68 citations · 120 across the 16 of their papers we have counts for
5 papers · 1 filter
Agents Explore but Agents Ignore: LLMs Lack Environmental Curiosity
Leon Engländer, Sophia Althammer, Ahmet Üstün +2
LLM-based agents are assumed to integrate environmental observations into their reasoning: discovering highly relevant but unexpected information should naturally lead to a model e…
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…
Ranger: A Toolkit for Effect-Size Based Multi-Task Evaluation
Mete Sertkan, Sophia Althammer, Sebastian Hofstätter
In this paper, we introduce Ranger - a toolkit to facilitate the easy use of effect-size-based meta-analysis for multi-task evaluation in NLP and IR. We observed that our communiti…
Linguistically Informed Masking for Representation Learning in the Patent Domain
Sophia Althammer, Mark Buckley, Sebastian Hofstätter +1
Domain-specific contextualized language models have demonstrated substantial effectiveness gains for domain-specific downstream tasks, like similarity matching, entity recognition…