7 citations · 11 across the 8 of their papers we have counts for
5 papers · 1 filter
Bayesian Fine-tuning Yields Language Models that are as Bayesian as their Beliefs Allow
Polina Tsvilodub, Andreas Waldis, Linlu Qiu +2
Language models (LMs) are increasingly used for tasks that require reasoning about hidden variables from a few observations, for which Bayesian inference is the normatively correct…
ELF: Embedded Language Flows
Keya Hu, Linlu Qiu, Yiyang Lu +5
Diffusion and flow-based models have become the de facto approaches for generating continuous data, e.g., in domains such as images and videos. Their success has attracted growing…
Learning User Simulators with Turing Rewards
Yingshan Susan Wang, Cedegao E. Zhang, Linlu Qiu +5
Learning to simulate human users in interactive settings could advance the training of agent assistants, evaluation of personalization systems, research in the social sciences, and…
DUEL: Adversarial Self-Play for Multimodal Reasoning
Lin Qiu, Hanqing Zeng, Yao Liu +3
Reinforcement learning (RL) has emerged as an effective paradigm for improving the reasoning capability of vision-language models (VLMs). However, RL-based optimization typically d…
Implicit Representations of Grammaticality in Language Models
Yingshan Susan Wang, Linlu Qiu, Zhaofeng Wu +2
Grammaticality and likelihood are distinct notions in human language. Pretrained language models (LMs), which are probabilistic models of language fitted to maximize corpus likelih…