25 citations · 56 across the 7 of their papers we have counts for
3 papers · 1 filter
Reason first, then respond: Modular Generation for Knowledge-infused Dialogue
Leonard Adolphs, Kurt Shuster, Jack Urbanek +2
Large language models can produce fluent dialogue but often hallucinate factual inaccuracies. While retrieval-augmented models help alleviate this issue, they still face a difficul…
Boosting Search Engines with Interactive Agents
Leonard Adolphs, Benjamin Boerschinger, Christian Buck +8
This paper presents first successful steps in designing search agents that learn meta-strategies for iterative query refinement in information-seeking tasks. Our approach uses mach…
How to Query Language Models?
Leonard Adolphs, Shehzaad Dhuliawala, Thomas Hofmann
Large pre-trained language models (LMs) are capable of not only recovering linguistic but also factual and commonsense knowledge. To access the knowledge stored in mask-based LMs,…