9 citations · 30 across the 19 of their papers we have counts for
3 papers · 1 filter
Some things are more CRINGE than others: Iterative Preference Optimization with the Pairwise Cringe Loss
Jing Xu, Andrew Lee, Sainbayar Sukhbaatar +1
Practitioners commonly align large language models using pairwise preferences, i.e., given labels of the type response A is preferred to response B for a given input. Perhaps less…
Emergent Linear Representations in World Models of Self-Supervised Sequence Models
Neel Nanda, Andrew Lee, Martin Wattenberg
How do sequence models represent their decision-making process? Prior work suggests that Othello-playing neural network learned nonlinear models of the board state (Li et al., 2023…
Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models
Oana Ignat, Zhijing Jin, Artem Abzaliev +19
Recent progress in large language models (LLMs) has enabled the deployment of many generative NLP applications. At the same time, it has also led to a misleading public discourse t…