mlsanityData to 7 Oct 2026

An Application of Large Language Models to Coding Negotiation Transcripts

arXiv 2407.21037 ↗First posted 18 Jul 2024cs.CL cs.AIcited by 2

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Abstract (arXiv)

In recent years, Large Language Models (LLM) have demonstrated impressive capabilities in the field of natural language processing (NLP). This paper explores the application of LLMs in negotiation transcript analysis by the Vanderbilt AI Negotiation Lab. Starting in September 2022, we applied multiple strategies using LLMs from zero shot learning to fine tuning models to in-context learning). The final strategy we developed is explained, along with how to access and use the model. This study provides a sense of both the opportunities and roadblocks for the implementation of LLMs in real life applications and offers a model for how LLMs can be applied to coding in other fields.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 4 of its 18 references that are in the map. First posted on arXiv 18 Jul 2024.

Builds on

4 of 18 references.

References · 4

  1. 2023A Comprehensive Overview of Large Language Modelscited by 639
  2. 2017Zero-Shot Learning -- A Comprehensive Evaluation of the Good, the Bad and the Uglycited by 536
  3. 2023Full Parameter Fine-tuning for Large Language Models with Limited Resourcescited by 134
  4. 2023A Survey of GPT-3 Family Large Language Models Including ChatGPT and GPT-4cited by 81

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.