3.1k citations · 3.1k across the 14 of their papers we have counts for
5 papers · 1 filter
From Narrow Unlearning to Emergent Misalignment: Causes, Consequences, and Containment in LLMs
Erum Mushtaq, Anil Ramakrishna, Satyapriya Krishna +5
Recent work has shown that fine-tuning on insecure code data can trigger an emergent misalignment (EMA) phenomenon, where models generate malicious responses even to prompts unrela…
PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards
Prasoon Goyal, Scott Niekum, Raymond J. Mooney
Reinforcement learning (RL), particularly in sparse reward settings, often requires prohibitively large numbers of interactions with the environment, thereby limiting its applicabi…
Using Natural Language for Reward Shaping in Reinforcement Learning
Prasoon Goyal, Scott Niekum, Raymond J. Mooney
Recent reinforcement learning (RL) approaches have shown strong performance in complex domains such as Atari games, but are often highly sample inefficient. A common approach to re…
Nonparametric Variational Auto-encoders for Hierarchical Representation Learning
Prasoon Goyal, Zhiting Hu, Xiaodan Liang +2
The recently developed variational autoencoders (VAEs) have proved to be an effective confluence of the rich representational power of neural networks with Bayesian methods. Howeve…
Voted Kernel Regularization
Corinna Cortes, Prasoon Goyal, Vitaly Kuznetsov +1
This paper presents an algorithm, Voted Kernel Regularization , that provides the flexibility of using potentially very complex kernel functions such as predictors based on much hi…