mlsanityData to 14 Oct 2026

A Recipe For Building a Compliant Real Estate Chatbot

arXiv 2410.10860 ↗First posted 7 Oct 2024cs.CL cs.AIcited by 1

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Abstract (arXiv)

In recent years, there has been significant effort to align large language models with human preferences. This work focuses on developing a chatbot specialized in the real estate domain, with an emphasis on incorporating compliant behavior to ensure it can be used without perpetuating discriminatory practices like steering and redlining, which have historically plagued the real estate industry in the United States. Building on prior work, we present a method for generating a synthetic general instruction-following dataset, along with safety data. Through extensive evaluations and benchmarks, we fine-tuned a llama-3-8B-instruct model and demonstrated that we can enhance it's performance significantly to match huge closed-source models like GPT-4o while making it safer and more compliant. We open-source the model, data and code to support further development and research in the community.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 14 of its 22 references that are in the map. First posted on arXiv 7 Oct 2024.

Builds on

14 of 22 references.

References · 14

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
  2. 2024The Llama 3 Herd of Modelscited by 14,715
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  4. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  5. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  6. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  7. 2020Measuring Massive Multitask Language Understandingcited by 7,963
  8. 2017Deep reinforcement learning from human preferencescited by 3,912
  9. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,720
  10. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,724
  11. 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,276
  12. 2023LIMA: Less Is More for Alignmentcited by 1,100
2 more
  1. 2024Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluatorscited by 897
  2. 2024GenQA: Generating Millions of Instructions from a Handful of Promptscited by 35

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026A Concise Agent is Less Expert: Revealing Side Effects of Using Style Features on Conversational Agentscited by 1