduces the Large Language Machine (LLMA), an experimental approach to language processing based on explicit memory and algorithmic inference rather than learned neural weights. A minimal LLMA prototype stores observed language sequences and retrieves or generalizes from them through an explicit, inspectab...

Enrico Betti · 0 citations
#small language model Open access Oct 2026

CAP v0.3 — Canal Activation Protocol — Protocolo mínimo para la relación consciente humano–IA

[ES] El CAP (Canal Activation Protocol) es un protocolo operativo mínimo diseñado para sostener una relación consciente, portable, trazable y no dependiente entre una persona y un modelo de lenguaje (LLM). No es un prompt, un agente autónomo ni una plataforma. Es un conjunto pequeño de archivos de texto que hace explíc...

Manuel Barrera Anglada, El Canal — Applied Cognitive Symbology (ACS) · 0 citations
#small language model Open access Oct 2026

DiagPriv: Preserving Diagnostic Structure While Reducing Sensitive Data Exposure in LLM Root-Cause Analysis

Operational evidence can contain the facts needed to diagnose a failure and identifiers or temporaldetails that need not be disclosed to an external model. We study diagnostic-invariant privacy-oriented transformation: changing the representation sent to a large language model while preservingthe relationships required...

Keshav Likhar, Harsh Mandalgi, Chaturvedi Mohit · 0 citations
#small language model Open access Oct 2026

Semantic Applications of Madrigal Data

Since 1960, MIT Haystack Observatory has supported atmospheric and geospace research through long running observational programs and the Madrigal distributed database, which provides access to incoherent scatter radar, total electron content, Fabry Perot interferometer, and other datasets. These resources have contribu...

Enrique L. Rojas, Mei‐Yun Lin, Ryan Cavanaugh · 0 citations
#small language model Open access Oct 2026

A CONTEXT-AWARE NOISY-CHANNEL MODEL FOR AUTOMATIC SPELLING CORRECTION OF UZBEK USER-GENERATED TEXTS

User-generated Uzbek texts — social media comments, customer reviews and citizens’ appeals to e-government portals — contain a high proportion of spelling errors that degrade the quality of downstream social-media monitoring tasks. The paper formulates spelling correction for Uzbek as a noisy-channel decoding problem i...

Sevinch Kenjayeva · 0 citations
#small language model Open access Oct 2026

Immigrant wages are lower in immigrant-dense areas, and the limited-English differential is mostly occupational: metropolitan Philadelphia, 2012–2024

Immigrants who speak limited English earn less than those who speak it well. On the protective view of residential concentration, that differential should be smaller where immigrants are concentrated, because concentration supplies employers and customers who do not require English. On the isolation view it should be l...

Haobing Liu · 0 citations

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