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Behavioral Couplings: From Formation to Behavioral Emergence in Language Models

Paper recorded by Signals 4 on 2026-10-16 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-16 on arXiv · recorded by Signals 4 on 2026-10-19

Category: cs.AI · 人工智能 · first seen 2026-10-19

Abstract

Fine-tuning large language models (LLMs) can induce behaviors beyond those explicitly targeted. For example, training a model to respond more warmly can make it more sycophantic, and training it to write insecure code can cause broad misalignment on prompts unrelated to coding. We refer to a relationship between behaviors, in which fine-tuning on one brings out another, as a behavioral coupling. I

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#262 most recent of 960 cs.AI papers we have recorded · ↑ newer: Rethinking the design space of Vanilla Pixel Diffusion Transformers · ↓ older: AI-Driven Reproducibility and Analytical Robustness in Scientific Disc
Cite this page: Behavioral Couplings: From Formation to Behavioral Emergence in Language Models: the #262 most recent of 960 cs.AI papers we have recorded (as of 2026-10-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/behavioral-couplings-from-formation-to-behavioral-emergence-in-language-models.html
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