2024
Probing the Capacity of Language Model Agents to Operationalize Disparate Experiential Context Despite Distraction
EMNLP 2024finding
Large language model (LLM) agents show promise in an increasing number of domains. In many proposed applications, it is expected that the agent reasons over accumulated experience presented in an input prompt. We propose the OEDD (Operationalize Experience Despite Distraction) corpus, a human-annota…