4 papers
Co-LMLM: Continuous-Query Limited Memory Language Models
Yair Feldman, Linxi Zhao, Nathan Godey +5
Limited memory language models (LMLMs) externalize factual knowledge during pretraining to a knowledge base (KB), rather than memorizing it in their weights. During generation, the…
Post-training for Efficient Communication via Convention Formation
Yilun Hua, Evan Wang, Yoav Artzi
Humans communicate with increasing efficiency in multi-turn interactions, by adapting their language and forming ad-hoc conventions. In contrast, prior work shows that LLMs do not…
Evaluating the Utility of Grounding Documents with Reference-Free LLM-based Metrics
Yilun Hua, Giuseppe Castellucci, Peter Schulam +2
Retrieval Augmented Generation (RAG)'s success depends on the utility the LLM derives from the content used for grounding. Quantifying content utility does not have a definitive sp…
Success and Cost Elicit Convention Formation for Efficient Communication
Saujas Vaduguru, Yilun Hua, Yoav Artzi +1
Humans leverage shared conversational context to become increasingly successful and efficient at communicating over time. One manifestation of this is the formation of ad hoc lingu…