10 citations · 19 across the 8 of their papers we have counts for
9 papers
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…
To Err is AI : A Case Study Informing LLM Flaw Reporting Practices
Sean McGregor, Allyson Ettinger, Nick Judd +10
In August of 2024, 495 hackers generated evaluations in an open-ended bug bounty targeting the Open Language Model (OLMo) from The Allen Institute for AI. A vendor panel staffed by…
AI as Humanity's Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Text
Ximing Lu, Melanie Sclar, Skyler Hallinan +8
Creativity has long been considered one of the most difficult aspect of human intelligence for AI to mimic. However, the rise of Large Language Models (LLMs), like ChatGPT, has rai…
WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models
Liwei Jiang, Kavel Rao, Seungju Han +8
We introduce WildTeaming, an automatic LLM safety red-teaming framework that mines in-the-wild user-chatbot interactions to discover 5.7K unique clusters of novel jailbreak tactics…
WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs
Seungju Han, Kavel Rao, Allyson Ettinger +5
We introduce WildGuard -- an open, light-weight moderation tool for LLM safety that achieves three goals: (1) identifying malicious intent in user prompts, (2) detecting safety ris…
When Hindsight is Not 20/20: Testing Limits on Reflective Thinking in Large Language Models
Yanhong Li, Chenghao Yang, Allyson Ettinger
Recent studies suggest that self-reflective prompting can significantly enhance the reasoning capabilities of Large Language Models (LLMs). However, the use of external feedback as…
The Generative AI Paradox: "What It Can Create, It May Not Understand"
Peter West, Ximing Lu, Nouha Dziri +11
The recent wave of generative AI has sparked unprecedented global attention, with both excitement and concern over potentially superhuman levels of artificial intelligence: models…
Can You Follow Me? Testing Situational Understanding in ChatGPT
Chenghao Yang, Allyson Ettinger
Understanding sentence meanings and updating information states appropriately across time -- what we call "situational understanding" (SU) -- is a critical ability for human-like A…
"You Are An Expert Linguistic Annotator": Limits of LLMs as Analyzers of Abstract Meaning Representation
Allyson Ettinger, Jena D. Hwang, Valentina Pyatkin +2
Large language models (LLMs) show amazing proficiency and fluency in the use of language. Does this mean that they have also acquired insightful linguistic knowledge about the lang…