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cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024

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…