5 papers
Incremental Summarization for Customer Support via Progressive Note-Taking and Agent Feedback
Yisha Wu, Cen Mia Zhao, Yuanpei Cao +4
We introduce an incremental summarization system for customer support agents that intelligently determines when to generate concise bullet notes during conversations, reducing agen…
Agent-in-the-Loop: A Data Flywheel for Continuous Improvement in LLM-based Customer Support
Cen Mia Zhao, Tiantian Zhang, Hanchen Su +8
We introduce an Agent-in-the-Loop (AITL) framework that implements a continuous data flywheel for iteratively improving an LLM-based customer support system. Unlike standard offlin…
Command A: An Enterprise-Ready Large Language Model
Team Cohere, :, Aakanksha +227
In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases. Command A is an agent-optimised…
Diversity Enhances an LLM's Performance in RAG and Long-context Task
Zhichao Wang, Bin Bi, Yanqi Luo +2
The rapid advancements in large language models (LLMs) have highlighted the challenge of context window limitations, primarily due to the quadratic time complexity of the self-atte…
Rate, Explain and Cite (REC): Enhanced Explanation and Attribution in Automatic Evaluation by Large Language Models
Aliyah R. Hsu, James Zhu, Zhichao Wang +11
LLMs have demonstrated impressive proficiency in generating coherent and high-quality text, making them valuable across a range of text-generation tasks. However, rigorous evaluati…