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Grammar Control for Language Learning with Sequential Monte Carlo and Small Language Models

Paper recorded by Signals 4 on 2026-10-29 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.CL · 自然语言处理 · first seen 2026-10-30

Abstract

Second language learners benefit from exposure to level-appropriate grammar in interactive language use. While prompted frontier language models can usually produce target grammar structures, less resource-intensive models that can be run on device often fail in this task. We use sequential Monte Carlo (SMC) to steer dialogue turn generation in small lan- language models toward target grammar cons

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#73 most recent of 628 cs.CL papers we have recorded · ↑ newer: KV Cache Quantization for Diffusion Language Models · ↓ older: The Role of Self-Concept In Language Models
Cite this page: Grammar Control for Language Learning with Sequential Monte Carlo and Small Language Models: the #73 most recent of 628 cs.CL papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/grammar-control-for-language-learning-with-sequential-monte-carlo-and-small-lang.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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