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Open-source RL model enhances LLMs for sales applications

A new open-source Reinforcement Learning (RL) model has been developed to enhance Large Language Models (LLMs) for sales applications. This RL model is trained using numerical sales features and rules, rather than extensive text datasets, to predict optimal sales actions like 'pitch' or 'close'. The model's hidden features and action states are then injected into the LLM's residual flow to augment its responses, aiming to overcome the overly agreeable nature of current LLMs in sales scenarios. The project includes a PyPI package and GitHub repository, building upon prior research and a newly submitted arXiv paper. AI

IMPACT This tool could improve the effectiveness of LLMs in sales by providing more nuanced and strategic responses, potentially leading to better customer engagement and conversion rates.

RANK_REASON The item describes an open-source tool that integrates with existing LLMs, rather than a novel LLM release or core research breakthrough.

Read on r/LocalLLaMA →

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

Open-source RL model enhances LLMs for sales applications

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  1. r/LocalLLaMA TIER_1 English(EN) · /u/Nandakishor_ml ·

    Open-sourced an RL model to give LLM the sales strategies

    <!-- SC_OFF --><div class="md"><p>The main problem faced when using these LLMs for sales usage is that they are perfect, smooth, polite, always accepting, and agree with whatever I say, even with strict prompting; things always go for acceptance in the long run. The same for Fabl…