2.3k citations · 6.5k across the 77 of their papers we have counts for
7 papers · 2 filters
Grokking of Hierarchical Structure in Vanilla Transformers
Shikhar Murty, Pratyusha Sharma, Jacob Andreas +1
For humans, language production and comprehension is sensitive to the hierarchical structure of sentences. In natural language processing, past work has questioned how effectively…
Backpack Language Models
John Hewitt, John Thickstun, Christopher D. Manning +1
We present Backpacks: a new neural architecture that marries strong modeling performance with an interface for interpretability and control. Backpacks learn multiple non-contextual…
Meta-Learning Online Adaptation of Language Models
Nathan Hu, Eric Mitchell, Christopher D. Manning +1
Large language models encode impressively broad world knowledge in their parameters. However, the knowledge in static language models falls out of date, limiting the model's effect…
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback
Katherine Tian, Eric Mitchell, Allan Zhou +5
A trustworthy real-world prediction system should produce well-calibrated confidence scores; that is, its confidence in an answer should be indicative of the likelihood that the an…
MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions
Zexuan Zhong, Zhengxuan Wu, Christopher D. Manning +2
The information stored in large language models (LLMs) falls out of date quickly, and retraining from scratch is often not an option. This has recently given rise to a range of tec…
ReCOGS: How Incidental Details of a Logical Form Overshadow an Evaluation of Semantic Interpretation
Zhengxuan Wu, Christopher D. Manning, Christopher Potts
Compositional generalization benchmarks for semantic parsing seek to assess whether models can accurately compute meanings for novel sentences, but operationalize this in terms of…