PulseAugur
EN
LIVE 01:09:51

Users struggle to control LLM reasoning despite system prompt instructions

Users are encountering difficulties in controlling the reasoning process of large language models, even when providing explicit instructions in system prompts. Despite attempts to limit token usage or prevent excessive drafting, models often continue to generate repetitive or wasteful reasoning steps. This issue persists across various models, including Gemma 4 26b, leading to inefficient token consumption and a lack of productive output in their thought processes. AI

IMPACT Users are seeking methods to improve the efficiency and controllability of LLM reasoning processes.

RANK_REASON User discussion on a technical challenge with LLMs.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/iz-Moff ·

    Why does it seems to be so difficult to control a model's reasoning process?

    <!-- SC_OFF --><div class="md"><p>I'm curious if anyone who is more familiar with the inner workings of LLMs can explain why does it seem like all reasoning models (or at least the ones i tried) always ignore any user instructions related to reasoning?</p> <p>Everyone probably ex…