15 citations · 15 across the 5 of their papers we have counts for
5 papers · 1 filter
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…
Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models
Pat Verga, Sebastian Hofstatter, Sophia Althammer +6
As Large Language Models (LLMs) have become more advanced, they have outpaced our abilities to accurately evaluate their quality. Not only is finding data to adequately probe parti…
Two Approaches to Building Collaborative, Task-Oriented Dialog Agents through Self-Play
Arkady Arkhangorodsky, Scot Fang, Victoria Knight +3
Task-oriented dialog systems are often trained on human/human dialogs, such as collected from Wizard-of-Oz interfaces. However, human/human corpora are frequently too small for sup…
MeetDot: Videoconferencing with Live Translation Captions
Arkady Arkhangorodsky, Christopher Chu, Scot Fang +5
We present MeetDot, a videoconferencing system with live translation captions overlaid on screen. The system aims to facilitate conversation between people who speak different lang…
MEEP: An Open-Source Platform for Human-Human Dialog Collection and End-to-End Agent Training
Arkady Arkhangorodsky, Amittai Axelrod, Christopher Chu +6
We create a new task-oriented dialog platform (MEEP) where agents are given considerable freedom in terms of utterances and API calls, but are constrained to work within a push-but…