3 citations · 8 across the 6 of their papers we have counts for
7 papers
Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)
Liwei Jiang, Yuanjun Chai, Margaret Li +7
Language models (LMs) often struggle to generate diverse, human-like creative content, raising concerns about the long-term homogenization of human thought through repeated exposur…
FlexOlmo: Open Language Models for Flexible Data Use
Weijia Shi, Akshita Bhagia, Kevin Farhat +20
We introduce FlexOlmo, a new class of language models (LMs) that supports (1) distributed training without data sharing, where different model parameters are independently trained…
(Mis)Fitting: A Survey of Scaling Laws
Margaret Li, Sneha Kudugunta, Luke Zettlemoyer
Modern foundation models rely heavily on using scaling laws to guide crucial training decisions. Researchers often extrapolate the optimal architecture and hyper parameters setting…
FLAME: Financial Large-Language Model Assessment and Metrics Evaluation
Jiayu Guo, Yu Guo, Martha Li +1
LLMs have revolutionized NLP and demonstrated potential across diverse domains. More and more financial LLMs have been introduced for finance-specific tasks, yet comprehensively as…
A Taxonomy of Ambiguity Types for NLP
Margaret Y. Li, Alisa Liu, Zhaofeng Wu +1
Ambiguity is an critical component of language that allows for more effective communication between speakers, but is often ignored in NLP. Recent work suggests that NLP systems may…
Breaking the Curse of Multilinguality with Cross-lingual Expert Language Models
Terra Blevins, Tomasz Limisiewicz, Suchin Gururangan +4
Despite their popularity in non-English NLP, multilingual language models often underperform monolingual ones due to inter-language competition for model parameters. We propose Cro…
In-context Pretraining: Language Modeling Beyond Document Boundaries
Weijia Shi, Sewon Min, Maria Lomeli +9
Large language models (LMs) are currently trained to predict tokens given document prefixes, enabling them to directly perform long-form generation and prompting-style tasks which…